19° Seminário Internacional de Alta Tecnologia
Inovações Tecnológicas no Desenvolvimento do Produto
Editor
Prof. Dr.-Ing. Klaus Schützer
Lab. de Sistemas Computacionais para Projeto e Manufatura
Faculdade de Engenharia, Arquitetura e Urbanismo
09 de Outubro de 2014
Universidade Metodista de Piracicaba
Teatro UNIMEP - Campus Taquaral, Piracicaba, SP
Lab. de Sistemas Computacionais para Projeto e Manufatura Prof. Dr.-Ing. Klaus Schützer FEAU - UNIMEP
Arte e Edição:
André Fagionatto de Castro Bruna Sakamoto
Dhiogenes dos Santos Sousa
Seminário Internacional de Alta Tecnologia (19. : 2014 : Piracicaba, SP)
S471a Anais do 19. Seminário Internacional de Alta Tecnologia, Piracicaba, SP, Brasil, 09 out., 2014 / editor Klaus Schützer. – Piracicaba: UNIMEP, 2014. 234 p. : il. ; 30 cm.
Tema central: Inovações tecnológicas no desenvolvimento do produto
ISSN 2175-9960
1. Seminários (Estudo) - Tecnologia de ponta. I. Schützer, Klaus. II. Título.
CDU – 62
I
Universidade Metodista de Piracicaba
A Universidade Metodista de Piracicaba (UNIMEP) é herdeira de uma tradição de mais de
265 anos em educação, iniciada em 1748, com a fundação da Kingswood School, primeira
escola Metodista na Inglaterra. Desta semente inicial, a educação metodista se expandiu,
alcançando atualmente mais de 775 instituições presentes em 70 países, em todos os
continentes. Inúmeras delas são universidades renomadas, como a Emory University
(Geórgia, EUA), Duke University (Carolina do Norte, EUA), American University (Washington
DC, EUA), Southern Methodist University (Texas, EUA), Roehampton University (Londres,
Reino Unido), Africa University (Zimbabwe), Aoyama Gakuin University (Tókio, Japão),
Hiroshima Jogakuin University (Hiroshima, Japão), Yonsei University e Ewha Womans
University (Seoul, Coréia do Sul), Boston University (Massachusetts, EUA) e a Southwestern
University (Texas, EUA), dentre outras. Destas duas últimas, saíram cinco prêmios Nobel,
quatro na área de medicina e um na área de química. Entre os ex-alunos, destacam-se
personalidades como Martin Luther King, responsável pela revolução dos Direitos Humanos
nos Estados Unidos, na década de 1960.
No Brasil, a educação metodista está completando 133 anos, contando atualmente com duas
universidades: UNIMEP e Universidade Metodista de São Paulo - UMESP; dois centros
universitários, Instituições com cursos da Educação Infantil à Superior e mais de vinte que
atuam desde creches até o Ensino Básico e Fundamental; três Faculdades de Teologia e seis
Seminários Teológicos Regionais, que agregam um universo de aproximadamente 62 mil
estudantes. No total são 52 instituições associadas à Rede Metodista de Educação no Brasil,
além de unidades especiais, como a Escola de Música de Piracicaba “Maestro Ernst Mahle”.
A Universidade Metodista de Piracicaba - UNIMEP, com aproximadamente 11.200
estudantes distribuídos em seus quatro campi, localizados nas cidades de Piracicaba, Santa
Bárbara d’Oeste e Lins, matriculados em 53 cursos de graduação, incluindo os cursos
superiores de tecnologia, 20 especializações (26 turmas), 7 mestrados e 4 doutorados, tem
a certeza de estar oferecendo uma educação diferenciada e de qualidade, baseada nos
princípios de sua Política Acadêmica, que tem como premissa a construção da cidadania
como patrimônio da sociedade.
A UNIMEP possui inúmeras parcerias com universidades de renome das Américas do Sul,
Central e do Norte, mantendo, também, parcerias e projetos com a Europa, Ásia e alguns
países da África. Dentre as principais parceiras destaca-se a Darmstadt University of
Technology na Alemanha, com a qual a UNIMEP desenvolve projetos de pesquisa,
intercâmbio de professores e estudantes, além da organização conjunta deste Seminário
Internacional.
II
Além da Darmstadt University of Technology, a UNIMEP mantém convênios com Marietta
College, University of Evansville, Universidad del Centro Educativo Latinoamericano
(Argentina), Universidad Madero (México), Universidad del Sevilla (Espanha), Technische
Universitat Berlin (TUB), Fraunhofer Institut für Produktionsanlagen und Konstruktionstechnik
(Fraunhofer IPK) e Nagasaki Wesleyan University (Japão). A Assessoria para Assuntos
Internacionais também realiza programas para aprendizado de línguas estrangeiras, como
inglês e espanhol. Não só envia alunos para o exterior, mas também recebe muitos alunos
para realizar estudos de curta ou longa duração, na graduação ou pós-graduação.
Mantendo a tradição de inovação e participação na comunidade, professores e alunos da
UNIMEP têm se destacado nas pesquisas e publicações, no intenso aproveitamento dos mais
de 100 laboratórios disponíveis, na prestação de serviços a empresas e à comunidade, no
desenvolvimento de um ambiente de estudos que favorece a convivência e o trabalho
conjunto, e no incentivo à busca das mais variadas oportunidades profissionais, através de
estágios supervisionados e convênios com indústrias, órgãos públicos e universidades no
Brasil e no exterior.
Faculdade de Engenharia, Arquitetura e Urbanismo
A Faculdade de Engenharia, Arquitetura e Urbanismo (FEAU)/UNIMEP, localizada em Santa
Bárbara d’Oeste, oferece sete cursos de Engenharia (Produção, Controle e Automação,
Mecânica, Alimentos, Química, Elétrica e Civil), Bacharelado em Química, Arquitetura e
Urbanismo e Tecnologia em Processos Químicos. Além disso, oferece um Programa de Pós-
graduação “stricto sensu” (Mestrado e Doutorado) em Engenharia de Produção.
Atualmente a FEAU tem cerca de 2.200 alunos nos cursos de graduação e pós-graduação.
Conta também com um corpo docente de 70 professores, sendo cerca de 55% em regime de
dedicação integral ou parcial. Cerca de 80% do corpo docente é titulado, sendo que 32
professores já concluíram o doutorado no Brasil ou no exterior. Este corpo docente tem
possibilitado o desenvolvimento de diversos projetos de pesquisa com financiamento de
órgãos governamentais (FAPESP, FINEP, CNPq, Capes, etc.), da iniciativa privada (Sandvik,
Indústrias Romi, Siemens PLM, Hexagon Metrology, Eletrocast, IBM entre outros) ou ainda
de organismos externos (DAAD, DFG, etc.).
A FEAU conta com 36 laboratórios para ensino e/ou pesquisa, entre eles um dos mais
modernos laboratórios para ensino de CAD e CAM dentre as universidades brasileiras, além
de duas Salas Ambiente que representam uma nova proposta para o uso da informática no
ensino da engenharia. Alguns de seus laboratórios de pesquisa têm se destacado no Brasil
III
e no exterior pelo trabalho desenvolvido, como nas áreas de sistemas CAD/CAM e PLM,
usinagem com altíssima velocidade, metrologia, materiais carbonosos, dentre outros.
A FEAU tem uma inserção bastante grande junto aos órgãos públicos, ONGs e no parque
industrial e de serviços regionais, que compreende além da região de Piracicaba, a região
Metropolitana de Campinas, através de convênios e projetos. A Incubadora de Empresas de
Santa Bárbara d’Oeste é gerida pela FEAU através de um de seus professores. Além disso,
a Faculdade mantém um forte contato internacional com Universidades e Instituições de
Pesquisa principalmente na Alemanha, Espanha, Bélgica, EUA e Argentina, através de
programas de intercâmbio entre professores, pesquisadores e alunos de graduação e pós-
graduação.
Laboratório de Sistemas Computacionais para Projeto e Manufatura
O Laboratório de Sistemas Computacionais para Projeto e Manufatura (SCPM) é um dos
mais de 30 laboratórios da Faculdade de Engenharia, Arquitetura e Urbanismo (FEAU) da
Universidade Metodista de Piracicaba. Na sua maioria, esses laboratórios estão voltados
primordialmente ao ensino, possibilitando aos estudantes um primeiro contato com a
realidade que enfrentarão no mercado de trabalho.
O SCPM, no entanto, foi criado com foco na pesquisa, residindo aí o seu diferencial, ou seja,
sua finalidade primeira é possibilitar a iniciação científica, através de projetos a serem
desenvolvidos pelos estudantes sob supervisão de professores. Esse é o papel que vem
desempenhando ao longo dos seus 19 anos de existência, sem descuidar da preservação da
indissociabilidade das duas outras colunas de sustentação de uma universidade, ou seja, o
ensino e a extensão.
Como uma das primeiras atividades, o Laboratório instalou os equipamentos de informática
recebidos através de dois projetos, o KIT #123 - FBaseDsgn, financiado pela Comissão
Europeia, e o projeto para implantação de infraestrutura, financiado pelo Deutsche
Ausgleichsbank. Em torno desse trabalho aglutinou-se um grupo de alunos de graduação e
pós-graduação que ajudou no planejamento e organização da primeira versão do que se
tornou o Seminário Internacional de Alta Tecnologia. O primeiro evento, em 1996, introduziu
no Brasil a temática da “Usinagem com Altíssima Velocidade de Corte”, que hoje é tema de
pesquisa em várias universidades e aplicada em diversas empresas.
Este grupo de pesquisa criou também o Núcleo para Projeto e Manufatura Integrados (NPMI),
incluído no Cadastro Nacional de Grupos de Pesquisa do CNPq desde 1995, e que oferece
IV
a interface para integração de outros professores e pesquisadores aos trabalhos
desenvolvidos no SCPM, além de participar ativamente de projetos de pesquisa em parceira
com outras universidades brasileiras.
O SCPM conta hoje com uma equipe de pesquisadores em tempo integral composta de 1
professor titular, 1 professor colaborador além de doutorandos, mestrandos, alunos de
iniciação científica e pessoal técnico de apoio. As atividades científicas desenvolvidas são
financiadas na sua maioria com recursos gerados através de projetos de pesquisa nacionais
e internacionais além da prestação de serviços e projetos em parceria com diversas
empresas. A estratégia de desenvolver seus projetos de pesquisa o mais próximo possível
das indústrias viabiliza uma rápida implementação dos resultados tecnológicos obtidos.
Reunir parceiros para desenvolver projetos mais arrojados tem sido a marca do trabalho do
SCPM, o que resultou em parcerias estratégicas desde a sua criação com o Institut für
Produktionsmanagement, Technologie und Werkzeugmaschinen (PTW) e com o Fachgebiet
Datenverarbeitung in der Konstruktion (DiK), ambos da Technische Universität Darmstadt na
Alemanha. Essas parcerias já resultaram em inúmeros projetos de pesquisa em conjunto e
um contínuo intercâmbio de alunos de graduação, mestrado e doutorado, além de
professores de ambos os lados.
Desde 2005 o SCPM possui também uma parceria com o Institut für Werkzeugmaschinen
und Fabrikbetrieb (IWF) da Technische Universität Berlin, Alemanha, e mais recentemente
com a Hochschule Rhein-Main em Rüsselsheim.
O SCPM dispõe de modernos recursos de hardware e software para o desenvolvimento dos
trabalhos de pesquisa atuando em quatro linhas de pesquisa: desenvolvimento integrado do
produto, usinagem com altíssima velocidade, monitoramento do processo de usinagem e
fábrica digital, além de oferecer suporte a pequenas e médias empresas para especificação,
escolha e implementação de sistemas CAD/CAPP/CAM/PDM.
Adicionalmente o SCPM possui uma Máquina de Medir por Coordenadas e um Sistema de
Calibração Laser Renishaw, que possibilitam o desenvolvimento de projetos de pesquisa
tanto com o foco na integração digital da cadeia CAD/CAM/CAQ, como também no
desenvolvimento de métodos para comparação da representação de superfícies complexas
nos sistemas CAD e o modelo real após a usinagem, permitindo a avaliação de estratégias
de corte e métodos de interpolação da trajetória da ferramenta.
Procurando atender às novas necessidades de empresas de pequeno e médio porte, o SCPM
iniciou trabalhos de pesquisa voltados ao Gerenciamento do Ciclo de Vida do Produto
(Product Data Management - PDM; Product Lifecycle Management - PLM). E hoje possui uma
V
plataforma de testes e uma equipe de alunos de graduação e pós-graduação (GAP - Grupo
de Aplicação de PDM) desenvolvendo simulações do processo de gerenciamento de dados
do produto ao longo de todo o ciclo de desenvolvimento.
Ainda dentro de seu objetivo de trabalhar com sistemas computacionais que representem o
estado da arte, o SCPM criou um grupo de trabalho para atuar no Planejamento Digital de
Processos tendo como foco o desenvolvimento de competências para atuar na temática
Fábrica Virtual e hoje já realiza projetos de pesquisa nesta área com renomadas empresas.
O material didático desenvolvido pela equipe do SCPM nas áreas de projeto e manufatura
auxiliados por computador tem sido utilizado não só nos cursos de engenharia da FEAU, mas
também por muitas outras universidades de diferentes lugares do Brasil. Esta atuação
pautada pelo trinômio pesquisa-ensino-extensão tem sido um importante processo re-
alimentador de todo o trabalho.
Desta maneira, o SCPM, além de uma forte inserção na área de pesquisa, tem conseguido
interagir de maneira positiva na definição das grades curriculares dos cursos de engenharia,
trazendo o que existe de mais inovador em desenvolvimento integrado do produto
contemplando desde a concepção até a manufatura.
Atualmente o SCPM desenvolve projetos financiados pelo CNPq e pelo BMBF-DLF e possui
outros em processo de avaliação junto às agências: CAPES, CNPq, FAPESP e DFG.
Mesmo enfrentando as dificuldades e os desafios inerentes à conjuntura brasileira e a uma
universidade particular, o projeto do SCPM visa uma formação ampla de seus pesquisadores
e estudantes, enfatizando o aspecto da pesquisa e a inserção internacional de sua equipe
através de intercâmbios, destacando-se assim dentro do projeto institucional como um
moderno provedor de serviços, dedicado às necessidades dos alunos que atuam no
laboratório, das indústrias com as quais tem desenvolvido projetos e da sociedade no seu
todo.
Universidade Metodista de Piracicaba
Faculdade de Engenharia, Arquitetura e Urbanismo
Lab. de Sistemas Computacionais para Projeto e Manufatura
Rod. Luis Ometto (SP 306), Km 24
13.451-900 Santa Bárbara d´Oeste, SP
Tel: (19) 3124-1792 Fax: (19) 3124-1788
E-mail: [email protected]
Home Page: http://www.unimep.br/scpm
VI
Parceiros SCPM
VII
Apresentação
O Laboratório de Sistemas Computacionais para Projeto e Manufatura (SCPM) realiza desde
1996 o Seminário Internacional de Alta Tecnologia, abordando temas focados em duas
grandes áreas: Manufatura e Desenvolvimento Integrado do Produto, alternadamente.
Dentro desses temas, seu Comitê Científico busca as inovações que estão sendo
implantadas com sucesso na indústria, e já no primeiro evento realizado trouxe para o Brasil
o tema da Usinagem com Altíssima Velocidade de Corte (High Speed Cutting - HSC).
Hoje este evento é reconhecido como um referencial no Brasil na divulgação de novas
tecnologias e métodos de trabalho, devido à atualidade e ao nível técnico dos temas
abordados, atraindo a atenção e a participação de pessoal técnico qualificado das mais
renomadas empresas localizadas no Brasil e de professores e pesquisadores de diversas
universidades.
Vencendo os desafios do desenvolvimento do Produto
Atualmente as empresas estão enfrentando grandes desafios devido à crescente
internacionalização da competição que vem sendo orquestrada por concorrentes mais
eficientes ou até mesmo mais agressivos, seja pela capacidade de inovação de alguns, seja
pelos baixos custos e escala de produção de outros. Isto tudo em um ambiente econômico e
político que demanda grande esforço e dedicação no planejamento estratégico visando o
futuro do país.
Para serem bem sucedidas as empresas precisam oferecer produtos inovadores, com time
to market reduzido, preços competitivos e com forte viés de sustentabilidade, características
estas que devem ser estabelecidas já na fase de desenvolvimento do produto e de forma
conectada com clientes e fornecedores.
Pesquisas sobre perspectivas nas áreas de Engenharia do Produto e Engenharia de
Processo demonstram que é necessário o acompanhamento minucioso, praticamente em
tempo real, do processo de desenvolvimento do produto, conjugado com o desenvolvimento
dos processos de produção com vistas a buscar a otimização do todo. Isso somente é
possível por meio da aplicação de tecnologias inovadoras nas várias fases do ciclo do
produto.
É considerando esse contexto que os organizadores do evento buscaram identificar as
inovações que vêm sendo geradas em projetos de pesquisa e desenvolvimento que já estão
sendo implantados com sucesso na indústria. Nos países desenvolvidos as perspectivas da
Engenharia do Produto apoiam-se em programas como o Industrie 4.0 na Alemanha e em
VIII
conceitos e tecnologias como Produtos e Sistemas Físico-cibernéticos, Smart Products,
aplicação de modelos humanos e o Frontloading, entre outros, no Japão e Estados Unidos.
É com essa visão que convidamos as comunidades industrial e acadêmica brasileiras para
participarem da 19ª edição do Seminário Internacional de Alta Tecnologia onde estaremos
discutindo os desafios que se apresentam no desenvolvimento do produto com o objetivo de
gerar novas ideias e soluções que serão determinantes para o sucesso das empresas.
Visando contribuir para a consolidação de um processo inovador no desenvolvimento de
produtos o evento deste ano abordará os seguintes temas:
4ª Revolução Industrial (“Industrie 4.0”)
Produtos e componentes físico-cibernéticos
Avaliação virtual da aplicação do produto
Modelos humanos biomecânicos
Sistemas PLM – ágeis e de arquitetura aberta
Frontloading e o desenvolvimento de novos produtos
Cooperação internacional universidade empresa
IX
Comitê Científico
Prof. Dr.-Ing. Klaus Schützer - SCPM - FEAU - UNIMEP, Brasil - Presidente
Prof. Dr. Alexandre T. Simon - PPGEP - UNIMEP - Editor Técn. Revista Máquinas e Metais
Prof. Dr. Alvaro J. Abackerli - IPT
Dr.-Ing. Bernd Pätzold - ProSTEP AG, Alemanha
Prof. Dr.-Ing. Dirk Bierman - IST - TU Dortmund, Alemanha
Prof. Dr.-Ing. Eberhard Abele - PTW - TU Darmstadt, Alemanha
Prof. Dr. h.c. Dr.-Ing. Eckart Uhlmann - Fraunhofer IPK, Alemanha
Prof. PhD. Elso Kuljanic - Università degli Studi di Udine, Itália
Prof. Tit. Dr.-Ing. Henrique Rozenfeld - NUMA - EESC - USP, Brasil
Prof. Dr. Jan Helge Bøhn - Virginia Tech University, Estados Unidos da América
Prof. Dr.-Ing. Michael Abramovici - Ruhr-Universität Bochum, Alemanha
Prof. MSc. Patrick G. Serraferro - Ecole Centrale de Lyon, França
Prof. Dr. Pedro Filipe Cunha - Escola Superior de Tecnologia de Setúbal, Portugal
Prof. Dr.-Ing. Rainer Stark - IWF - TU Berlin, Alemanha
Prof. Habil. Dr.-Ing. Ralph H. Stelzer - KTC - TU Dresden, Alemanha
Prof. Habil. Dr.-Ing. Reiner Anderl - DiK - TU Darmstadt, Alemanha
Prof. Dr. Reginaldo Teixeira Coelho - NUMA - EESC - USP, Brasil
Dr.-Ing. Teresa De Martino - European Commission - Directorate General XIII, Bélgica
Prof. Dr. Sc. Toma Udiljak - Croatian Association of Production Engineering, Croácia
X
Comitê Organizador
Prof. Dr.-Ing. Klaus Schützer – Presidente
Marcela Santana da Silva Romão – Secretária Executiva
Quinhones de Santana – Analista de Suporte
MSc. Carlos Eduardo Miralles
MSc. Renato Luis Garrido Monaro
Eng. Bruna Sakamoto
Eng. Dhiogenes dos Santos Sousa
Eng. Tiago Cacossi Picarelli
André Fagionatto de Castro
Felipe Alves de Oliveira Perroni
Florian Wolf
Gabriel Gaiotto Tezoto
Gabriel Abhener Medeiro Martins
Luiz Guilherme Luchiari Ferrari
Marcelo Octávio Tamborlin
Matheus Franco Soares
Sebastian Mack
Realização
Lab. de Sistemas Computacionais para Projeto e Manufatura Prof. Dr.-Ing. Klaus Schützer FEAU - UNIMEP
XI
Índice
Industrie 4.0 - Advanced Engineering of Smart Products and Smart Production ............................................................................................... 3
Prof. Dr.-Ing. Reiner Anderl, Technical University Darmstadt - DiK, Germany
Os Desafios e as Estratégias Nacionais para Tecnologia e Inovação ................................................................................................................ 29
Prof. Dr. Alvaro Toubes Prata, MCTI - Governo Federal, Brasil
Virtual Assessment of Product Use Based on Biomechanical Human Models ...................................................................................... 31
Prof. Dr.-Ing. Sandro Wartzack, KTmfk - FAU, Germany
Daniel Krüger, KTmfk - FAU, Germany
Jörg Miehling, KTmfk - FAU, Germany
Integrated Component Data Model for Smart Production Planning 59
Dipl.-Ing. André Picard, Technical University Darmstadt - DiK, Germany
Prof. Dr.-Ing. Reiner Anderl, Technical University Darmstadt - DiK, Germany
Cooperação com Universidades Alemãs: Oportunidades para a Indústria no Brasil ................................................................................ 81
Marcio Weichert, Centro Alemâo de Ciência e Inovação - DWIH, Brasil
Frontloading is a Key Success Factor and a Basis for Efficiency and Effectiveness of NPI Projects .............................................................. 95
Dr. Andreas Romberg, STAUFEN.Táktica - Consultoria.Academia Ltda., Brazil
Recent Approaches of CAD/CAE Product Development. Tools, Innovations, Collaborative Engineering ........................................... 119
Dr.-Ing. Peter Binde - Dr. Binde Ingenieure, Design & Engineering GmbH, Germany
XII
Additive Manufacturing in the Product Development ..................... 131
Dr. Jorge Vicente Lopes da Silva - CTI Renato Archer, Brazil
Bosch Engineering System – A Robust Design Process and 3D Model Applied in the Complete Product Development Chain ........ 173
MSc. Eng. Erwin Karl Franieck - Robert Bosch Ltda., Brazil
Processo de Desenvolvimento de Produtos Aeronáuticos ........... 191
MSc. Eng Waldir Gomes Gonçalves - Embraer S.A., Brasil
PLM na Magneti Marelli Cofap: Compartilhando um Caminho, Dificuldades e Desafios na Implantação Globalizada ..................... 203
Mauro Conceição - Magneti Marelli Cofap, Brasil
1
Artigos Técnicos
Technical Papers
2
Prof. Dr.-Ing. Reiner Anderl
Prof. Anderl was born in 1955 and studied mechanical engineering at
the Universität Karlsruhe, Germany, where he received his diploma in
1979. He received the Dr.-Ing. degree in Mechanical Engineering at
the Universität Karlsruhe in 1984. From 1984 to 1985 he served as
technical manager of a medium sized company. He then returned as
a senior engineer to the Institute for Applied Computer Science in
Mechanical Engineering (RPK) at the Universität Karlsruhe. In 1991
he has habilitated and in 1992 he has received the Venia Legendi,
which includes the authorization to teach CAD/CAM technology. In
April 1993 he accepted the call for the professorship for computer
integrated design (Fachgebiet Datenverarbeitung in der Konstruktion,
DiK) at the faculty Mechanical Engineering, Technische Universität
Darmstadt,Germany. At the Technische Universität Darmstadt, he
served as the dekan (dean) of the faculty in Mechanical Engineering
from 1999 until 2001, during which time the new bachelors and
masters program in mechanical engineering, mechatronics, and
computational engineering was defined and implemented; the first of
such in Germany. He has served on numerous faculty and university
committees and commissions, including serving as prodekan where
he managed the mechanical engineering faculty business office. He
is a member of the Zentrale Evaluierungs- und Akkreditierungs-
agentur (ZEvA), a national accreditation council based in Hannover,
Germany, where he works on issues related to bachelor- and master-
program accreditation. Prof. Anderl has served as vice president at
the Technische Universität Darmstadt from January 2005 until
December 2010.
DiK, TU Darmstadt
The Department of Computer Integrated
Design (DiK) is part of the Faculty of
Mechanical Engineering of the Technische
Universität Darmstadt. The integration of
information technology as integral part of
modern mechanical engineering and the
linkage of research and education to
industrial needs are our fundamental targets.
The principles and methods of processing
product data even today are developing
rapidly. To understand product data, product
data flows and product data processing, a
holistic approach named Product Data
Technology (PDT) has been chosen for
education and research. The scientific
strategy of the DiK is based on four main
research fields: “Information Modeling”,
“Virtual Product Creation", ”Collaborative
Engineering” and “Digital Factory. These
research fields contribute significantly to the
scientific progress of Virtual Product
Development and Virtual Factory and support
the creation of advanced competencies to
enable new innovation and strengthen
industrial competitiveness.
3
Industrie 4.0 - Advanced Engineering of Smart
Products and Smart Production
Abstract
Industrie 4.0 is a strategic approach for integrating advanced control systems with internet
technology enabling communication between people, products and complex systems. The
key approach is to equip future products and production systems with embedded systems
as a basis for smart sensor and smart actuators for enabling communication and intelligent
operation control. These so-called Cyber-Physical-Systems challenge design and
development processes and require appropriate engineering approaches. Within this
contribution the state–of-the-art for Industrie 4.0 is being presented, key use cases are
reported and an approach for establishing Industrie 4.0 in industry is presented. In this
context, a fundamental issue is to understand the role of integrated safety, security, privacy
and knowledge protection.
Keywords
Industrie 4.0; smart engineering; smart sensors; smart actuators; safety and security;
multidisciplinary product development; mechatronics; adaptronics, cyber-physical
systems.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
4
1 Introduction
Industrie 4.0 implies the 4th industrial revolution and is one of the German research initiatives
to implement the German high-tech strategy 2020 [1] to meet the challenges of the 21st
century. While the 1st industrial revolution is considered as the introduction of hydro power
and steam power, the 2nd industrial revolution is understood as the introduction of mass-
production techniques by using electric energy. The 3rd industrial revolution is based on the
application of electronic systems and information technology for enhancing manufacturing
automation. A significant breakthrough is now expected as the 4th industrial revolution by
introducing so-called cyber-physical systems (see Figure 1) [2, 3, 4, 5].
Figure 1: Industry 4.0 - The 4th industrial revolution (source:Zukunftsprojekt Industrie 4.0 [3])
The fundamental approach of Industrie 4.0 is using the ability of cyber-physical systems to
provide intelligence and communication for artificial, technical systems, which then are called
smart systems. Smart systems may be understood as a consequent successor technology of
mechatronic and adaptronic systems. The main feature is the integration of cyber-physical
systems for enabling inter-system communication and self-controlled system operation. Smart
systems are to be used for condition monitoring, structural health monitoring, remote diagnosis
and remote control. They are a kernel component for smart products, smart factories, smart
grids, smart logistics or even the smart city (see Figure 2). The intension for introducing smart
systems is the establishment of new value-added processes and new value-added networks
to increase and to improve flexibility, adaptability and efficiency of business processes.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
5
Figure 2: The smart system approach
Business processes based on smart systems will also open the gate to establish
fundamentally new business models where the functionality of smart systems will be extended
with integrated services. This new packaging of systems’ functionality and services will enable
new approaches to meet customer and market demands.
Within this contribution the approach of Industrie 4.0 will be explained and use case scenarios
will be presented. Furthermore, the approach of transferring Industrie 4.0 to the industry in
Germany will be illustrated as well as some international activities to strengthen industrial
competitiveness based on smart systems.
2 Fundamental Approaches of Industrie 4.0 Technology
Industrie 4.0 technology aims at enabling communicating, intelligent and self-controlled
systems. From a technological point of view, Industrie 4.0 is characterized by 4 fundamental
conceptual approaches. They comprise:
Cyber-physical systems,
Internet technology,
Components as information carriers and
Holistic safety and security including privacy and knowledge protection.
The combination of these conceptual approaches enable smart systems as a kernel feature
of Industrie 4.0 applications.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
6
2.1 Cyber-Physical Systems
The approach of cyber-physical systems has been described by LEE [6] as an intersection of
the theory of computation and the theory of dynamic systems. This results in two
complementary approaches called
Cyberizing the physical:
Cyberizing the physical aims at specifying physical subsystems with computational
abstractions and interfaces. This also leads to equip physical subsystems with
intelligence enabled e.g. through embedded systems. Furthermore, communication
becomes an important feature to interact with both, other cyber-physical systems as well
as humans.
Physicalizing the cyber:
Physicalizing the cyber expresses abstractions of dynamic systems to software and
interfaces as well as network components to represent their dynamic behavior in time.
Cyber-physical systems may be understood as a consequent configuration of embedded
systems, sensors, actuators including network access. Figure 3 shows a configuration
approach that enables the creation of cyber-physical systems and its further application as
cyber-physical production systems.
Figure 3: Cyber-physical systems
In cyber-physical systems network access can be provided in particular by equipping
embedded systems with an internet protocol address (IP address).
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
7
2.2 Internet Technology
Modern and future internet technology provides essential approaches to enhance the
performance of cyber-physical systems. These internet technology approaches comprise 3
concepts:
The internet of things (IoT):
The internet of things comprises communicating smart systems using IP addresses. The
upcoming IPv6 (internet protocol version 6) supports an IP address space of 128 bits
which enables to define 2^128 individual addresses or 3.4*10^38 addresses. This
enables each and every physical object being equipped with a unique IP-address.
The internet of services (IoS):
The internet of services comprises new service paradigms such as provided by the
service oriented architecture (SOA) [11] or the REST-technology [8] .
The internet of data (IoD):
In an environment of the previously mentioned internet of things and internet of services
technologies huge amount of data will be generated. The internet of data will enable to
transfer, to store mass data appropriately, and to provide new and innovative analysis
methods to interpret mass data in the context of the target application.
Figure 4 illustrates the internet technology impact on cyber-physical systems.
Figure 4: Impact of modern and future internet technology
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
8
As a consequence new industrial topics such as big data and could computing are gaining an
increasing importance.
2.3 Manufacturing Objects as Information Carriers
The approach of cyber-physical systems enables objects to be identified, localized and
addressed. Assigned to manufacturing objects such as single parts and assemblies this
technology opens new innovation paths. Manufacturing object become information carriers as
well as connected objects in a network of communicating instances. Manufacturing history
assigned to manufacturing objects create individual object information which is essential for
successive manufacturing processes and backtracing analysis.
Furthermore, manufacturing objects are connected to product model structures as well as
process planning data and thus they are enabled to actively control their own manufacturing
processes and procedures. Figure 5 illustrates an example of a manufacturing object, the
bottom of a pneumatic cylinder. The bottom part is identified and by analyzing its product
structure, its assembly is detected and through the assembly the assigned assembly plan, the
assembly area as well as the appropriate counter parts are accessed. This scenario also
shows how optimization for assembly processes is supported.
Figure 5: Manufacturing objects as information carriers
To support the concept of manufacturing objects becoming information carriers an appropriate
specification of information attached to manufacturing objects is required. This requirement
can be met by specifying a so-called component data model. The component data model is
derived from the product data model approach as available through the STEP standard
(Standard for the Exchange of Product Model Data, ISO 10303 “Product Data Representation
and Exchange [7]).
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
9
2.4 Holistic Approach for Safety, Security, Privacy and Knowledge Protection
Cyber-physical systems equipped with internet technology (IoT, IoS and IoD) require
outstanding concepts and technologies for to ensure safety, security, privacy and knowledge
protection. These concepts have to be applied in a real-time environment, which typically
addresses manufacturing environments. Figure 6 compares issues of the office-oriented
environments with those issues typically addressed by manufacturing environments.
Figure 6: Synchronous versus asynchronous application environments [9]
Safety requirements address the continuously available manufacturing operation ability while
security aims at the resilience against external and internal attacks against the cyber-physical
environment.
Privacy ensures the execution of operational functions without being monitored to a third
instance. Furthermore, knowledge protection provides methods and tools to avoid access to
manufacturing knowledge from outside or from non-authorized instances.
Clearly, Industrie 4.0 concepts require IT safety and security to be tied closely to physical
manufacturing processes also meeting real-time requirements.
3 Use Case Scenarios
Industrie 4.0 is expected to change the industry significantly. One of major changes is to
further develop process management, which today is strongly depending on centralized
methods to more de-centralized but interlinked methods. Planning and control of processes
will become much more flexible, adaptable and resilient against disruption. Some use case
scenarios illustrate expected benefits.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
10
3.1 Use Case 1 “Component as an Information Carrier”
Provided that components as manufacturing objects are identifiable or even addressable their
current status will be registered individually. Use case 1 addresses manufacturing failures and
its effect analysis. After having manufactured the bottom of the pneumatic cylinder the part is
checked and verified against product design data in particular its dimensions and tolerances.
The measurement indicates dimensions not meeting tolerance requirements (see Figure 7).
Figure 7: Checking and verifying manufactured parts
As a consequence the reasons why tolerances are not met have to be detected. Therefore,
effect analysis is appropriate and in this case the manufacturing plan indicates which
manufacturing process is responsible for the failure. Through the manufacturing process the
machine tool and the operation tool are identified and their conditions are being analyzed (see
Figure 8).
In this use case it becomes evident that the operation tool (red curve in the right picture of
Figure 8) approaches the end of its lifetime.
Figure 8: Manufacturing plan and monitoring of the operation tool
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
11
3.2 Use Case 2 “Process and Condition Monitoring”
Process and condition monitoring is one of the most important use cases. As products or
components of products are based on cyber-physical systems their smart sensors are able to
deliver data about the products’ or the components’ condition. Such data might be e.g.
temperature, strain or vibration. The analysis and assessment of the data streams deliver
information about the products’ or components’ condition. Consequently, process monitoring
methods can be supplied with information indicating the process stability or instability [10].
Actions to ensure process stability such as load balancing and predictive maintenance can be
taken. Figure 9 illustrates process monitoring in a manufacturing environment.
Figure 9: Process monitoring in a manufacturing environment
While this use case has a high impact on the efficiency of respective value-added processes,
this use case also underlines the high importance of analyzing promptly data streams
produced by smart sensors. This is considered as an area where significant development of
new innovation is expected.
3.3 Use Case 3 “Additive Manufacturing”
A very promising use case comprises additive manufacturing. This upcoming technology uses
3D-CAD data to drive a layer-by-layer manufacturing process. Data representing a spare part
is delivered from a 3D-CAD system and is exported either as a STEP file or as a STL file. This
description of the parts’ geometry is used to compute ordered slices of the parts’ geometry.
For each of these slices the tool path is generated and used to control the tool operation to
produce the part layer by layer (see Figure 10).
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
12
Figure 10: Additive manufacturing based on fused deposition manufacturing
The attractiveness of these use case results from locating additive manufacturing centers in
the main markets worldwide and controlling the production by sending manufacturing control
data to the appropriate additive manufacturing unit. Equipped with cyber-physical systems the
additive manufacturing unit will report back about the successful production or in case of any
problems also reports will be sent back. This scenario is in particular of interest for producing
spare parts (Figure 11).
Figure 11: Use case “Additive Manufacturing”
Furthermore, also statistical data could be reported back indicating the frequency of produced
parts in the various market worldwide.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
13
4 Transferring Industrie 4.0 to Industry
Industrie 4.0 an important research initiative to implement the German high-tech strategy. A
report about the transfer of the conceptual approach of Industrie 4.0 to German industry has
been delivered to the German government in spring 2013. Industry itself has taken action to
drive the implementation of Industrie 4.0. The main activity is the establishment of the so-
called Platform Industrie 4.0 under the organizational auspices of 3 industrial associations
BITKOM (ICT industry), VDMA (mechanical and process industry) and ZVEI (electrical and
automation industry). Figure 12 shows the organizational structure of the Platform Industrie
4.0.
Figure 12: Platform Industrie 4.0 [14]
A major approach is the collaboration between industry and the scientific community through
the initiation of a scientific advisory board. An important contribution of the scientific advisory
board was the definition of 17 theses explaining the main features of Industrie 4.0 (see Figure
13).
In the meantime, a research roadmap has been published and a number of research projects
have been initiated to contribute to the Industrie 4.0 technology. Furthermore, a couple of
demonstration centers for Industrie 4.0 have been established (Figure 14).
Industrie 4.0 has created awareness in both, German industry and academia. The technology
development, however, has also been started internationally. The European Commission has
published a research initiative on advanced manufacturing [12], in the United States the
Industrial Internet Consortium [13] has been established and further initiatives have been
started in China, South Korea and Japan. This confirms the strong movement to make the
Internet of Things, the Internet of Services and the Internet of Data a reality.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
14
Figure 13: Theses of the scientific advisory board of the Platform Industrie 4.0 [15]
Figure 14: Research roadmap and demonstration centers for Industrie 4.0 [14]
5 Summary
Industrie 4.0 has become an important initiative for German industry. It is of strategic
importance and aims at strengthening industrial competitiveness. The main features driving
Industrie 4.0 are the development of cyber-physical systems, the integration of the internet of
things, the internet of services and the internet of data technology, the understanding of
components being information carriers and the implementation of a holistic approach to
ensure safety, security, privacy and knowledge protection.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
15
The main target is to improve the value-added processes and to develop new business models
for strengthening industrial competitiveness. Future research activities will focus on smart
systems development, vertical and horizontal process integration and seamless digital
integration of lifecycle phases.
6 References
[1] N.N.
Hightech-Strategy 2020 for Germany
http://www.hightech-strategie.de/en/350.php
access: August 13th, 2012
[2] N.N.
Industry 4.0
http://www.hightech-strategie.de/de/2676.php
Access: August 13th, 2012
[3] Kagermann, H.; Wahlster, W.; Held, J.; (Hrsg.)
Bericht der Promotorengruppe Kommunikation. Im Fokus: Das Zukunftsprojekt
Industrie 4.0. Handlungsempfehlungen zur Umsetzung
Forschungsunion, 2012
[4] Broy, M.; (Hrsg.)
Cyber-Physical Systems. Innovation durch Software-intensive eingebettete
Systeme
acatech DISKUTIERT. Springer Verlag, Berlin Heidelberg, 2010
[5] acatech (Hrsg.)
Cyber-Physical Systems. Innovationsmotor für Mobilität, Gesundheit, Energie und
Produktion
acatech POSITION. Springer Verlag, Berlin Heidelberg, 2011
[6] Lee, E. A.: CPS Foundations. In: Proceedings of the 47th Design Automation
Conference (DAC). ACM/IEEE, June, 2010, S. 737 – 742
[7] Anderl, R., Strang, D., Picard, A., Christ, A.
Integriertes Bauteildatenmodell für Industrie 4.0 – Informationsträger für cyber-
physische Produktionssysteme. In: Zeitschrift für den Wirtschaftlichen
Fabrikbetrieb (ZWF), 109 (2014, 1-2), 64-69.
[8] Steinmetz C., Christ, A., Anderl R.
Data Management based on Internet Technology using RESTful Web Services In:
Proceedings 10th International Workshop on Integrated Design Engineering
IDE September 2014, Gommern, Germany
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
16
[9] Grimm, M.;., Anderl R.; Wang, Y.
Conceptual Approach for Multidisciplinary Cyber-Physical Systems Design and
Engineering. In: Proceedings of TMCE 2014, ISBN 978-94-6186-177-1
Budapest Hungary 2014
[10] Picard, A.; Anderl, R.
Smart Production Planning for Sustainable Production based on Federative
Factory Data Management. In: Proceedings of TMCE 2014 (Horvath I., Rusak Z.,
eds.). Budapest , pp. 1147-1156. ISBN 978-94-6186-177-
[11] Picard, A.; Anderl, R.; Schützer, K.; Moura, A. Alvaro de Assis :
Linked Product and Process Monitoring in Smart Factories based on Federative
Factory Data Management. ASME 2013 International Mechanical Engineering
Congress and Exposition, Volume 11: Emerging Technologies San Diego,
California, USA
[12] N.N.
Adavanced Manufacturing – Advancing Europe: Report of the Task Force on
Advanced Manufacturing and Clean Production
http://ec.europa.eu/enterprise/flipbook/ADMA/#/1/zoomed
European Union 2014; accessed August 15th, 2014
[13]N.N.
Industrial internet Consortium
http://www.iiconsortium.org/
Accessed August 15th, 2014
[14]N.N.
Plattform Industrie 4.0
http://www.plattform-i40.de/
Accessed August 15th, 2014
[15]N.N.
acatech: Thesen des Wissenschaftlichen Beirats
http://www.acatech.de/fileadmin/user_upload/Baumstruktur_nach_Website/Acatec
h/root/de/AktuellesPresse/PresseinfosNews/ab_2014/Industrie_4.0_Broschuere.pd
f
Accessed August 15th, 2014
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
17
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
18
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
19
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
20
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
21
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
22
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
23
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
24
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
25
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
26
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
27
28
Prof. Dr. Alvaro Toubes Prata
Secretário Executivo do Ministério da Ciência, Tecnologia e Inovação.
É professor titular do Departamento de Engenharia Mecânica da
Universidade Federal de Santa Catarina, UFSC. Possui graduação
em Engenharia Mecânica e em Engenharia Elétrica pela
Universidade de Brasília, mestrado em Engenharia Mecânica pela
Universidade Federal de Santa Catarina e doutorado em Engenharia
Mecânica pela Universidade de Minnesota, EUA. Há 36 anos na
UFSC, atua na graduação e pós-graduação, coordenando projetos de
ensino, pesquisa e extensão. Já publicou mais de 230 artigos
científicos completos em periódicos e anais de congressos, orientou
41 dissertações de mestrado e 20 teses de doutorado - possui duas
patentes depositadas. Em função de sua reconhecida atuação em
pesquisa e ensino em nível de pós-graduação, é pesquisador nível
1A no CNPq. De 2000 a 2004 foi pró-reitor de pesquisa e pós-
graduação da UFSC e ocupou a presidência do Fórum Nacional de
Pró-Reitores de Pesquisa e Pós-Graduação das Instituições de
Ensino Superior. É reconhecido com a Comenda da Ordem Nacional
do Mérito Científico - Classe Grã Cruz, dirigida a personalidades que
se distinguem por relevantes contribuições à ciência. Recebeu o
Prêmio Anísio Teixeira por ocasião do 60 aniversário da CAPES, em
reconhecimento à sua grande contribuição ao desenvolvimento das
Instituições Educacionais, Científicas e Tecnológicas no Brasil, por
meio do magistério, da pesquisa e da liderança institucional. De maio
de 2008 a maio de 2012 foi reitor da UFSC e por dois mandatos
ocupou a Vice-Presidencia da Associação Nacional dos Dirigentes
das Instituições Federais de Ensino Superior. É membro titular da
Academia Brasileira de Ciências, e coordena o Instituto Nacional de
Ciência e Tecnologia em Refrigeração e Termofísica. Suas áreas de
pesquisa são transferência de calor e mecânica dos fluidos.
MCTI – Governo Federal
O Ministério da Ciência, Tecnologia e
Inovação (MCTI) foi criado pelo Decreto
91.146, em 15 de março de 1985,
concretizando o compromisso do presidente
Tancredo Neves com a comunidade
científica nacional. Sua área de competência
está estabelecida no Decreto nº 5.886, de 6
de setembro de 2006. Como órgão da
administração direta, o MCTI tem como
competências os seguintes assuntos: política
nacional de pesquisa científica, tecnológica e
inovação; planejamento, coordenação,
supervisão e controle das atividades da
ciência e tecnologia; política de
desenvolvimento de informática e
automação; política nacional de
biossegurança; política espacial; política
nuclear e controle da exportação de bens e
serviços sensíveis.
29
Os Desafios e as Estratégias Nacionais para
Tecnologia e Inovação
30
Prof. Dr.-Ing. Sandro Wartzack
Prof. Wartzack, born in 1966, studied production engineering at the
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany, where
he received his diploma in 1994. From 1995 to 2000 he served as a
scientific assistant in engineering design at the same university. After
he had received his doctoral degree in 2000, he held several positions
at Brose Fahrzeugteile, a leading supplier in the automotive industry.
During that period he gained experience as a project engineer for
vehicle door systems. Later he became director of simulation and
knowledge management. Since 2009 he is head of the Department of
Engineering Design (Lehrstuhl für Konstruktionstechnik) at the FAU
Erlangen-Nürnberg. His research focuses on virtual and knowledge-
based engineering, user-centered design, lightweight design as well
as roller bearings and tribological coatings. Prof. Wartzack is member
of several national and international scientific committees including
e.g. Design Society and TechNet Alliance.
KTmfk - FAU
The mission statement of the Department of
Engineering Design (KTmfk) of the Friedrich-
Alexander-Universität Erlangen-Nürnberg is
“Design for Environment, Health and Safety”.
The KTmfk therefore works on the
development of optimal producible, resource
efficient and robust systems which address
the user’s needs in all research activities at
KTmfk. These activities include methods and
tools for optimized and shortened CAx
processes (CAD, CAE, KBE, DHM), for
dimensional management as well as user-
centered design. A further focus is on
practical examinations on the several test
facilities at the institute with emphasis on
roller bearings and tribological PVD-/PACVD-
coatings. The KTmfk is eagerly interested in
knowledge transfer between university and
industrial practice. Opportunities for
cooperation can be found in all fields of
research of the institute. KTmfk also offers a
variety of well-coordinated and modern
university courses for the design education of
students from engineering degree programs.
31
Virtual Assessment of Product Use Based on
Biomechanical Human Models
Abstract
For a long time the dominating view on product design was affected basically by functional
and economic aspects. Today a growing awareness of health in society is emphasizing
the importance to put the human into the center of all considerations. Indeed the basic
theme of a user-centered design is to provide an optimal fit between human beings and
technical systems by adjusting the properties of products to harmonize with the individual
competencies and needs of the users. In order to implement this idea, detailed information
on the prospective use of the product is needed already in the early stages of the
development process. This especially comprises the direct interaction between the user
and the product. Focusing on the assessment of ergonomic product properties like comfort
or safety, the question is to what extent the human body is stressed during the interaction
with a product. In this contribution simulations on the basis of biomechanical digital human
models are proposed to determine these physiological stress indicators. However since
the simulation procedure is based on methods and tools that were originally developed for
the purpose of medical motion analysis a meaningful application in product design requires
several issues to be addressed. Recent research therefore focuses on the integration of
biomechanical simulation models into common engineering environments. The objective
is to provide a straightforward way to describe and analyze the interaction between a
virtual product prototype and a virtual user model entirely within a CAD environment.
Therefore not only appropriate interfaces for the data exchange between multiple software
systems but also fundamental procedures to predict human motion based on interaction
goals are being developed and evaluated. Another crucial aspect is the adaptation of
human models to match the specific body characteristics and competencies of a certain
user group. Especially the latter aspect points out that the overall topic has an
interdisciplinary character. In this respect, the expertise of human scientists is
indispensable besides product designers and experts in numerical simulation.
Keywords
Ergonomics; virtual product development; design for use.
Authors
Prof. Dr.-Ing. Sandro Wartzack
Daniel Krüger
Jörg Miehling
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
32
1 Motivation
For a long time the dominating view on product design was affected basically by functional
and economic aspects. Today a growing awareness of health in society is emphasising the
importance to put the human into the center of all considerations. In fact the value of many
products is determined essentially by how well their properties harmonise with the individual
competencies and needs of the people who use them. [Dreyfuss 2003] The objective must be
to provide an optimal fit between human beings and technical systems. The idea of a user-
centred design is reflected in considerations that focus on aesthetics but most of all on product
ergonomics. This however requires detailed information on the prospective use, especially on
the direct interaction between users and products to be available already in the early stages
of the development process. The use of a product (Figure 1) is always associated with a task
the user wants to accomplish. Therefore a sequence of actions is chosen that trigger
appropriate functions of the product. At the same time the user constantly adjusts his
behaviour based on the perception of the products response. It is important to notice that
human behaviour (action) and product behaviour (response) are mutually dependent and
cannot be analysed separately.
Figure 1: User-product interaction
From an ergonomic perspective the matter of interest is how the organism of the user is
affected by the interaction process. Therefore the popular concept of load and stress [Bullinger
1994] is applied to product use. While interacting with a product a person can be subject to
external loads such as mechanical forces, vibrations, noise, chemical substances and also
cognitive loads (information). These external influences induce an internal stress on the
organism. Mechanical loads for example mainly affect the person’s musculoskeletal system
resulting in biomechanical stresses. The ergonomic load-stress concept is analogous to the
Environment
Interaction
product
technical
and
human-related
properties
user
demographic
and
psychographic
characteristicsactions
response
task
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
33
corresponding notions in engineering mechanics, which is shown by a simple example in
Figure 2. A cantilever beam is loaded by a force. The resulting deformation (stress) is a
function of the load but also of the physical properties Young´s modulus and moment of
resistance. Equally ergonomic stresses not only depend on the loads but also on the
biomechanical, physiological and psychological characteristics of the user.
Figure 2: Equivalence of the load - stress concept in engineering mechanics and ergonomics
Biomechanical stresses, e.g. muscular activity or joint reaction forces, can be associated with
ergonomic goals like comfort, safety and harmlessness. Hence if designers were able to
simulate the relationship between product characteristics and the level of stress prevalent
during the phase of use they would gain valuable insights on how to improve the ergonomic
quality of products.
In this paper therefore a novel application of biomechanical digital human models is proposed
to simulate ergonomic aspects of product use employing virtual product prototypes only. The
ob-jective is to provide a framework to analyse interaction processes between users and
products within a common computer-aided design (CAD) environment. Further it is shown
how user or user-group specific properties can be considered in biomechanical human
models. Even though the scope of this paper is on the design of products with close user
interaction like vehicle inte-rior, medical devices or sports equipment, many aspects are also
relevant for the design of workplaces and the planning of assembly processes.
2 Biomechanical Digital Human Models for Ergonomic Evaluation
In the early stages of the product development process industry standards like DIN 33401 can
provide general guidelines on issues of human-product interaction. However due to the
heterogeneity of human characteristics and the huge amount of imaginable products universal
rules on ergonomic design are often too generic as being helpful in a specific case. The
standard ISO 9241-210 therefore points out the importance of testing. Thereby a fully or partial
functional physical mock-up of the product is presented to persons in order to evaluate its
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
34
ergonomic quality. Even though the informational value of physical experiments is undoubted
they are always time consuming and costly. Consequently as in other areas of engineering
there is a strong motivation to replace physical testing with computer simulations. This gives
rise to digital human modelling. The idea is to have a virtual model of the user interacting with
a virtual prototype of the product. This not only leads to a reduction of costs but also gives
much more freedom to designers to think through multiple concepts because the results of a
virtual experiment are usually available within a short time span. Biomechanical simulation
systems like OPENSIM [Delp 2007] or ANYBODY [Damsgaard 2006] were developed to describe
structure and motion of the human musculoskeletal system based on multibody dynamics.
The skeleton is modelled as a set of rigid or partially compliant bodies that are interconnected
by joints. Muscles, tendons and ligaments are represented by special force actuators. Some
advanced muscle models even consider effects of fatigue. The primary purpose of these
software packages is the analysis of human motion sequences employing inverse dynamic
calculations (Figure 3). This method requires that the motion of the human model is
unambiguously determined by time series of the generalised coordinates and their derivatives
which correspond to the angles of human joints. If further all external forces F acting on
the body are known the equations of motion can be solved for the actuating forces T which
are identified as the joint torques generated by the muscles. In subsequent postprocessing
steps additional indicators of biomechanical stress like the level of muscular activity,
metabolism and joint reaction forces can be determined. Even though biomechanical digital
human models were developed for applications in motion medicine, they perfectly fit into the
ergonomic load-stress concept. Since they reveal the physiological causes for ergonomic
issues, the simulation results (e.g. muscular activity) can directly be regarded as ergonomic
assessment criteria.
Figure 3: Inverse dynamic analysis of motion
Being among the first to suggest biomechanical human models as design tools [Rasmussen
2003] used the ANYBODY modelling system to optimise the ergonomic properties of a hand
saw. Also the US Defense Advanced Research Projects Agency supports an effort to use
OPENSIM for de-sign activities within the scope of developing special suits for soldiers that
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
35
reduce the risk of injuries and fatigue in combat missions [Simtk 2013]. A broader application
in design however may be inhibited by the fact that biomechanical simulation systems have
not been integrated into the processes of virtual product development. Inverse dynamic
simulations determine the bio-mechanical stresses as a consequence of posture, motion and
external forces. The problem is that in case of a truly virtual simulation the information on how
a user will move during the interaction with a product is not available. A possible solution is to
record the motion of a test per-son and map the data on the human model [Robert 2013] but
this would again mean that a physical experiment had to be conducted and the major benefits
of virtual testing would be lost. In this paper therefore a concept for a CAD integrated
biomechanics laboratory is presented. The objective is to improve the usability of
biomechanical simulations in design. Usability in this context means that the person that uses
a simulation program must be able to provide the input data required to setup the
computations as well as understand and interpret the results. Design engineers usually know
very precisely what functions of the product have to be triggered in or-der to fulfil the tasks it
has been designed for. A formulation of the interaction processes be-tween the user and the
product should therefore rely on task descriptions that encode infor-mation on how the state
of the product or the environment has to be manipulated. Human ac-tions (posture and motion)
that achieve these manipulations should not be required as input in-formation but be predicted
by the simulation. Since a huge proportion of the synthesis work in design is nowadays done
using computer-aided methods it is reasonable to postulate a close integration of
biomechanical simulations with CAD engineering environments. In this regard user or user
group-specific properties are to be taken into consideration in the preceding digital hu-man
modelling step, eventually facilitating robust designs concerning ergonomic aspects of the end
product.
3 Consideration of User-Specific Characteristics in Biomechanical
Digital Human Models
As biomechanical digital human models, also called musculoskeletal models, comprise just a
skeleton as well as muscles, in the first stage we focus on differences in anthropometry as
well as motor functions like strength, range of motion and motion speed. [Miehling 2013]
proposed a process for the conception of biomechanical digital human models taking the
interdependences of the considered domains into account. This procedure is outlined in figure
4. The relevant data to consider the heterogeneous differences over the human life span in
the conception stage are taken from literature.
First of all gender and age of the model to be generated have to be chosen according to the
target group of the product to be developed. In the consecutive steps of the adaption process
percentile values in conjunction with already existing population data are favourable to specify
the model. However, data from manual measurements can be beneficial to model a specific
person or user group.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
36
The method of choice for specifying the body measures in most cases is to chose a
percentile. The height and consequently scaling information for the body segments can then
be computed using population data taking into account the specified age and gender. Body
height data of one culture and gender in most cases can be presumed to follow a normal
distribution. Studies therefore mostly make the body height distribution of a specific age group
and sex available as mean value accompanied by the standard deviation or standard error as
for example in the National Nutrition Survey II (NVS II) published by the Max Rubner-Institut
in 2008. This representative survey among others reports the sociodemographic
characteristics as well as anthropometric measures of the german population. In contrast, if
the model to be generated should resemble a specific (real) person, manual measurements
have to be conducted to get the overall body height as well as values for the dimensions of
the individual body segments. Regardless of the data origin, subsequently scaling factors for
all body segments are calculated which are eventually used to scale the musculosceletal
model.
Figure 4: Overview of the conception process [Miehling 2013]
Another sophisticated method is to retrieve the segmental lengths through optical, marker-
based or markerless measurement systems usually used for motion capture purposes.
[Krüger 2012] for example developed a system for the markerless capture of motions as well
as scaling of biomechanical digital human models using the Microsoft Kinect sensor, originally
developed as game controller. This system automatically provides the scaling factors for the
body parts without need for further computation. Its user interface is depicted in Figure 5.
After collecting the data for the segmental lengths, the body weight of the model to be
generated has to be specified. Even though body weight is usually not normally distributed,
the majority of surveys report the weight in the same way as the body height and therefore
neglect valuable information about the underlying sample. Moreover, body weight tends to
increase with body size. This correlation hampers the computation of the body weight using
the body weight distribution of the population.
age / gender
body height /segment lengths
body weight /segment weights
range of motion strength
mass momentsof inertia
motion speed
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
37
Figure 5: Low-cost motion capture system based on Microsoft Kinect
In the present approach body weight can therefore either be chosen directly or by the body
mass index (BMI). [Keys 1972] advised the BMI (body weight [kg] / (body height)² [m²]) as a
measure for the physical constitution of populations. It removes the dependency between
weight and height and is a good predictor for body fat percentage. [Hemmelmann 2010]
calculated the BMI distribution for both genders and every single year of age using the LMS
method based on the raw data of the NVS II. After chosing a percentile of the BMI distribution,
the BMI can be computed. Hereafter, the body weight can be calculated taking into account
the body height of the preceding step. The entire body’s mass distribution, respectively
individual body segment weights, are then computed considering the scaling factors for the
body part dimensions. If the human model’s dimensions are scaled just considering the overall
change in body height, the mass distribution stays unaffected. The mass moments of inertia
of the individual body segments are especially important in dynamic simulations. If the
changes in the segments’ mass and dimensions are known, the inertia tensors can be
calculated. The maximum isometric forces generated by skeletal muscles are highly
dependent on age, weight and size. A taller, heavier person tends to be able of generating
bigger muscle forces in comparison to a shorter, lighter person of the same age, gender and
ethnicity. From around 30 years of age on, the maximum muscle forces decrease steadily.
Women are generally less strong than their male counterparts. [Stoll 2002] measured and
percentiliced the maximum isometric voluntary joint torques for a healthy population in a given
joint angle constellation. This data is used to scale the maximum isometric force of every
muscle of our biomechanical digital human model. Unlike with body measures, weight and
strength, there seems to be no clear correlation between the range of motion and the age of
a person. The distributions in this respect coincide largely, given that diseases like arthritis are
ignored. Due to the just stated aspects the range of motion is scaled using percentile values
without regarding the affiliation to a specific age group [Greil 2008]. The maximum motion
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
38
speed does not directly depend on body weight and size. The execution of movements
decelerates just a small proportion due to physiological changes in the skeletal muscles, but
largely due to the smaller maximum forces resulting from the progressing muscular dystrophy
with age. Additionally as weight increases, the segments’ mass moments of inertia rise and
therefore the same muscle forces yield lower angular accelerations and in turn angular
velocities. Taking the age distribution of the targeted culture into account, representative user
groups can be generated for the following virtual assessment of product use.
4 A CAD Integrated Biomechanics Laboratory
4.1 Concept and Related Work
In section 2 a task oriented formulation of user-product interactions and a seamless
integration with CAD environments have been identified as the most important
requirements on a virtual biomechanics laboratory. Existing approaches to connecting
biomechanical models and CAD systems are mainly addressing the problem of data
exchange. The Anybody modelling system e.g. provides an import filter for product geometry
created in SolidWorks. A closer integration can be achieved by coupling a complex
biomechanical model to the kinematics of a CAD integrated anthropometric model as
published by [Jung 2013] and previously by [Krüger 2012].
Figure 6: Concept of a CAD integrated biomechanics laboratory
Our concept (Figure 6) uses a similar idea: an anthropometric human model (skin model)
inside a common CAD environment serves as a front-end the design engineer uses for
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
39
preprocessing. Preprocessing mainly comprises the definition of geometric relationships
between the user and the product that are needed to setup the actual simulation performed
on the musculoskeletal model.
The concept is built on four important pillars: the transfer of anthropometric data and posture
(spatial registration) between the skin model and the musculoskeletal model, a task oriented
pro-tocol to formulate user-product interactions, a methodology to predict human motion and
the simulation of product behaviour. In the following sections these topics are illustrated by
means of a simple case study. The interaction process to be analysed is the situation of a
person driving a passenger car as depicted in Figure 7. Even though in reality the driver is
interacting also with the gear lever and the pedal, the only task considered in this example is
to turn the steering wheel slightly to the right. The question to be answered by this analysis is
which region of the body shows the highest muscular activity.
Figure 7: Case study: steering a passenger car
4.2 Transfer of Anthropometric Data and Posture
In the beginning of a virtual experiment all relevant characteristics of the user like body
measures or strengths must be choosen according to the procedure described in section 3.
The output of this process is a musculoskeletal model for the OPENSIM platform. For the case
study the musculoskeletal model has been choosen to resemble the anthropometric
properties of an average European male. From within the CAD environment this
musculoskeletal model is loaded and connected to the skin model. The connection consists
of a scaling operation and a subse-quent spatial registration of the two models. In the scaling
operation the limb lengths of the mus-culoskeletal model are determined by calculating the
distances of marker points located in the centres of the joints. These values are assigned to
corresponding CAD parameters of the skin model. Since the skin model is used as a front-
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
40
end of the actual simulation model it has to be assured that both models coincide
geometrically. This means that for example the location of a point defined on the skin model
must be unambiguously found also on the musculoskeletal model. This is achieved by a point
by point registration (see Figure 8): a set of datum points dis-tributed over the limbs of the
musculoskeletal model is fitted to a corresponding set located on the skin model by numerical
inverse kinematics. As a result the musculoskeletal model follows the posture specified by the
skin model.
Figure 8: Transfer of data between skin model and musculoskeletal model
4.3 Task Oriented Interaction Protocol
Once the human model is set up the next step is the formulation of the task to be analysed.
As postulated in section 2 this formulation should not rely on descriptions of human behaviour
(e.g. “move the right arm”) but on required manipulations of the product. Therefore a formal
interaction protocol has to be elaborated that could rely on a structured model of user-product
interaction as published by [Mieczakowski 2010]. The current prototype of the protocol
contains action goals and boundary conditions. To define an action goal the designer identifies
parts of the product model as human-machine interfaces and describes how these parts have
to be manipulated in order to trigger the desired function of the product. A boundary condition
is a geometric relationship between the user model and the product model or the environment.
In case of the steering example (Figure 9) the claims that the buttocks of the user remain on
the seat while both hands remain on the whee are typical boundary conditions whereas the
required rotation of the wheel link is an action goal.
The boundary conditions and action goals are the input parameters for an algorithm (motion
predictor) that predicts the motion the user will most likely choose to fulfil the task. This
algorithm is described in the next section.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
41
Figure 9: Interaction protocol: boundary conditions and action goals
4.4 Prediction of Human Motion Based on the Optimality Principle
Optimality as the property of a system to maximise or minimise some function under given
con-straints is often found in nature. Examples are the minimisation of potential energy as a
driving force for chemical and physical processes or the assumption of natural selection
according to which form and behaviour of creatures are developing towards optima. Many of
the characteris-tics of human motor behaviour can be explained by the optimality principle. It
seems natural that humans perform movements in a way that minimum mechanical effort is
necessary. But also the elimination of kinematic and dynamic redundancy can be achieved if
those joint con-stellations and patterns of muscular excitation are preferred that entail less
effort compared to alternative solutions. Computer simulations based on the optimisation of
mathematical functions are therefore very promising approaches to predict posture and
motion of biomechanical human models.
The dynamics of the human musculoskeletal system can be described by equation (1).
(1)
Here (t) is the skeletons physical state vector consisting of the joint angles, the corresponding
generalised speeds as well as additional states of the muscles like tendon length, contraction
velocity and level of activation. The time derivative of the state depends on the current
state and the current control vector . Controls are time dependent neural signals that
activate the muscles and lead to torque generation in the joints. Under a simplified point of
view without considering muscles one can also directly apply torques to the joints and regard
these as controls. The evolvement of the state (= motion) is simulated by integrating equation
(1) over time. Hence predicting human motion means to determine a set of control signals
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
42
that lead to the achievement of a task defined by the interaction protocol described in section
3. Due to the kinematic and dynamic redundancies of the human musculoskeletal system
there is usually no unique solution to this problem. Instead one has to settle for finding a best
solution that minimises an objective function given in (2).
with (2)
This objective function assesses the motion (state and control) of the human model by means
of arbitrary optimality criteria encoded by the cost value that is associated with each time
step. Possible optimality criteria are discussed further below. The optimal control
signals are consequently the solutions of the following dynamic optimisation problem.
(3)
Optimal control problems of this type can be solved by several numerical methods [Todorov
2006]. A limiting factor for the application on complex dynamic systems like the human body
however is that most of the algorithms are computationally extreme costly.
An exception to this is the iterative linear quadratic regulator (iLQR) method that was originally
published by [Todorov 2005]. It would go beyond the scope of this contribution to cover all the
mathematical details. Instead only the coarse working principle of iLQR and how it is employed
to predict human motion within virtual testing of use is explained. The algorithm takes
advantage of the fact that for linear system dynamics and objective functions quadratic in u
the solution to the optimal control problem is relatively straightforward. Unfortunately
musculoskeletal dynamics are highly non-linear. The idea of iLQR is to iteratively use linear
approximations of the system dynamics function (1) and quadratic approximations of the
objective function (2) to construct a sequence of solutions that finally converges to the exact
solution. The methodology actually yields an optimal feedback controller which means that
not only the controls are determined but also feedback gains that could be used to correct
the motion from external disturbances. An iLQR controller was implemented on top of the
biomechanical simulator OPENSIM and applied to the case study introduced in section 4.1.
The task (turning the steering wheel) has been formulated using the interaction protocol
described in the previous section. The boundary conditions (buttocks on seat, both hands on
the wheel, feet on the pedals) are implemented by inserting five kinematic constraints into the
musculoskeletal model. The action goal (rotate the wheel to ) is used to derive the
optimality criteria for the iLQR controller. The resulting objective function is given in equation
(4).
+ (4)
The term in front of the integral only depends on the final time step T and penalises the
deviation of the gear levers actual position from the required position. In addition since the
motion should stop at the required position the velocity of the lever is required to be zero. The
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
43
integral term is called the running cost function since it assesses the way towards the target
position penalising the control effort for the muscles.
4.5 Simulation of the Product Behavior
User-product interaction processes as depicted in figure 1 are actually feedback loops. The
be-haviour of the product is affected by the behaviour of the user and vice versa. A simulation
for virtual testing of use must consequently also contain a behavioural model of the product.
Our concept permits a computational separation of the musculoskeletal user model and the
product model. Hence user behaviour and product behaviour can be processed in separate
simulation programs that however need to be synchronised to exchange data. The advantage
of this co-simulation approach over monolithic solutions [Damsgaard 2006] that handle the
product as a part of the multibody system employed to describe the user is that the behaviour
of the product is not limited to what can be described by multibody dynamics. In fact the
product simulator can be any kind of algorithm capable of emulating mechanical responses.
A problem of co-simulations is to define the system boundary of each simulation model. In
case of user-product interaction it is reasonable to define this boundary along the human-
machine interfaces of the product. In the case study the steering wheel can be identified as a
part of the human-machine interface. The product behaviour however is mainly determined
by the internal design of the steering system. This behaviour is sensed in terms of a reaction
force on the wheel. Hence the system boundary is the interface between the wheel and the
steering gear. In other words the wheel is treated as a component of the biomechanical
multibody tree while the reaction force generated by the steering system could be emulated
by an external product simulator. In this case the communication between the simulators
would be an exchange of wheel rotation and reaction torque. This approach entails the
necessity to export parts of the product model (the human machine interfaces) from the CAD
environment into the biomechanical simulation sys-tem. A prototypical interface between
OPENSIM and the CAD system CREO/PARAMETRIC (PTC) has been developed that allows
exporting arbitrary parts or sub-assemblies of the product model into the multibody simulator.
Therefore the mass properties of the parts and the kinematic con-straints to the surrounding
assembly are analysed automatically
5 Results of the Case Study
The CAD integrated biomechanics laboratory has been used to create a dynamic simulation
model for the car driving example introduced in section 4.1. The resulting motion sequence is
illustrated in Figure 10. Moreover the total sum over the control signals of the muscles that
are actuating the right shoulder joint is shown. This muscle group has been identified to
contribute the largest part of the actuation effort in the upper extremities of the body. Since
control signals are direct proportional to the level of muscular activitiy, they are ideal criteria
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
44
to assess the risk of muscular fatigue, which is one aspect of discomfort, during the user-
product interaction pro-cess. In the present case adjustments of the product design that lead
to a lower control values can therefore be regarded to improve the ergonomic quality of the
vehicle cockpit. However since the complete dynamic state trajectory is known, additional
stress indicators (e.g. joint loads) can be extracted in subsequent computations.
Figure 10: Case study: motion sequence and major actuation
6 Summary and Outlook
A growing awareness of health in society emphasises the importance of a user-centred design
process.
More than in former times design engineers will have to focus on product ergonomics. Since
ergonomic product properties are related to the interaction processes with the user, the im-
portance of testing for use is also growing. However traditional testing concepts are time con-
suming and costly because they usually require the manufacturing of physical mock-ups and
the conduction of experiments involving multiple test persons to cover the characteristics of
the tar-get user group. In this paper therefore biomechanical human models were proposed
as a possibility to simulate ergonomic aspects of user-product interaction already in the early
stages of the development process.
Hereby designers are enabled to predict and quantify the relationship between design
parameters and the level of biomechanical stress effects prevalent during product use within
the users organism. To improve the ergonomic quality of products the design is adjusted so
that stress indi-cators like muscular activity are kept at a moderate level. However the
application of biome-chanical simulations in design is currently not very widespread. The
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
45
dependence on experi-mental data for the specification of human behaviour and the
unsatisfying integration with exist-ing methods and tools of virtual product development were
identified as the main hurdles. The benefit of the concept for a virtual biomechanics laboratory
presented in this paper is the seam-less integration into an existing CAD/CAE environment.
Designers are not confronted with ex-perimental data and anatomical details on
biomechanical modelling. Due to the computational separation of product model and user
model it is possible to take advantage of a huge number of sophisticated CAE algorithms to
resemble the behaviour of the product. This is especially im-portant since many products
today are mechatronic systems that can’t be analysed using solely multibody dynamics. The
most crucial but also the most challenging aspect of virtual simulation of use is however the
prediction of human behaviour. Based on a task oriented formulation of user-product
interaction an optimal control algorithm is employed to synthesise the motion of the user. Even
though this is regarded a promising approach its validity has not been verified yet. Future
research will therefore have to address the experimental validation of motion prediction
methods. Equally the implementation of the concept presented is still incomplete. In particular
the task oriented interaction protocol and the computational interfaces to perform a co-
simulation of user model and product model require additional effort to become usable in
indus-trial applications.
Another important question is how designers have to interpret the results of a biomechanical
analysis. Biomechanical stress indicators at first glance tell little about what design changes
could improve the ergonomic properties of the product. The simulation system therefore
should provide the designer with guidance to design improvements by mapping the results
back into the space of design parameters.
7 References
Bullinger, H.; Ilg, R.: “Ergonomie: Produkt und Arbeitsplatzgestaltung“, Teubner Stuttgart,
Germany, 1994.
Damsgaard, M. et al.: “Analysis of musculoskeletal systems in the AnyBody Modeling
System”, Simulation Modelling Practice and Theory, Vol. 14, No. 8, 2006, pp
1100–1111.
Delp, S. et al.: “OpenSim: Open-Source Software to Create and Analyze Dynamic
Simulations of Movement”, IEE Transactions on Biomedical Engineering, Vol. 54,
No. 11, 2007, pp 1940-1950.
Dreyfuss, H.: “Designing for people: [the classic of industrial design]”, Allworth New York,
USA, 2003.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
46
Greil, H.; Voigt, A.; Scheffler, C.: „Optimierung der ergonomischen Eigenschaften von
Produkten für ältere Arbeitnehmerinnen und Arbeitnehmer – Anthropometrie“,
Bundesanstalt für Arbeitsschutz und Arbeitsmedizin, Dortmund, 2008.
Hemmelmann, C.; Brose, S.; Vens, M.; Hebebrand, J.; Ziegler, A.: “Percentiles of body mass
index of 18-80-year-old German adults based on data from the Second National
Nutrition Survey”, Deutsche medizinische Wochenschrift (1946), Vol. 135, No. 17,
2010, pp 848-852.
Jung, M.; Damsgaard, M.; Andersen, M.; Rasmussen, J.: “Integrating Biomechanical
Manikins into a CAD Environment”, 2nd International Digital Human Modeling
Symposium, Ann Arbor Michigan, 2013.
Keys, A.; Fidanza, F.; Karvonen, M. J.; Kimura, N.; Taylor, H. L.: “Indices of relative weight
and obesity”, Journal of chronic diseases, Vol. 25, No. 6, 1972, pp 329-343.
Krüger, D.; Miehling, J.; Wartzack, S.: “A simplified approach towards integrating
biomechanical simulations into engineering environments”, 9th Norddesign
Conference, Aalborg, 2012, pp 334–341.
Max Rubner-Institut (Hrsg.): Nationale Verzehrsstudie II. Ergebnisbericht, Teil 1. Die
bundesweite Befragung zur Ernährung von Jugendlichen und Erwachsenen,
Berlin, 2008.
Mieczakowski, A.; Langdon, P.; Bracewell, R.; Clarkson, P.: “Toward a model of product-user
interaction: a new data modelling approach for designers”, International Design
Conference DESIGN 2010, Dubrovnik, 2010, pp 875–884.
Miehling, J.; Geißler, B.; Wartzack, S.: “Towards Biomechanical Digital Human Modeling of
Elderly People for Simulations in Virtual Product Development”, Human Factors
and Ergonomics Society 2013, International Annual Meeting, San Diego, 2013, pp
813-817.
Rasmussen, J. et al.:”Musculoskeletal modeling as an ergonomic design method”,
International Ergonomics Association XVth Triennial Conference, Seoul, 2003.
Robert, T.; Causse, J.; Denninger, L.; Wang, X.: “A 3-D dynamics analysis of driver’s
Ingress-Egress Motion”, 2nd International Digital Human Modeling Symposium,
Ann Arbor Michigan, 2013.
Simtk, “Warrior web project website”, https://simtk.org/home/opensim_ww, accessed
20.11.2013
Stoll, T.; Huber, E.; Seifert, B.; Stucki, G.; Michel, B. A.: “Isometric Muscle Strength
Measurement”, Thieme, Stuttgart, 2002.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
47
Todorov, E.: “Optimal Control Theory”,in Doya, K.(ed.), Bayesian Brain, MIT Press
Cambridge, USA, 2006.
Todorov, E.; Weiwei, L.: “A generalized iterative LQG method for locally-optimal feedback
control of constrained nonlinear systems”, American Control Conference 2005,
Portland, 2005.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
48
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
49
Nam
e 05
.32.
001
© LEHRSTUHL FÜR KONSTRUKTIONSTECHNIKFriedrich-Alexander-Universität Erlangen-NürnbergProf. Dr.-Ing. Sandro Wartzack 5
Chair of Engineering DesignFriedrich-Alexander-Universität Erlangen-Nürnberg
Sto
ckin
ger
HeadquartersSouthern Campus
SubsidiaryRöthelheim Campus
Executive BoardSchlossplatz
Faculty of EngineeringSouthern Campus
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
50
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
51
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
52
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
53
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
54
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
55
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
56
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
57
58
Dipl.-Ing. André Picard
Dipl-Ing. André Picard graduated from Technische Universität
Darmstadt in 2010. With the completion of his studies as Diplom-
Ingenieur, he joined in October 2010 his position as Research
Assistant at the Department of Computer Integrated Design (DiK) at
Technische Universität Darmstadt. Since midth of 2012 Mr. Picard is
part of the research field “Digital Factory” at the DiK. He was a member
of the DFG promoted project “Federative Factory Data Management”.
In particular he is engaged in the linking of different factory data and
the integration of mobile internet devices into the federative factory
data management. Since 2014 he takes part in the LOEWE centre
AdRIA (Adaptronic - Research, Innovation, Application). His research
covers methods for virtual development of adaptronic and cyber-
physical systems.
DiK, TU Darmstadt
The Department of Computer Integrated
Design (DiK) is part of the Faculty of
Mechanical Engineering of the Technische
Universität Darmstadt. The integration of
information technology as integral part of
modern mechanical engineering and the
linkage of research and education to
industrial needs are our fundamental targets.
The principles and methods of processing
product data even today are developing
rapidly. To understand product data, product
data flows and product data processing, a
holistic approach named Product Data
Technology (PDT) has been chosen for
education and research. The scientific
strategy of the DiK is based on four main
research fields: “Information Modeling”,
“Virtual Product Creation", ”Collaborative
Engineering” and “Digital Factory. These
research fields contribute significantly to the
scientific progress of Virtual Product
Development and Virtual Factory and support
the creation of advanced competencies to
enable new innovation and strengthen
industrial competitiveness.
59
Integrated Component Data Model for Smart
Production Planning
Abstract
The integrated component data model describes individual components throughout the
whole component life cycle from product development to recycling or disposal. Contrary
to the integrated product data model in which a generic product data model is instantiated
to multiple virtual product objects the integrated component data model focuses on a single
physical instance of real parts and assemblies generically called components. It therefore
combines individual data about the physical component with virtual product lifecycle
information.
Consequently the integrated component data model is a key-enabler for smart production
planning. Smart production planning is characterized by a bidirectional flow of information
between virtual product data on the one hand and physical component and environment
information of existing product generations on the other hand. In this context individual
component data actively influences preceding product development and production
planning processes.
In the context of the smart and resource-efficient factory of the future one main goal of
component-driven manufacturing is the improvement of resource exploitation. Aggregated
information provided in a schematic representation within the integrated component data
model facilitates the component-specific adaption of processes.
Within this paper the integrated component data model as well as an exemplary use case
for improved resource exploitation in the smart factory is presented.
Keywords
Integrated component data model; Industrie 4.0; computer aided manufacturing, cyber-
physical production systems.
Authors
Dipl.-Ing. André Picard
DiK, TU Darmstadt [email protected]
Prof. Dr.-Ing. Reiner Anderl
DiK, TU Darmstadt [email protected]
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
60
1 Introduction
In the past years manufacturing companies are facing a dramatic change. Individual customer
demands on highly customer-tailored goods and services are getting most important on the
global markets. Consequently the product variety increases while meantime the lot size
decreases. For such goods short time to market with innovative technologies at remarkable
low prices are crucial to successfully compete on the global markets.
The application of recent information and internet communication technologies to mechatronic
products in combination with today’s ubiquitous computing seems a promising solution for
these demands. So-called cyber-physical systems (CPS) are developed. They are digitally
enabled products which communicate and collaborate within ad-hoc networks of other cyber-
physical systems. They get the ability to autonomously decide and adaptively react on internal
and external events in order to optimize, diagnose and calibrate themselves and their
surrounding environment [1].
Digital product memories within those cyber-physical systems enable the seamless gathering
and use of component-individual on-line information throughout the whole life cycle from the
cyber-physical systems’ creation to recycling or disposal [2].
The provision of this information to engineers of the production planning is a key-enabler for
the creation of process knowledge. Engineers get the ability to extract interdependencies
between production planning and manufacturing processes at the shop floor first and to
consider this knowledge during production planning secondly. Therefor the continuous bi-
directional information flow throughout the whole component life cycle from product idea to
component recycling or disposal is needed.
To support such an information flow, an approach for the specification of the integrated
component data model and its integration in the engineering processes of the production
planning is presented within this paper. The integrated component data model enables front-
loading of production planning with derived knowledge from products, processes, resources
and component data. An exemplary use case on this smart production planning further
illustrates the benefits of the given approach.
2 Cyber-Physical Production Systems
Cyber-physical systems are an integration of mechanical, electronic components with recent,
internet based information and communication technologies [3]. Lee describes two
complementary approaches for cyber-physical systems, called “cyberizing the physical” for
specifying physical systems with computational abstractions and interfaces and “physicalizing
the cyber” for expressing abstractions and interfaces of software and network components to
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
61
represent physical systems’ dynamics in time [4]. Cyber-physical systems therefore are
considered as key-enabler to develop the “Internet of Things” [5][6] due to integrated complex
logics for information processing, intelligent sensors and actuators as well as their ability to
cooperate in cyber-physical systems’ networks [7].
The installation of cyber-physical systems in the production form a smart environment, called
cyber-physical production systems [8]. In this environment cyber-physical systems get
interconnected in networks using today’s ubiquitous broadband communication infrastructure.
They actively make decisions, manage processes and trigger events in order to improve for
example:
Efficient production and logistics,
Adaptive manufacturing,
Quality assurance,
Predictive maintenance,
New or enhanced business processes, and
Custom-tailored functionalities.
All activities of cyber-physical systems support the horizontal integration of participants along
the value-added chain and the vertical integration of participating stakeholders and
information technology tools.
Therefore they grant access to component-individual on line data throughout their life cycle
for example from the shop floor during production or during usage. Appropriate data storages,
infrastructures and mechanism for data access are mandatory.
3 Semantic Product Memory
The application of digital product memories to components enable the gathering of
component-individual data throughout their lifecycle [1]. Digital product memories are
miniaturized digital data storages being physically attached to concrete components. The
gathered data of a digital product memory focuses on all information which is related to the
concrete physical component and intentionally created during component’s creation and use
[2][9][10].
Digital product memories store data on the component [2]. Common technologies used for
these product memories are radio based tags like radio frequency identification transponder
(RFID) and near field communication chips (NFC) as well as two-dimensional barcodes like
the quick response code (QR code) and the data matrix [9].
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
62
Due to the technical limitation of these product memories, the amount of available data storage
is limited.
Data Format. An appropriate data format is needed. Digital product memories use a binary
data format [9]. This propriety data format is only readable using equivalent information
technology tools [9]. The semantic product memory, a subclass of digital product memories,
aims to provide a machine-understandable description of the digital product memory [2]. It
therefore uses semantic web technologies to describe the primitives and ontologies for the
stored data [2]. Open access to the stored data is enabled instead of restricted access as
found for the digital product memories [2].
The semantic product memory defines a modular container format. Existing digital product
memories as well as other data can be embedded [9]. The container format consist of three
sections: a header, followed by a table of contents of the block headers and multiple data
blocks [2][9].
Descriptive metadata about for example the creation date, the author or the phase of the
product lifecycle are stored in the header or the block header. For the data blocks multiple
content types are allowed like plain text, HTML, images, archives or byte streams [9]. Unique
identifier, structures and relationships are equally stored in such data blocks [10]. They are
used to create references to distributed semantic product memories or composite product
memories. Composite product memories contain semantic product memories of multiple
components. They provide an additionally infrastructure to access every single semantic
product memory [10].
Challenges. The total size of available storage has always be kept in mind while storing data
to the semantic product memory. Therefore two challenges occur: aggregation of data and
storage of life cycle information.
Distributed storage of data complicates the aggregation and update of data [10]. The semantic
product memory uses a peer-to-peer infrastructure to update and gather information [10].
Searching and updating processes therefore use requests, which are forwarded to all
neighbors [10] at a cost of time and at cost of overhead data.
As the amount of storage data is limited while storing life cycle information, semantic product
memories propose to overwrite previous data using a circular buffer [11]. Consequently
component life cycle data is only accessible for a limited time period. After this time period the
information gets lost.
4 Integrated Product Data Model
Appropriate knowledge about products and processes are crucial for successful engineering.
Due to the increasing virtualization of the product development and production planning,
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
63
knowledge, information and data is stored to semantic product data models. Integrated
product data models support the whole product lifecycle and enable a continuous flow of
information throughout all product life cycle phases. Such an integrated product data models
is the Standard for the Exchange of Product Model Data (STEP) as specified in the
International Organization for Standardization 10303 (ISO 10303).
Format. STEP aims to reduce heterogeneity of product model data and thus reduce the
amount of data exchange interfaces needed to integrate all information tools in product
development [12]. It therefore defines a core structure, which is specialized for every use
cases in application protocols [12].
STEP application protocols include product data such as [12][13][14]:
General management information,
Part identification,
Product structure and assemblies,
Requirements and functionality,
Geometry,
Machining form feature,
Product manufacturing information,
Product configuration,
Product status, and
Presentation.
All STEP application protocols use singular text files in the ASCII format. These text files
provide a machine- and human-readable representation of the whole integrated product data
model.
Challenges. The integrated product data model faces two relevant challenges: handling
information spread over multiple information technology tools and lifecycle interdependencies.
The integrated product data model integrates all product information. Information spread over
multiple information technology tools therefore is aggregated in one singular file. This
approach improves data access and exchange, but the actuality of high dynamic data is not
respected.
Another challenge for the integrated product data model is the representation of lifecycle
interdependencies. For every product one virtual product object is instantiated. Multiple
components physically manufactured at shop floor are then virtually represented by only one
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
64
singular virtual product object. All component data is aggregated within this object. A
dedicated separation between different component life cycle data and thus the source of data
is not possible even if obligatory for engineering.
Interdependencies due to specific product concepts and physical processes combination
during component’s life cycle are not explicitly recorded in the data model. Consequently the
derivation of knowledge for subsequent product development and production planning based
on these given data is restrained.
5 Integrated Component Data Model
The aim of the integrated component data model is to close the gap between product data in
the integrated product data model on the one side and component-specific data from the
semantic product data model on the other side.
The integrated component data model is an approach for the specification of the semantic
representation of the component data model. It integrates product, process, resource and
component data as well as it provides the corresponding behavior. It concerns the whole life
cycle from product idea to the component recycling or disposal.
Distinction. The integrated component data model thus extends both previously described
approaches of the semantic product memory and of the integrated product data model.
In contrast to the semantic product memory the integrated component data model is integrated
actively to all engineering processes, including the product development and the production
planning. Besides component-specific data the integrated component data model assures a
bidirectional association between component states and their behavior in the physical and
virtual world throughout the whole product and component life cycle. In contrast to the
semantic product memory this life cycle already starts before the physical creation of the
component and also includes planned life cycle events in the future of the component. To be
highlighted is the fact that the approach is not only the data model for data storage of semantic
product data, but is involved actively in the current and planned processes due to its
component-specific behavior.
Compared to the integrated product data model the integrated component data model is
focused on the component. Each component is represented by a specific instantiated object
of the integrated component data model. The identification of specific components and their
data is assured. Instead of data aggregated in a singular product data model instance, specific
data as result of concrete life cycle states and events is stored and kept in relation to the
component. Knowledge about interdependencies between product concepts and production
gets recognizable and traceable. To be more precise, a remarkable example for the difference
between the integrated component data model and the integrated product data model is the
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
65
storage of concrete dimensions instead of nominal dimensions with tolerance fields (see
Figure 1).
Figure 1: From product model to component model
Data Format. The approach for integrated component data model consists of core and partial
information models (see Figure 2). The core information model specifies the identification,
addressing, localization, administrative and organizational information as well as the
geometric representation [7]. Partial information models include data resulting from other
virtual and physical processes like the simulation, the manufacturing or the assembly [7]. Due
to the modular characteristics of the integrated component data model each partial model
further extends the core data model.
Figure 2: Core and partial models of the integrated component data model
Each partial information model must consequently consider formal requirements [7]:
Integrity (semantic correctness of information),
Coherence (correlation of information without transformation),
Accumulation (explicit representation of all relevant information), and
Association (derivation of implicit information) [7].
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
66
The seamless integration of the integrated component data model into the existing
infrastructure is currently investigated. A promising approach is the use of a federation based
on RESTles web services [15][16] and the extensible markup language (XML).
The approach for the integrated component data model consists of a variety of different core
and partial models. In the following the approach for the partial model for production planning
and its relevance in the engineering process is described.
6 Smart Production Planning
Today's production planning is driven by orders. In the smart and efficient factory of the future
components control actively or at least influence directly their life cycle phases. In the
component creation phase they control their production. They are aware of their environment
and planned life cycle states. Consequently they aim for the appropriate adoption of their
situation to reach these planned life cycle states. Thus in the factory of the future production
is no longer driven by orders, but by components.
In this context bi-directional flow of information and transparency of information is crucial for
engineering processes. Engineers of the production planning need a holistic understanding
about interdependencies in the production processes. These production processes face
component-specific production processes which are globally planned for product series, but
individualized upon production. Each component is individually produced depending on
environmental influences like customization, production bottlenecks or machine breakdown.
Consequently production planning is specific for each component. Interdependencies are
manifold, but recorded to component-specific life cycle histories in the integrated component
data model.
In this paper an approach, called smart production planning, is presented. Smart production
planning uses the integrated component data model to increase the efficiency in the resource-
efficient factory of the future by the front-loading of detected interdependencies between
production planning and shop-floor states. Thus it creates a data base for deriving the required
holistic understanding about the production processes.
Example. The integrated component data model specifies partial information models for the
wear of tools in milling machines at shop floor and resulting producible tolerances on the one
hand. On the other hand it equally specifies numerical control (NC) code as result of the
computer aided manufacturing (CAM) as well as the corresponding tolerance fields chosen
during the product development.
Creating relationships between this information and its use in the smart production planning
allows the improvement of the tool wear exploitation. The smart production planning therefore
enables production planner to schedule milling operations with the respect to the planned
tolerance fields. Operations with respect to narrow tolerance fields are scheduled first,
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
67
operations with wider tolerance fields are scheduled later. The milling tool is exploited at the
maximum of its manufacturing capacity. The efficiency of the production process is increased.
7 Conclusion
The integrated component data model is an approach for the specification of the semantic
representation of component data. It specifies core and partial information models to integrate
product, process, resource and component data. The integrated component data model
further extends the semantic product memory in terms of life cycle support, represented data
and behavior. It equally extends the integrated product data model in terms of component-
specific data storage and retrieval.
The use of the integrated component data model within the production planning makes the
process smart. Integrated data enables production planner to derive interdependencies
between product concepts and production processes. In this paper an example for the
improvement of the resource-exploitation of milling tools is given. There the integrated
component data model is used to reschedule milling operations in respect to concrete tool
wear at the shop floor in relation with producible tolerance fields and approved tolerance fields
of the product development.
Upcoming work in the research project is the further specification of the integrated component
data model and its integration to existing product development and production planning tools.
A promising approach therefor is the use of a federative architecture as proposed in the
federative factory data management [16]. Additionally research projects analyze the use of
the integrated component data model in other engineering processes and its impact on the
engineering processes [17].
8 References
[1] Broy, M.; Kagermann, H.; Achatz, R. (eds.): Agenda Cyber Physical Systems – Outlines
of a new research domain. acatech – National Academy of Science and
Engineering, München, 2010.
[2] Wahlster, Wolfgang: The Semantic Product Memory: An Interactice Black Box for Smart
Objects. In: SemProm – Foundations of Semantic Product Memories for the
Internet of Things, Wolfgang Wahlster (eds.). Springer-Verlag, Berlin, Heidelberg,
2013, pp. 127-148.
[3] Eigner, Martin; Anderl, Reiner; Stark, Rainer: Interdisziplinäre Produktentstehung. In:
Smart Engineering – Interdisziplinäre Produktentstehung, Reiner Anderl, Martin
Eigner, Ulrich Sendler, Reiner Stark (eds.). acatech Diskussion, München, 2012,
pp. 7-16.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
68
[4] Lee, Edward A.: CPS Foundations. In: Design Automation Conference ’10, Anaheim,
California, 2010, pp. 737-742.
[5] Broy, Manfred (eds.): Cyber-Physical Systems. Innovation durch Software-intensive
eingebettete Systeme. acatech DISKUTIERT, Springer, Heidelberg 2010.
[6] Acatech (Hrsg.): Cyber-Physical Systems. Innovationsmotor für Mobilität, Gesundheit,
Energie und Produktion. acatech POSITION. Springer, Heidelberg, 2011.
[7] Anderl, Reiner; Strang, Daniel; Picard, André; Christ, Alexander: Integrated Component
Data Model for Industrie 4.0 – Information Carrier for Cyber-physical Production
Systems. In: ZWF – Zeitschrift für wirtschaftlichen Fabrikbetrieb (1-2/2014), 2014,
pp. 64-69.
[8] Kagermann, Henning; Wahlster, Wolfang; Helbig, Johannes (eds.): Recommendations for
implementing the strategic initiative INDUSTRIE 4.0.acatech – National Academy
of Science and Engineering, Frankfurt/Main, 2013.
[9] Horn, Sven; Claus, Alexander; Neidig, Jörg; Kiesel, Bruno; Hansen, Thorbjørn; Haupert,
Jens: The SEMPROM Data Format. In: SemProm – Foundations of Semantic
Product Memories for the Internet of Things, Wolfgang Wahlster (eds.). Springer-
Verlag, Berlin, Heidelberg, 2013, pp. 127-148.
[10] Horn, Sven; Schennerlein, Barbara; Pförtner, Anne; Hansen, Thorbjørn: Distributed
Digital Memories. In: SemProm – Foundations of Semantic Product Memories for
the Internet of Things, Wolfgang Wahlster (eds.). Springer-Verlag, Berlin,
Heidelberg, 2013, pp. 127-148.
[11] Neidig, Jörg; Preißinger, Jörg: A SEMPROM Use Case: Maintenance of Factory and
Automotive Components. In: SemProm – Foundations of Semantic Product
Memories for the Internet of Things, Wolfgang Wahlster (eds.). Springer-Verlag,
Berlin, Heidelberg, 2013, pp. 363-380.
[12] Anderl, Reiner; Trippner, Dietmar (eds.): STEP – Standard for the Exchange of Product
Model Data. B.G. Teubner, Stuttgart, Leipzig, 2000.
[13] http://www.ap242.org – last visited on 2014-07-18
[14] International Organization for Standardization: Application protocol: Product life cycle
support. In: International Standard ISO 10303-239:205 - Industrial automation
systems and integration — Product data representation and exchange, Geneva,
2005.
[15] Picard, André; Anderl, Reiner; Schützer, Klaus: Controlling Smart Production Processes
Using RESTful Web Services and Federative Factory Data Management. In: 14th
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
69
Asia Pacific Industrial Engineering and Management System, 2013, Cebu,
Philippinen.
[16] Picard, André; Anderl, Reiner: Smart Production Planning for Sustainable Production
based on Federative Factory Data Management. In: Proceedings of TMCE 2014,
Imre Horvath, Zoltan Rusak (eds.). Budapest, 2014, pp. 1147-1156.
[17] Strang, Daniel; Galaske, Nadia; Anderl, Reiner: Beschreibungsmethode für die
Repräsentation cyber-physischer Produktionssysteme. In: Entwerfen, entwickeln,
erleben, Ralph Stelzer (eds.). TUDpress Verlag der Wissenschaften GmbH,
Dresden, 2014, pp. 13-26.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
70
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
71
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
72
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
73
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
74
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
75
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
76
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
77
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
78
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
79
80
Marcio Weichert
Marcio Weichert é, desde maio de 2012, coordenador do Centro
Alemão de Ciência e Inovação São Paulo (DWIH-SP) e coordenador
do programa acadêmico e científico do Ano Alemanha + Brasil 2013-
2014. Bacharel em Comunicação Social pela Universidade Federal
Fluminense (UFF), em Niterói-RJ, fez carreira como jornalista no Rio.
Atuou nos jornais O Dia e O Globo, na Bloch Editores, bem como em
assessorias de comunicação e imprensa e como editor independente.
Na Alemanha, trabalhou na Deutsche Welle, a emissora internacional
da Alemanha. De volta ao Brasil, fez pós-graduação em Gestão
Estratégica na Universidade Cândido Mendes (UCAM) e tornou-se
assessor de marketing e comunicação do Serviço Alemão de
Intercâmbio Acadêmico (DAAD), função que exerceu de fevereiro de
2006 a maio de 2012.
Centro Alemão de Ciência e Inovação São Paulo
Projeto de iniciativa do Ministério das
Relações Externas da Alemanha, o Centro
Alemão de Ciência e Inovação São Paulo
(DWIH-SP) nasceu em 2009, tendo
funcionado provisoriamente na Câmara de
Comércio Brasil-Alemanha até 2011. Em
fevereiro de 2012, foram inauguradas suas
atuais instalações, com oito escritórios e uma
sala de reuniões. Sua principal missão é
servir de ponto de encontro e ponte para
instituições e profissionais dos meios
acadêmico, científico, de inovação e de
fomento da Alemanha e do Brasil. Três
agências de fomento, cinco representações
de instituições de ensino superior alemãs e a
sociedade de pesquisa aplicada Fraunhofer
estão reunidas no DWIH-SP. As instituições
de ensino e pesquisa alemãs buscam
cooperar com a indústria no Brasil, sejam em
projetos de pesquisa e inovação, sejam na
capacitação profissional.
81
Cooperação com Universidades Alemãs:
Oportunidades para a Indústria no Brasil
Resumo
O Centro Alemão de Ciência e Inovação São Paulo (DWIH-SP) busca, entre outros
objetivos, aproximar instituições de pesquisa alemãs e empresas no Brasil para
cooperações de vários tipos. A palestra informará as opções. Como coordenador da
programação científica da Temporada Alemanha+Brasil 2013-2014, o DWIH-SP
estimulou eventos com este objetivo. A palestra apresentará um resumo das iniciativas
em andamento.
Palavras chave
Ciência; inovação; pesquisa; intercâmbio; cooperação; fomento; universidade-empresa.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
82
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
83
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
84
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
85
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
86
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
87
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
88
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
89
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
90
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
91
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
92
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
93
94
Dr. Andreas Romberg
Dr. Romberg was born in 1962 and studied mechanical engineering
at the University of Kaiserslautern, Germany, where he received his
Diploma in 1988. In 1992 he earned his Dr.-Ing. degree in production
engineering and business organization also at the University of
Kaiserslautern. Dr. Romberg gained profound lean and managerial &
leadership knowledge during his industrial career working for several
automotive suppliers within production and as a plant manager. He
also implemented different lean systems with focus on production and
supply chain within this period. Since 2003 he has been working as a
business consultant and management coach for Staufen AG. He is
Head of Business Unit „Innovation and Product Development“. His
core competencies are: Lean Management in Innovation and Product
Development; Project Management in multi-project environments;
Shopfloor Management; Implementation of holistic Value
Management Systems; Ramp-up Management. Dr. Romberg has
authored or co-authored 2 books and about 20 papers.
Staufen AG
Staufen AG is one of the leading Lean
Management consultancies in Germany. As
"Partner on the way to Top-Performance", the
internationally operating consulting house
supports companies in optimising their value
creation and management processes as well
as increasing the efficiency of their innovation
and product development processes.
Furthermore, the consultants develop
concepts to manage crisis situations as
turnaround or interim managers. With the
Staufen Academy, the consultancy also
offers certified practice-oriented training.
More than 200 employees look after
customers on site from offices in Germany,
Switzerland, Italy, Poland, Czech Republic,
Hungary, Slovakia, China and Brazil. The
recent Lünendonk® 2013 trend study on
"Performance - growth strength of
management and IT consultancy companies"
ranks Staufen among the consulting houses
with the strongest growth over the last five
years.
95
Frontloading is a Key Success Factor and a
Basis for Efficiency and Effectiveness of NPI
Projects
Abstract
There is a saying in Germany: “Tell me how you are starting a project and I will tell you
how it will end up!” Nothing has been more confirmed in our 10 years of project experience
within Lean Development than this saying. Most of the projects we saw life in the multi
project environments of our customers have been started without taking advantage of
better input up front the project.
Frontloading anticipates problems in a project before they even can occur. That kind of
early risk assessment and advanced problem solving helps to reduce risks. Good
Frontloading starts with the input of a sufficient customer/ market specification data to
make sure that especially engineering has understood the content as well as clarified the
priority of conflicting features and functions. Frontloading, from the organizational point of
view, is a very cross-functional approach to collect all the ideas, problems and other
relevant issues of all NPI (New Product Introduction) process related functional
departments. Even the inclusion of key suppliers is helpful. The outcome is a whole set of
solutions partly based on already existing solutions which helps to reduce effort, risks/
quality issues and costs. Frontloading also enhances the team-building process. The
common assessment of specifications, anticipation of possible problems and risks in early
stages of the project creates a common awareness of the key success factors in the
project. This contributes to a higher commitment of team members to the project.
The lead-time of a well-moderated frontloading process from our experience lasts about a
third of the whole lead-time of a product development process. Our recommendation: Have
the courage to spend this time because it will help you to save more time during following
realization and validation phase.
Keywords
Set based concurrent engineering; point based engineering; cross-functional approach;
maturity model for predevelopment; early risk assessment; efficiency; effectiveness; lean
development system.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
96
1 Introduction
As the Chaos Institute considered in its Chaos Report 1994 [1], 82% of all projects do not
achieve the project targets and/ or customer requirements.
Figure1: Achievements of objectives of projects [1]
That means projects do not complain with planned deadlines (performance delivery) or they
exceed the planned budget and product costs. Sometimes projects compromise in terms of
quality by missing certain functions and features. This has multiple root causes. One of the
major root cause is missing cross-functional frontloading. That means we miss the chance for
projects to:
Verify the completeness of all necessary and sufficient input data about specification and
frozen objectives especially of the customers’ side.
Use common and cross-functional knowledge about the project tasks including the
knowledge of key suppliers, which supplement the projects with their core competencies.
Re-use standards for parts, modules and technologies; avoid re-inventing the wheel.
Verify the maturity of technologies coming out of pre-development processes. Lack of
maturity of technologies often leads to unnecessary and costly loops within product
development projects.
As shown in Fig. 2 the above-mentioned circumstances of missing or bad frontloading first of
all normally cause high effort in late project phases. And the second aspect of this additional
effort is that this is normally a not planned effort.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
97
Figure 2: Missing or bad frontloading leads to high effort in second half of projects [2]
An additional amplifying effect occurs when imbalanced project pipelines meet missing or bad
frontloading. We more frequently recognize that the project environments of companies have
most of their projects in late phases due to the fact that engineering has to support production
facilities ramping up the new products longer times after SOP. Compared to that there are
only a small number of projects in early phases. Combined with high-unplanned project effort
within the late phases companies are often firefighting and have no time/capacity to frontload
new projects. This very early starts to become a vicious circle.
Figure 3: Imbalanced project pipeline meets projects with high effort in late phases
To get out of that situation companies must start with additional effort to get frontloaded
projects. Step by step the red curve in Fig. 4 will move to the direction of the blue curve.
Frontloaded projects have the most of their effort in the first half of the NPI process and this
effort is planned.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
98
Figure 4: Ideal state: Frontloaded projects have most effort in the first half of the project
2 About Frontloading
It is common knowledge that (product-) costs are determined by Engineering (Fig.5) in early
phases of NPI processes [3] hence it is strictly recommended to take care about well-done
frontloading.
Figure 5: The determination of costs takes place in the first phases of NPI process [3]
Frontloading supports effectivity and efficiency within NPI process; typical characteristics of
good frontloading are shown in Fig. 6:
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
99
Concept phase/ frontloading lasts round about 1/3 of a whole NPI project.
Clarifies all necessary and sufficient information about project tasks and objectives, such
as market and product specification.
Frontloading is a cross functional discipline; all necessary functional departments are
represented within the frontloading team to support the process with their knowledge.
The frontloading team is working highly integrative within cross-functional workshops
moderated by the chief engineer (= project lead).
The cross functional workshops ideally are taking place in a big project meeting room
(= OBEYA) with visual management of all relevant information.
After clarification of the product specification, the team is working in sub phases on
functional models and product architecture with a set based approach.
The product concept will be narrowed by the following sub phase “concept aggregation
& evaluation”.
Frontloading ends up with a clear written system specification, which contents all
information how the new product will be realized. This specification ideally is frozen after
that milestone (M3).
Figure 6: Characteristics of frontloading [4]
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
100
Comparing traditional NPI processes/ projects with a Lean NPI process using frontloading it
is possible to reduce lead-time > 25 … 30%. Even though spending more time as usual in the
first phase due to a longer frontloading, the lead-time of the whole project will be shortened
by the reduction of realization and validation phase (see Fig. 7). That is the result of permanent
reconciliation within the cross-functional workshops discussing and solving future problems
before they occur and avoiding risks normally followed by time and budget consuming process
loops. Doing the things right – right from the start.
Figure 7: Frontloading: The effect of effective collaboration [4]
3 Set Based Concurrent Engineering
Set based concurrent engineering is a process approach, which in contrast to the traditional
point based product development requires multiple design solutions, outlining how Japanese
companies gain advantage in delaying design decisions by relying on sufficient knowledge
[5].
As illustrated in Fig. 8, the point based approach limits the design space upfront, hence
providing less flexibility to adjust design solutions among the different product development
functions. Set based approach on the other hand enables product development functions to
explore design space and converge to an optimum design solution during the set narrowing
phase [6]. Set based concurrent engineering is a knowledge intensive process that comprises
the communication, trade-off and narrowing down a set of potential design solutions whilst
proceeding in product development [7].
Once a reasonable solution has been examined (end of narrowing phase) the cross-functional
fine-tuning and adjustment starts within a kind of problem solving or problem correction phase.
In case of an unresolvable problem the team can with a small step back choose an alternative
solution out of the former solution set.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
101
Figure 8: Point based vs. set based engineering [6]
In contrast to that within the point based approach every pretended step further is very often
also combined with bigger changes and adjustments which are time consuming and often very
costly.
Figure 9: Effective among others means “using existing knowledge and experiences” [8]
Providing the right knowledge to the right time is the key issue within Lean Development
processes. A three dimensional model of knowledge management has been emerged to be
vital for effective product development [8].
Horizontal dimension (X) symbolizes that knowledge is required to sequentially proceed in the
product development process. For example, in the design (D) function the knowledge acquired
in the concept (D1) phase, such as new customer requirements, is provided to the detail
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
102
design team in order for it to be realized in the new design. Vertical dimension (Y) exemplifies
that knowledge needs to be obtained or shared within other functions in the product
development process. This can include sharing knowledge concurrently between the
manufacturing (M) and design (D) function during the concept phase in order to assure that
manufacturing feasibility is considered at an early stage of the product design process.
Previous projects dimension (Z) embodies knowledge a company has acquired in the past.
For instance, during validation (D3) in the design (D) function, the product development
engineer retrieves proven test configurations from previous projects in order to initiate the
validation process [8].
Representing, sharing and shifting the knowledge in a way that it can be easily adapted is the
challenge. Because a big part of the knowledge is tacit knowledge driven by lots and lots of
experience, which is actually difficult to represent.
Experienced driven knowledge also means that companies have to handle lots and lots of
data. There are two interesting methods to represent such kind of data.
One shown in Fig. 10 are “trade off curves” which is already used for a long time by TOYOTA
[9]. Trade off curves are showing correlations of different impacts on certain product design
issues. The example in Fig. 10 shows some correlations for the design of a car seat structure
[8] such as product unit cost vs. production volume or material cost vs. weight and so on. Such
knowledge representation combine “big data” volumes on some easy to read, handle and
maintaining graphs.
Figure 10: Examples for trade of curves [8]
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
103
The second (Fig. 11) shows how to capture and provide knowledge coming from A3 problem
solving processes.
Figure 11: A3 problem solving template completed by 2 steps to capture and provide knowledge [8]
Fig. 12 shows an example of an A3 problem-solving template completely filled. The knowledge
is captured within decisive design rules or design recommendations to be applicate for similar
future designs in a definite process phase.
This knowledge could easily be provided within a database.
There are many other partly well-known methods to increase effectivity in product
development processes such as: QFD, value analysis, value engineering, design for
manufacturing and assembly, value management for complexity etc. These methods are also
applicable within frontloading – the earlier the better.
Efficiency means “do the things right”. What causes the effect of efficiency within frontloading?
As shown in Fig. 13 the effect of being efficient can be recognized by a tremendous lead-time
reduction. Good frontloading within product development enables us to switch from a
sequenced NPI process to a highly parallelized NPI process.
Throughout an intensive cross-functional discussion on the best product design we can find a
very good reconciliation between the different relevant functions. Everyone has a clear picture
what to do and can work in parallel with all the other functions.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
104
Figure 12: Example for a completed A3 problem-solving template [8]
Figure 13: Efficiency effect caused by frontloading
In case of any problem, open issue or question the team together will work on a cross
functional solution supported by OBEYA and visual management as the major tools.
So while Engineering & Development is working on the best product design the Process
engineering is working on the ideal processes. Even the market development & introduction
can be work out by Product Management in parallel.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
105
4 Summary
Frontloading as a part or a principle of Lean Product Development is a process approach
narrowing a final product design out of a set of feasible solutions (design space) which have
been worked out within a cross functional team supported by the application of some methods,
tools and techniques. By using an OBEYA, project-/ process related communication within the
team is parallel and almost free of interfaces. Visual management supports the product
development process and team discussion with all necessary and sufficient information such
as calculation data, BOMs, sample parts, competitor information and parts etc.
The application of frontloading happens in very early stages of a product development process
long before the release of major investment, tooling issues and so on. Frontloading from the
beginning also focusses strongly on external and internal customer satisfaction (“doing the
right things” effectivity) as well as short lead times (“doing the things right” efficiency).
Resources are also able to invest their capacity because they are not planned out by 100%
but only 75 … 80% of their theoretical available capacity. So they are able to put in their
knowledge.
This from our experience helps to reduce lead-time tremendously by avoiding a lot of waste
within traditional approaches and processes. Some of our customers reduced lead-time up to
60% and they improved their project throughput up to 40% by the same amount of resources!
Normally due to the fact that lead-time reductions also cause a higher project throughput the
innovation rate also increases from the lower one-digit ranges up to 25 … 30%. Innovation
rate thus describes the part of the annual turnover with products younger than the half of their
typical life cycle.
5 References
[1] Chaos Report (1994). The Standish Group
[2] Romberg, A. (2010). “Schlank entwickeln, schnell am Markt - Wettbewerbsvorteile durch
Lean Development“. Log-x-Verlag.
[3] Lindemann, Mörtl (2008): „Kostenmanagement in der Produktentwicklung“ (= “Cost
management in product development“) Chap.1, Part 1
[4] Romberg et al (2013): “Lean Development Trainer”; Training material Staufen AG.
[5] Ward, A. C. (2007), Lean product and process development, Lean Enterprises Inst. Inc.
[6] Ward, A., Liker, J. K., Cristiano, J. J. and Sobek, D. K. (1995), "The second Toyota
paradox: How delaying decisions can make better cars faster", Sloan management
review, vol. 36, pp. 43-43
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
106
[7] Sobek, D.K.; Ward, A. C.; Liker, J. K.(1999). “Toyota’s Principles of Set-Based Concurrent
Engineering”. MIT Sloan Management Review.
[8] Maksim Maksimovic (2013), "Lean knowledge life cycle framework to support lean
product development”, PhD Thesis, Cranfield University, England.
[9] Liker, J. K.; Morgan, J. M. (2006). “Toyota Product Development System”. Taylor &
Francis Inc.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
107
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
108
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
109
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
110
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
111
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
112
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
113
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
114
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
115
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
116
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
117
118
Dr.-Ing. Peter Binde
Dr. Binde was born in 1970 and studied mechanical engineering at the
Universität Darmstadt, Germany, where he received his diploma in
1997. Towards the end of his studies, he began working as a
freelancer consultant in CAD/CAE. He received the Dr.-Ing. degree in
Mechanical Engineering at the Universität Darmstadt in 2004. In 2005
he founded Dr. Binde Ingenieure, Design & Engineering GmbH, a
company that specializes in CAE consulting all around the Siemens
NX System. The company grew steadily and now employs engineers
who are all experts for product simulation. The fields of expertise are
Structural Mechanics, Rigid Body Mechanics, Fluid Mechanics,
Thermodynamics, Electrodynamics and the integration of all this in
PLM. 2009 he established a code for electromagnetic analysis
integrated in the NX System. For this he performed government-
funded research projects together with the Universität Darmstadt and
University of Liège, Belgium. From 2008 to 2012, he taught Numerical
Structural Analysis and Multi-Body Dynamics at the RheinMain
University of Applied Sciences. Since 2011 he leads the German CAE
Special Interest Group in the PLM Connection, a user group which
meets twice a year on the topic of simulation.
Dr. Binde Ingenieure, Design & Engineering GmbH
119
Recent Approaches of CAD/CAE Product
Development. Tools, Innovations,
Collaborative Engineering
Abstract
In this paper, the latest approaches in the field of CAD-CAE product development are
presented, as they are applied in industry. Innovations in the software tools are shown
such as they arise from multi-physical simulation technologies. The implementation of
these processes in collaborative engineering is discussed, such as the relation between
OEM and supplier.
Keywords
CAD; CAE; Simulation; Product development; Collaborative engineering.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
120
1 Introduction
In former times integrated CAD analysis tools were limited to basic applications only. These
were mainly linear Finite Element Analysis (FEA, FEM) types for strength analysis and Multi
Body Dynamics (MBD) analysis for kinematics.
The focus of these tools was the design- and not the analysis-engineer. Goal was easy setup
of analysis models and fast responses to enable designers for A-B comparisons and
decisions. Designer’s analysis tasks are typically characterized by less abstraction
techniques, so his 3D CAD models should not be modified or idealized very much for analysis.
Consequently meshing for FEA was performed by simple tetrahedral elements which can well
be automatically created on solid geometry. These element types have been designed in such
a way that for the basic discipline of linear statics even poor quality element-shapes already
led to relatively accurate results. Therefore adaptive meshing strategies and high-grade
polynomials were developed in FEA shape functions. Still a problem for designers is correct
validation of strength results, so decisions about strength are usually not done by them rather
by analyst- or measurement engineers.
Analysts in former times never used CAD integrated simulation tools, because of their usual
need for more abstraction and complexity in geometry and physics. Missing functionalities
relate in particular to possibilities for non-linear simulation (contact, material and geometry),
advanced material laws, advanced meshing techniques with shells, beams and hexahedral
elements and the coupling of different simulation methods. Additionally in many cases there
exist self-made software codes for individual problems which must be coupled or integrated
to FEA or MBD systems to be efficient.
One more limitation in former systems was the focus on mechanical engineering only. Other
engineering disciplines like electrical-engineering, control-engineering and system simulation
were not supported.
The situation in today’s large CAD software vendors is characterized by the fact that they more
and more must satisfy needs coming from big OEM customers such as automotive and aircraft
industries. This leads to large software vendors take over smaller companies that have
specialized technologies and try to include these technologies into their major system.
Competition around these specialized technologies is running and the question how to
integrate all these technologies efficiently into the main system becomes crucial.
That’s why more and more specialized high-end CAE software becomes integrated into major
CAD systems. Analysis engineers now more and more do find their special functionalities that
were missing in the past. This is one focus in this article.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
121
Figure 1: Disciplines integrated in CAD/CAE systems
Elementary disciplines that are integrated in most major CAD/CAE systems today are
Strength Analysis computing displacements, stresses and strains through FEM,
Dynamic Responses of Structures for free or forced vibration effects by use of FEM,
Multibody Dynamics taking into account rigid body motion (MBD) to compute
displacement, velocity, acceleration, joint-force and
Thermal Analysis for thermal conduction, convection or radiation by FEM.
The following two disciplines are more advanced and currently at the beginning of becoming
popular in major systems:
Computational Fluid Dynamics (CFD) for pressure, velocity, turbulence through use of
Finite-Volume-Method (FVM) and
Electromagnetic Analysis (EM) for forces, eddy-currents and field-strengths computed
by FEM.
Stand-alone tools of course are there and are powerful in their respective fields. But the
challenge today for OEMs is the utilization of integrated CAD/CAE software that does allow
for adaption to needs. Stand-alone tools must fit in this structure. So interfaces play an
important rule.
Backbone for all of this is Product Data Management (PDM), what in area of CAE turns out
as Simulation Data Management (SDM).
2 Multiphysics Solutions
While in the past solutions for those elementary disciplines mentioned above have been in
focus today and in future there are more and more solutions for coupled problems needed.
Following we describe some main types of those solution types, how they can be performed
and in which industrial applications they are used.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
122
2.1 Thermal / Structural one Way
One way thermal structural coupled analysis does first compute for temperature fields and
then apply those temperature fields as loads to structural models. This is needed in all fields
of strength analysis cases where thermal expansions plays a role. An example are motor
housings.
Since mapping of temperature data from a thermal mesh to a structural mesh through
interpolation methods is not very complicated this analysis type is not difficult to perform. It
can be done in most integrated CAD/CAE systems today.
2.2 Thermal / Structural two Ways
A two way coupled thermal structural analysis is much more sophisticated. Temperature loads
lead to structural deformation similar to the simple one way coupling described above. But the
two way approach takes into account that deformed models may lead to different thermal
conditions. This particularly appears if there exist contacts that – if closed - transfer thermal
fluxes. Example applications for this are screwed container seals in nuclear plants.
This type of analysis is much harder to perform since iterations must be carried out and some
convergence criteria must be controlled. Also meshes are needed that are good for the
thermal as well as for the structural part. Because of those many iterations result mappings
between different meshes should be avoided.
In todays integrated CAD/CAE systems this type of analysis is beginning to take place.
2.3 Thermal / Fluid two Ways
The combined analysis of thermal and fluid is carried out separately in rigid body regions and
in fluid regions. At all interfaces there must be solved for heat transfer conditions. Example
applications are cooling of electronic systems.
The analysis in rigid bodies is of simple thermal type. In fluid regions Navier-Stokes-Equations
are solved by CFD. Since CFD is already an iterative solution that takes temperatures into
account an application of rigid body temperatures is not very much more complicated.
Several systems today do have availability for this analysis type. But still this is not common
for most of them.
2.4 Fluid / Structural one Way
Forces and pressures arising from fluid lead to deformations. These effects are taken into
account by first analyzing for flow, capturing forces on walls from pressure results and
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
123
transferring them to following structural analysis. Again mapping between different meshes
must be carried out. Applications are stationary aircraft wing investigations.
Only some of the integrated CAD/CAE systems allow this analysis type.
2.5 Fluid / Structure Interaction (FSI)
The case FSI is fluid structural coupling in two ways. Fluid forces lead to deformations and
those deformations lead to different fluid conditions. Applications are aircraft wings and turbine
blades braking due to FSI oscillations.
FSI type analysis is currently not well established in the major integrated CAD/CAE systems.
2.6 Electromagnetic / Structural one Way
Electromagnetic forces, for example Lorentz-forces, are computed in the EM solver and
transferred to structural models to be solved for deformation, stress and strength. Applications
are minimum air-gap studies in electric motors. This analysis type and all following regarding
to EM, are possible in few systems only.
2.7 Electromagnetic / Thermal one Way
Losses that result from electromagnetic eddy-currents and hysteresis effects, are computed
in EM solvers and then used as thermal loads in following temperature studies. Application is
electric motor thermal analysis. Few systems only allow this type of analysis.
2.8 Electromagnetic / Thermal two Ways
Again losses are computed by EM and used to find temperature fields in the second step. But
now those temperatures lead to different material-properties and back influence the EM result.
Particularly the electric conductivity in electro-sheets of motors varies heavily with
temperature. So common applications are electric motors again. Again, only few systems
allow this type of analysis.
2.9 Control-System / Dynamic Response
For example in machine tools, vibration behavior is improved with controller circuits. For
simulating these effects either control system models must be integrated into FEA or FE
models must be integrated into control system models. Few systems only allow this type of
analysis.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
124
3 Solver Languages
All major FEA solvers today provide thousands of commands that allow analysis of very
special problems. In common cases only small percentages of all commands are used in the
analyst’s daily work. User interfaces allow easy finding necessary commands for the daily
work.
One recent approach addresses general ways how to implement new solver technologies in
CAD/CAE systems. The need for this comes from the fact that more and more special
technologies must be implemented in large CAD/CAE systems. This method utilizes so called
solver languages and a neutral language for solvers. Currently this is developed for FEA
solvers, but in future it may be available for other types like MBD too. Key idea is that all input
data for any FEA solver can be classified by the following set of objects:
Element Quality Checks: Special quality checks for the considered solver.
Solution Class: Description of all solutions that characterize the solver, for instance
Thermal or Structural or Electromagnetic.
Sections: One-dimensional elements may need various sections.
Elements: The various element types a solver can handle.
Physical Property Tables: All physical properties like material data.
Modeling Objects: Additional data blocks.
LBCs: Loads, boundary conditions, constraints and related data.
Solution: Detailed description of the physical solutions that the solver can perform.
By use of these solver languages companies can implement their own solvers with specialized
capabilities into the commonly used CAD/CAE system. This increases collaboration
effectiveness between different analysis groups in companies.
The software vendor has another advantage: He can easily and fast implement new solver
technologies into the CAD/CAE system.
4 Master Model Approach
While simple analysis types – linear FEA and MBD Kinematics - became integrated into CAD
systems some basic techniques were developed that allowed associativity between CAD and
CAE data. These techniques resulted to be very successfully and today are still exploited by
CAD/CAE systems. Of course the master model approach is used there basically. This means
that all data for downstream processes is held in separate files being connected to the CAD
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
125
master geometry. If the CAD geometry changes everything can update. Also this gives the
basic possibility for engineers working concurrently on a digital product.
5 Designer / Analyst Collaboration
Next basic approach is the idea that CAE objects are linked to CAD objects. CAE Objects
describe the CAE problem, such are forces, meshes, boundary conditions, material properties
and others for FEA and similar links, joints, drivers, sensors for MBD. CAD objects are faces,
edges, bodies and vertexes. While these CAE objects are connected to CAD objects fully
automatic updates after geometry changes are possible. As an example you can imagine a
CAE force object. The force object stores its magnitude and direction. The direction may be
set to perpendicular to a CAD face. So if the CAD face changes because of designers work
this force will update to a new direction. The following figure shows an example of MBD objects
referencing CAD objects.
Figure 2: Associativity CAD to CAE
One newer approach supports concurrent engineering between CAD designers and analysts.
In general also analysis engineers need to modify CAD models. Commonly there must be
done simplifications, defeaturings, midsurfaces and other modifications. Therefore they need
to modify CAD geometry but it is not allowed to modify the CAD master. So this approach
offers an additional CAD model, we call it idealized CAD model, which is placed between the
origin CAD master and downstream CAE files. Associativity between the origin CAD master
and this idealized CAD model must be given by using associative geometry links. By this way
changes in the CAD master lead to updates of CAE data. Nevertheless CAE engineers do
have possibilities to modify geometry.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
126
Figure 3: Idealized file and its integration in the CAD, CAE file structure
6 Design-Embedded Analysis / CAE-Experts Collaboration
A further approach for the support of concurrent engineering between design- and analysis
engineers is given by the following. There are CAE software tools used by design-engineers
and there are other tools used by analysis engineers. Both must have access to the CAD
master so in the first step they simply can be placed parallel in the master model approach.
But there are one or two additional data exchanges necessary because design-engineers may
want to transfer their CAE models to analysis engineers to make it possible to see and check
what is done there and maybe to use parts of it in more sophisticated simulations. This is the
first additional data exchange and the second one, which is optionally only, allows improved
models from analysis engineers to be back transferred to design engineers. These exchanges
between design- and analysis engineers can be realized in various ways. An optimal solution
would be if they both worked with exactly the same software, so all files could be shared. A
good compromise is to use the same solver, so data exchange can be performed via solver
input files. In many practical cases today there is still no digital data exchange between the
two groups, models are set up multiple times and communication works via telephone or
meeting-sessions.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
127
Figure 4: Design embedded Analysis / Analysis Experts Collaboration
7 Data Management
The management of analysis and simulation data aims to integrate analysis and simulation
results in the workflow of virtual product development. For this purpose, this information is
embedded in a PDM environment. Background information can be found in the
recommendation [SimPDM]. An overview of the results of the SimPDM project group provides
[Anderl3].
Most manufacturing companies today face the challenge of having to develop faster and more
complex products. Design and simulation play a key role for the evaluation of product
development results. What is new for many engineers is that simulation is gaining an
increasing importance and for a higher development efficiency its integration with 3D product
modeling is a critical success factor.
This linkage problem is characterized by the following properties [AnderlBinde1]:
Personnel separation of modeling from the analysis,
Many different CAE software systems,
Many analysis variants,
Lack of relationship of CAD to CAE models,
Lack of process orientation,
Inadequate data protection,
Insufficient supplier integration.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
128
In our following discussion, we restrict ourselves to the solutions of the PLM system
Teamcenter from Siemens Industry Software GmbH and its CAE expansion modules, which
are known under the name of Teamcenter for Simulation. These solutions now offer solutions
for some of the above-mentioned problems or at least approaches to overcome them.
If in Teamcenter a standard CAE analysis is performed, the native files (Figure 3: Simulation,
FEM and Idealized) are assigned to the corresponding Item Revisions (CAEAnalysis,
CAEModel and CAEGeometry) as references (see next figure). These CAE Item revisions can
be revised independently. In addition, data is automatically provided with relationships. This
data model and the relations - somewhat simplified - are shown in the following figure [TCSim].
Figure 5: CAE Data Model used in Teamcenter
The relations have the following meaning:
TC_CAE_Defining: Therefore relationship can be traced, which CAEModelRev is used
by the CAEAnalysisRev, so which meshing is computed with a SIM file. For a
CAEAnalysisRev there can be only one CAEModelRev, because there can be only one
mesh for the computation.
TC_CAE_Source: This relationship indicates from which item revision a model has been
created, so what item revision was the source. It can be defined between CAEModelRev
and CAEGeometryRev or between CAEGeometryRev and CAD Master revisions. In
case that no idealized file is used, this relationship may also exist between
CAEModelRev and CAD master. There can be only one source at a time.
TC_CAE_Target: This relationship documents for which CAD-Master-Revision each
CAE-Item-Revision applies (from CAEModelRev to CAD -Master-Revision, from
CAEGeometryRev to CAD-Master-Revision). There may exist several TC_CAE_Target
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
129
relationships in parallel. An example of multiple parallel TC_CAE_Target relations is the
following: The simulation for a green part shall have validity for the identical blue, yellow
and red parts.
Using this data model, the desired relationships between CAD and CAE are now available.
Thus it can answer the questions: "Which CAD model belongs to which FEM model?" and
“Are there new CAD revisions for my FEM model?”. Also the problem of a high variety of
analysis variants is addressed. Additionally, these relations allow to automate approval
processes between design and analysis.
8 Literature
[SimPDM] ProStep iViP Recommendation “Integration of Simulation and Computation in a
PDM Environment (SimPDM)”. PSI 4, Version 2.0 2008
[Anderl3] Anderl R./Grau M./Malzacher J.: SIMPDM – a harmonized approach for the
strategic implementation of simulation data management. NAFEMS World
Congress 2009
[Anderl4] Anderl R./Malzacher J.: SimPDM – Simulationsdatenmanagement-Standard nach
Maß. In: CAD CAM, Nr.1-2, 2009, Pg. 38-41
[AnderlBinde1]
[TCSim] Training documentation for Teamcenter for Simulation. Siemens PLM Software.
130
Dr. Jorge Vicente Lopes da Silva
É doutor em Engenharia Química, mestre e graduado em Engenharia
Elétrica. Foi o fundador e coordena desde 1996 a Divisão de
Tecnologias Tridimensionais do CTI Renato Archer. Sob a sua
supervisão esta divisão desenvolve aplicações e projetos de pesquisa
em cooperação com o setor produtivo e academia no Brasil e exterior.
É membro de vários comitês científicos, participante e palestrante
convidado nas conferências mais relevantes de impressão 3D.
CTI Renato Archer
O Centro de Tecnologia da Informação
Renato Archer é uma unidade de pesquisa
do Ministério da Ciência, Tecnologia e
Inovação (MCTI) que atua na pesquisa e no
desenvolvimento em tecnologia da
informação. A intensa interação com os
setores acadêmico, através de diversas
parcerias em pesquisa, e industrial, em
vários projetos de cooperação com
empresas, mantém o CTI no estado da arte
em seus principais focos de atuação, como a
área de componentes eletrônicos,
microeletrônica, sistemas, displays, software
e aplicações de TI, como robótica, softwares
de suporte à decisão e tecnologias 3D para
indústria e medicina.
131
Additive Manufacturing in the Product
Development
Abstract
Additive manufacturing (AM), also known as rapid prototyping or 3D printing, is nowadays considered a groundbreaking technology for the production of high added-value products with great investment from the developed countries. Additive manufacturing began as a way to produce higher quality prototypes more quickly, with minimum human intervention. However, what happened during the almost 30 years during which this technology has existed is that there was a great migration to various sectors of the industry, thanks to the evolution of the AM processes and their associated materials. It is already common to see highly customized products of AM being used in medical applications, or some not so customized products used in aircrafts. This paper has the purpose of summarizing the technological evolution of AM, pointing out its most important applications as well as some challenging applications in some sectors in which product development is a critical element. Additionally, this paper intends to present final use applications of this technology as well as what has been happening in terms of standardization in the area. Finally, some potential impacts predicted in the manner in which the products will be produced, as well as their logistics in the future, will be commented.
Keywords
Additive manufacturing; rapid prototyping; 3D printing; product development; product
customization.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
132
1 Introduction
The 3D technologies are present in all domains, from the most simple product development,
optimization and production to the more complex products like in the aerospace industry. In a
broad definition 3D technologies can be classified into virtual and physical. The virtual ones
can provide computational models for many types of representation, simulation, optimization
and scientific visualization. The physical 3D technologies are responsible for transforming
virtual models into real objects. When using a layer-by-layer paradigm to build objects, it is
known as rapid prototyping and more recently called 3D printing by the non-specialized media.
The original name, rapid prototyping, was conceived in the sense that a prototype of a product
could be quickly and automatically created with any level of geometric complexity. A prototype
is the first of a series that is being used in many different industries to speed up new product
development cycle, lowering costs and increasing final quality.
Almost 30 years ago, a company called 3D Systems, today the biggest in this business,
launched in the USA the first commercial machine. It was the stereolithography apparatus
(SLA) invention of Charles Hull, co-founder of 3D Systems. In stereolithography equipment a
photopolymeric resin can be hardened by the incidence of a computer controlled ultraviolet
laser beam (Silva et al., 1999). Since then, a myriad of new technologies using many different
materials and processes became commercially available with many others in development or
at in research stage.
These new processes are everyday more present and focused in the real production every
day. In this context, the American Society for Testing and Materials – ASTM established in
2009 the Committee F42 on Additive Manufacturing Technologies to deal with this innovative
way of production. The Committee F42 scope is “the promotion of knowledge, stimulation of
research and implementation of technology through the development of standards for additive
manufacturing technologies” (http://www.astm.org/COMMITTEE/F42.htm). The very first
action of ASTM-F42 was to establish a standard terminology defining the official name of the
technology as Additive Manufacturing (AM). ASTM is integrating efforts with International
Organization for Standardization (ISO/TC 261) by means of a “Joint Plan for Additive
Manufacturing Standards Development”. The first joint plan session was hosted by ASTM in
June 2013. The plan is to integrate efforts in the area of test methods, processes, materials,
terminology and design in order to create international standards for the area. In this article
we will use, from now on, the term Additive Manufacturing or simply AM to be compliant with
the standards (ASTM, 2012) when referring to this technology.
The umbrella term AM encompasses a broad class of processes based on continuous
deposition of material, layer-by-layer, until a physical object is automatically built following
instructions from a computer with a virtual model designed in a Computer-Aided Design (CAD)
system (Figure 1). The material deposition can be achieved using highly specialized, high-end
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
133
machines, for serial production of metal, polymers and ceramics parts, or a composite
material, but can also be achieved with the new low-end so called “3D printers” that can be
acquired in many stores. The bigger companies on AM business are acquiring many of the
start-ups companies that produce this type of popular machines, closing the hardware and
software. Giants of the software area are becoming aware of importance of this type of popular
machines. Most recently, Microsoft announced 3D printing support for developers of Windows
8.1. Also, Autodesk (maker of AutoCAD) is supporting the development of specific software
to design human tissue and organs to be produced in the future in bioprinters, a variation of
AM for biological and medical use.
The AM is an evolution in course only compared to the personal computer (PC) revolution.
Today, a smartphone can have a processing power unimaginable 30 years ago with
insignificant costs and much higher processing capacity if compared to the former corporative
massive and expensive computers. Analogously, a 2D printer is today much more precise
costing thousands times less. The engineering development in electronics, software
development, control strategies, precise mechanics and communication (Internet) associated
to the new behavior in social networks, creates a fertile environment for AM evolution.
Figure 1: Physical object produced by a layer-by-layer deposition of material
The aim of this article is to highlight some of the AM processes, example of available
technologies and its applications and expected impact in high value manufacturing sectors.
Section 2 shows the categorization of Additive Manufacturing in classes of processes; Section
3 describes the AM main processes classifying them in one of the ASTM category; Section 4
brings a short discussion about the advantages of the AM in comparison with conventional
processes of production; Section 5 discuss materials available for AM and its challenges;
Section 6 highlights the AM as a convergence of the artisan production and mass production
as well as some applications that can corroborate this hypotheses. Section 7 highlights
potential impacts of the AM in global logistic. Finally, section 8 brings a general conclusion
about AM, including some expected impact it can cause in the future society.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
134
2 Additive Manufacturing Categories
There are more than 30 commercial AM processes with economic importance. In order to
organize these processes in classes, in 2012, the ASTM International Committee F42 on AM
voted on a list of process category, names and definitions. The processes available nowadays
and in the future will be included in one of the following seven categories, according to ASTM
definition (Wohlers, 2012):
1 Material extrusion is an AM process in which the material is selectively dispensed
through a nozzle or orifice.
2 Material jetting is an AM process in which droplets of build materials are selectively
deposited.
3 Binder jetting is an AM process in which a liquid bonding agent is selectively deposited.
4 Sheet lamination is an AM process in which sheets of material are bonded to form an
object.
5 Vat photopolymerization is an AM process in which liquid photopolymer in a vat is
selectively cured by light-activated polymerization.
6 Powder bed fusion is an AM process in which thermal energy selectively fuses regions
of a powder bed.
7 Directed energy deposition is an AM process in which focused thermal energy is used to
fuse materials by melting as the material is being deposited.
There is a strong need for standardization and regulations for materials and testing of AM
products including all aspects of the AM technology. There is still a long way for AM to be
widely applied in areas like aerospace and healthcare. Therefore, processes reproducibility
and materials composition are necessary to produce high quality parts with required properties
and durability for the application.
3 Additive Manufacturing Available Processes
Among the dozens of commercially available AM processes, the most economically significant
are highlighted bellow and classified into one of the seven ASTM defined categories:
3.1 Stereolithography (SLA)
SLA was the first commercially available process in 1986. In this process a laser beam of
specific wavelength hits selectively the surface of a photopolymeric resin deposited in a vat.
The resin gets hard to form a layer. Then, a platform inside the vat is moved down and another
resin layer is photopolymerized. The process repeats until finishing the whole part. Support
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
135
structures are built with the same material and are broken down after taking out the part. It is
a process in the category of Vat photopolymerization according to ASTM. In the beginning,
there were few materials available but today there are many options. All of the available
materials, mainly polymers, try to imitate the properties of regular material for industry.
3.2 Fused Deposition Modeling (FDM)
FDM is a process where a filament of material and a filament of support material are
automatically deposited on a platform by means of a heated extrusion head. The process is
repeated layer-by-layer until the physical model is finished. By the end, the support material
is taken out by means of an ultra-sound bath. This process is in the category of Material
extrusion as defined by ASTM. This process produces accurate models in many different
thermoplastic materials, including special engineering thermoplastics.
3.3 Selective Laser Sintering (SLS)
SLS is a process where a laser beam transfers energy into a surface containing a thin layer
of pre-heated powder material. A computer automatically controls the movement of the laser
beam focus. The energy transferred by the laser beam fuses specific areas of the surface.
After fusing one layer, another one is deposited and again the laser fuses this layer that will
glue in the previous ones. This is repeated until the physical model is finished. The remaining
non-sintered powder is taken out after finishing. This process is located in the ASTM category
of Powder bed fusion. It produces strong models in many different materials and composites.
There are two other important commercial processes that can be classified in this category.
The first is the Direct Metal Laser Sintering (DMLS) that uses the same concepts with a fiber
laser to melts down materials with higher melting point like metals and alloys. The second
process is Electron Beam Melting (EBM) that instead of using a laser it utilizes an electron
beam to transfer energy to a metal or metallic alloy powder bed. SLS is highly suitable to
process composite and functionally graded materials with cellular structures.
3.4 Multi Jet Modeling (MJM)
MJM is an additive process where a print head containing hundreds of nozzles selectively
spreads in a surface a photopolymeric material that is cured and hardened by the incidence
of a specific wavelength – normally an ultraviolet laser or lamp. Another print head spreads
support material, normally in form of a gel that is also polymerized. It is a continuous process
where the platform is lowered down a tenth of a millimeter for each layer. Finally, the support
material is taken out with water jet. It is a process classified, according to ASTM, as Material
Jetting. The company Objet Geometries calls this process Polyjet. Some of the Objet´s
machines are able to combine different material within a single 3D printed model. This
company provides a myriad of material that mimics regular plastic materials.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
136
3.5 3D Printing (3DP)
3DP is a process where a multinozzle print head selectively spreads a liquid binder in a
platform with a powder. The binder reacts with the powder to compose a layer while the
platform is moved down. The process repeats until the end of the part. There is no necessity
for support structures since the loose powder is responsible for stabilizing the part being built.
After finishing, the loose powder is taken out and the part is infiltrated with resin to increase
mechanical properties. ASTM classifies this process as Binder jetting. It is one of the most
popular today because of the low costs of acquisition and operation.
Figure 2 shows a diagram with the main commercially AM processing principle, materials
used, the process acronym and its schematic.
Figure 2: Schematic of the main AM processes, basic principle and type of materials that can be
processed
4 Additive Manufaturing versus Conventional Production
Beyond regular prototyping processes that were the first use of AM, this technology is
seriously entering the domain of production. Because its high flexibility AM presents many
pros and some cons when compared to conventional production processes. Among many we
can highlight the following:
Energy optimization – AM implies the use of energy only to transform the material only
enough. Conversely to conventional process, as metal milling process for example, in which
a material is transformed into a block of bulk material that is milled and the big amount of chips
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
137
has to be reprocessed (recycled) into a new block again and so on. According to the USA
Energy Department, AM can reduce energy costs in 50% and material costs in 90%.
Reduction in material waste – AM uses just enough materials to create pieces. However, this
is not completely true because sacrifice support structures sometimes are necessary and
some materials, in special polymers, it degrades with continuous use under heating.
Special tooling and speed – generally, additive manufacturing processes are slower than
conventional processes, but their speed is increasing in a very fast pace. There are some
advantages producing small and very complex parts when compared to conventional
processes. There is great flexibility to produce many different parts at the same time,
automatically, without the necessity of special tooling and fixtures. Today, the drawback of
additive manufacturing processes in comparison with conventional production processes is,
in general, the fast degradation of material properties (mainly polymers), stiffness, surface
finishing, costs and production time for big lots.
Design optimization – the use of additive manufacturing allows the designer to produce
complex shapes and moving parts without the constraints of conventional production.
Production of internal or hidden structures, conformal cooling channels, special passages for
cables, pockets for embedded sensors, actuators and optics, are also possible. The CAD
systems are not suitable for this task and new developments in CAD to represent complex
structures and diverse materials distribution from micro to macro sizes have to be developed.
AM will be useful and suitable to produce any structure for a simple product or for a complex
human anatomy, including organs mathematical representation. The latte will be responsible
for the development of a new class of specific CAD for healthcare as a BioCAD system (Silva
et al., 2012).
Figure 3 shows 10 principles of additive manufacturing that complement the previously
presented based on Lipson and Kurman (2013).
Figure 3: Ten principles of Additive Manufacturing, based on Lipson and Kurman (2013)
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
138
5 Materials Development for Additive Manufacturing
The ultimate goal of additive manufacturing processes is to produce physical models with
known and predictable properties. The commercial additive manufacturing systems
developers offer a huge amount of material choices but they are mostly specific for one type
of process and many times for a specific machine. There are developers that have almost 60
different materials for their processes. Each of their material offer specific capability to meet
specifications of form, fit, and function needs. Normally they defend their choices of proprietary
arrangements promising the best features you need but it is mainly a matter of Market. The
additive manufacturing materials are still very expensive proprietary solutions.
In some processes the development of a new material that behaviors “like” a well-established
material in industry is a challenge. Therefore you can see offers of the type “ABS-like” or
“Polyethylene-like” and many others that simulate the required features of a regular industrial
material but it is not exactly the same. Even when the suppliers specify their material as
“industrial grade” the final part produced using it does not have the same properties of the
regular injected or milled material, found in industry.
The development of materials that fit the AM process aiming certain application with a
minimum of waste and a maximum of functionality is paramount for the future of production.
Figure 4 depicts today’s possibilities of materials for additive manufacturing. These materials
will be shortly explained in the next paragraphs.
Figure 4: Materials for additive manufacturing
The polymers are the biggest class of material for AM. The polymers can be a thermoset or a
thermoplastic and be found in many different forms like liquid, semi-liquid, powder, filaments
and sheets, depending on the process to be utilized. The most important categories are the
epoxies, acrylate epoxies, Acrylonitrile butadiene styrene (ABS), Polycarbonate, Polyamide,
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
139
Polyphenylsulfone (PPSF), polyetherimide (PEI), etc. The most common processes cited in
this article that run polymers are SLA, Objet and SLS.
Metals and their alloys are the second biggest class of material for additive manufacturing.
Theoretically any metal material or alloy can be used in form of powder as far as the
temperature is enough to reach the metal specific melting point. On the other hand, there are
some intermediate processes that glue metal powder using a polymer and after the green part
is fabricated it is sintered and infiltrated by a lower melting point metal in an oven like in the
SLS process. Direct metal laser sintering and metal fusion are implemented by DMLS, SLM
and EBM proprietary processes. The most common metals and alloys are the various
Stainless Steel alloys, Cobalt Chrome, Titanium Ti6AI4V/ELI, Titanium Grade 2, Inconel,
Maraging Steel, Aluminum, and many others. The metal applications for added valued industry
and medical applications are growing very fast.
Ceramic is the smallest class of regular material for additive manufacturing but it is growing
significantly due to the possibility to modulate ceramic materials in complex geometry with
details not possible when using regular production processes. There are different ways to
process ceramic materials: a) Direct and indirect laser sintering of ceramic powders (SLS); b)
Movable print head selectively deposits a binder onto a platform (3DP); c) sheets of ceramics
can be laser cut, stacked and bonded using adhesives and heat (this process is known as
Laminated Object Manufacturing - LOM); d) ceramic particles in a semi-liquid or aqueous
suspension can be extruded into a filament (FDM) and e) ceramic particles can be suspended
into a photocurable liquid monomer, which can be selectively cured (SLA). The most usual
process is 3DP, where a liquid binder glues layers of material, and afterward it can be
processed in oven or infiltrated with resins to acquire mechanical resistance. Special sand can
be sintered by means of the DMLS process to create molds for metal casting. The production
of ceramic parts is very promising in industry due the possibility to produce very complex
shapes and modulate material properties. The ceramic area still lacks accurate process
development and applications. The materials mostly used are sand, gypsum, Zirconia, Silicon
Nitride, Alumina, etc.
Composite materials can be a mix or combination of the formers in any proportion and it is
very common to find materials like a polyamide matrix filled with ceramic or metal like glass,
aluminum or carbon fibers. There are also photocurable resins with ceramic particles,
especially for AM microstereolithography systems like Ormosil - organically modified silica and
Ormocer - organically modified ceramics.
New processes and materials are becoming available to produce final parts. A complex
combination of composite materials - with better properties than when they are isolated
materials; functionally graded material (FGM) - a class of advanced materials that varies the
properties along its dimension; and cellular structured materials – that can obtain an optimum
material distribution reducing weight and costs, are being researched and finding new
applications every day.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
140
The recycling of plastic materials using AM can receive special attention from environmental
agencies and governments. There is a considerable amount of waste when post processing
for support removal or in powder based plastic material like SLS process that discards at least
30% of the material every batch of production, because of heating degradation of the polymer
powder. On the other hand, metallic materials produce little waste. Therefore, recycling is a
word that shall urgently enter AM dictionary.
Materials are responsible for a huge part of the AM providers’ incoming. The global AM market
reached $2.2 billion in 2012 with an increase of 28.6% for the last year, according to Wohlers
Associates Inc. a specialized consultancy in AM. It is still a small market (1,000 smaller than
conventional manufacturing in the USA) according to Lipson and Kurman (2013).
6 Uses and Applications of Additive Manufacturing
There are many well-known applications of AM. The initial purpose of the technology was to
create prototypes in a flexible and quicker way. With the evolution of the processes and
materials AM became a natural tool to solve some specific problems for small series direct
production (rapid manufacturing), tooling production, and more recently a powerful toll to
produce intricate and complex parts cost-effectively. AM is not yet a production process that
fulfills all the applications and industry requirements as dimensional, structural and surface
finishing. Parts produced in AM can be post-processed in conventional systems for a more
suitable and complete solution. Therefore, AM is not intended to substitute all conventional
production processes, mainly because of economical factors, but work integrated, at least in
the near future.
Although additive manufacturing is becoming an economically promising technology, it is now
almost impossible to expect that this technology can replace the mass production of parts or
components. It is still difficult to determine the cut-off volumes when comparing, for example,
plastic parts made on AM with injection molding production. On the other hand, AM flexibility
and increasing offer of materials can be a great solution for specific production of small series,
as well as for mass customization. Material and machines are expected to decrease price
occupying a more expressive market-share in the industrial goods sector.
Applications of AM are broad and present in areas like art, architecture, jewelry, consumer
products, entertainment, education, energy, electronics, paleontology, scientific visualization,
nanotechnology, automotive, aerospace, aeronautics, medical, dentistry, tooling, just to name
a few. Our mind is the limitation for AM application. The applications are driven today mainly
by the higher value-added goods and complexity of the solution that AM can help to solve.
Figure 5 shows the AM as a convergence of the benefits of mass production and artisan
production. In some extent AM can be close to the artisan solution or even the mass-
customization production but it is very difficult that in the future mass production will be
realized in AM due to the very specialized and optimized solutions like milling, plastic injection
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
141
and so on. Then, AM will play a special role in the industry but not substitute conventional
production as a whole.
The recent world crises, started in 2008, highlighted the manufacturing sector as one of the
most affected. It is the economical basis for industrialized countries corresponding to about
16% of the GDP and responsible for 30 to 55% of the jobs. The high value-added products
have an important participation in this percentage hiring a very specialized work force. In this
context, AM appears as one of the new enabling technologies for a series of advancements
and the basis for mass customization in the modern manufacturing (McKinsey, 2012).
Figure 5: Potential use of Additive Manufacturing as a convergent technology
In terms of the importance of the AM technology, every year Gartner Group assesses about
1900 information technologies in its report called “Hype Cycle for Emerging Technologies”. In
2012 AM (referred as 3D printing in Gartner’s report) is positioned together with its medical
variant “bioprinting” as one of the fastest growing for the next years (http://www.
forbes.com/sites/gartnergroup/2012/09/18/). In 2013, the same study reported AM in two
different points of the graphic “Customer 3D printing“ in the “peak of inflated expectations”,
probably because of the low-end printers being sold everywhere directly to customer and
“Enterprise 3D printing“ in the “slope of enlightenment” as a mature technology for industry
direct production but still far from its potential applications (http://www.gartner.com/newsroom/
id/2575515).
Today the most appealing areas for AM are the healthcare and aerospace industry. Medical
and dentistry demand highly customized solutions to fit a specific patient. Aerospace and
aeronautical industries involve highly complex product in small series. Both areas are strictly
regulated by national and international standards and agencies. These two applications are
more detailed bellow:
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
142
6.1 Healthcare
Today the application of AM in healthcare is one of the most promising using AM. The
fulfillment of needs and customization that the technology can reach is a good solution for a
specific patient’s needs. The most known use is the medical model (biomodel) for precise
surgical planning. A biomodel is a perfect replica of the patient produced based on
computerized tomography (CT) or magnetic resonance imaging (MRI) dataset of this patient.
The dataset is processed using specialized software that can generate a virtual 3D model in
a specific file format with the anatomical region of interest for AM production. It is possible to
export the processed files to CAD systems and generate customized prostheses for a patient.
During this process a simulation of the interaction implant-anatomy structure can be useful.
As an example, Figure 2 shows a complete cycle for a hemimandible production due a tumor
resection. Medical images from CT are acquired from the patient and a 3D model (STL file
format) of the mandible is produced using specific software (as InVesalius, an open source
software developed by CTI-Brazil) and translated into surfaces using the BioCAD approach
(Noritomi et al., 2011) (see Figure 6(a)). The missing part of the mandible is redesigned
considering biomechanical requirements. A mesh is then generated for simulation using Finite
Element Methods – Figure 6(b). The simulation involves bone and prosthesis made of
Chrome-Cobalt medical alloy with the DMLS process – (Figure 6(c)). The prosthesis is then
fabricated in the simulated material in AM (Figure 6(d)) (Delgado et al, 2012).
Figure 6: Implant production using additive manufacturing developed at CTI
Therefore, the above example shows that AM associated with other technologies can offer
solutions, for a temporary or permanent implant, with better functionality. So far, this
customized solution has not been cleared by the national agencies and its actual use depends
on approval from ethical committees.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
143
The growing and aging of the population, mainly in BRICS countries, where the life expectancy
is growing in a fast pace can demand very specific solutions for healthcare. Brazil increased
life expectancy in 18 years in the last 50 years, reaching 74.6 years in 2012. It can be
translated into needs for high-performance orthopaedic implants for a longer and active
lifestyle. A growing number of companies with AM personalized solutions for healthcare,
already CE-certified and FDA-cleared, is blooming. One example is a company in Italy called
Lima that produces thousands of acetabular cups every year (http://www.lima.it/technology-
trabecular_titaniumtm-1.html). Beyond prostheses, orthopaedic tooling and instrumentation
are billionaire and very competitive markets involving a high quality control. AM is already in
use in cutting edge companies that produce thousands of these devices but there is plenty of
room for improvements, optimizations, customizations and time-to-market reduction. Dentistry
is already an area of consolidate applications and active developments using AM, like in
orthodontics, dental implants, drilling guides, dental molds, forensic, metal infrastructures as
bridges and crowns, just to name a few. The main AM providers are investing in materials and
specific processes for direct implant production in plastic, metal and ceramic, as a strategic
market.
In the multidisciplinary research domain the integration of AM and tissue engineering is
showing its preliminary results. The combination of biomaterials and AM can produce
structured replicas of an anatomy with strict controls of porosity that is colonized by patient
steam cells. After some time the material is reabsorbed by the organisms and a new tissue or
organ is created. This approach is called “scaffold tissue engineering” that is being improved
in a very effective way using AM (Pereira et al., 2012). More recently a new approach for
tissue engineering using AM has been investigated. This new approach considers the
automatic deposition of cells or macrotissues (called tissue spheroids) as an additive
processes to produce organs and complex tissues. This is called organ bioprinting (Rezende
et al, 2012) and promises to revolutionize the way tissue engineering is today, producing
organs ready for implantation. In the next decades, positive results of organ bioprinting can
overcome organ shortage and complex logistics of natural organs donation.
6.2 Aeronautic and Aerospace
Aeronautic and aerospace industry is one of the most powerful and a natural candidate for
AM using in the next years. Some applications are already in production and others in
research labs. This section will provide a short view of these applications.
NASA launched a program to include AM in its operations to produce parts for satellites and
space exploration vehicles, in space, in the near future. In this sense, they embraced a
program in cooperation with Washington State University intending to use a moon material
simulant with the same composition of ground moon surface dust to produce parts for a lunar
base by means of SLS process. More recently NASA at the Marshall Space Flight Center
tested two AM manufactured subscale rocket injectors in a hot-fire environment with
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
144
temperatures over 3,315oC. It was a monolithic complex part built in less than three weeks
with 60% costs reduction that stand-up for almost one minute with the same performance of
the injectors traditionally produced (http://www.nasa.gov/exploration/systems/sls/
3dprinting.html). NASA is also carrying out parabolic flight to improve AM equipment
robustness and operability to make them more suitable for space applications to deliver,
during long flights, on demand spare parts (http://www.space.com/16656-space-
manufacturing-3d-printing.html#sthash.5avSw7bg.dpuf).
According to Michael Idelchik, vice president for advanced technologies at GE Global
Research, in four decades from now on GE will be able to print a complete engine. If it will be
happen, only time will tell, but GE Aviation is investing hard and recently acquired Morris
Technology and Rapid Quality Manufacturing, two AM pioneers in aeronautics. GE Aviation
is also in a joint venture with the Snecma from France to incorporate AM produced combustion
systems in their newest jet engines (http://www.gereports.com/printing-jet-engines/).
Boeing is a pioneer and a long-term user of AM to produce parts for planes. Among those
parts there are air ducts for F/A-18 Hornet fighter aircraft produced from 10 years ago. The
ducts were originally intricate parts produced in aluminum. Now they can produce air ducts as
monolithic part in SLS process using plastic powder FAA cleared. The main gain is design
freedom, no assembling or welding necessary, reduced weight and consequently costs
reduction. Boeing produces its own high standard material with improvements in SLS process
stabilization and monitoring to produce high quality parts for its planes (Lions, 2012). One of
the recent patents claimed by Boeing is a new concept for SLS continuous linear production
for high production of parts (US Pat Appl. 20120067501). Another company in the AM parts
production for aircraft is CalRAM, a spin-off from Boeing, founded in 2005, that produces
plastic and metal certified components.
The AVIO Group in Italy designs, develops and manufactures aerospace propulsion
components and systems for both for civil and military aircrafts. To overcome traditional
investment casting and achieve outstanding properties, more complex and lighter
components, AVIO use Titanium aluminide in EBM machines and Stainless steel, cobalt,
nickel and aluminum alloys in DMLS process. AVIO also commercializes powder alloys
optimized for these processes (http://www.aviogroup.com).
6.3 Other AM Applications
Beyond the aerospace and aeronautical use, AM has been researched for complex
applications using precise new materials and processes. Size is becoming a very interesting
and important concern in AM. Today it is already possible to produce huge parts with four
meters wide. On the other hand, it is also possible to produce parts in the micro world with
details smaller than few microns, using processes like Two-Photon Polimerization (2PP)
(Ovsianikov and Chichkov, 2012). Nanoscribe GmbH, a spin-off of Karlsruhe Institute of
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
145
Technology (KIT), is producing what they claim to be the world's fastest AM equipment to
produce micro and nanostructures (sub-micrometer details) with Direct Laser Write
technology (http://www.nanoscribe.de). The microstructures can be potentially used in
healthcare (micro needles, stents, scaffolds for tissue engineering, etc.) 3D photonics,
biomimetics, microfluidics, mechanical microstructures and the polymer templates to create
metallic structures for electronics, among many others. Many universities, companies and
research institutes are investing in micro and nano AM technologies for advanced and diverse
applications.
Figure 7 shows in its right side the micro world of AM where small structures can be produced
like the micro airplane model produced in Karlsruhe Institute of Technology using its Direct
Laser Write technology and a functional monolithic micro turbines produced at Laser Zentrum
Hannover using a microstereolithography apparatus, both research centers in Germany. The
nano world is close. In the most right side of the picture can be seen a National Geographic
cover produced manipulating atoms at IBM Almadem research center. It is still a 2D (flat)
structure but opens up doors for a 3D structure. On the other hand, big structures like a 28
wingspan Unmanned Aerial Vehicle (UAV) was produced and tested by the American
Lockheed Martin, and whole buildings to be robotically produced as proposed by Professor
Behrokh Khoshnevis of Industrial & Systems Engineering in Southern University of California
using the process called Contour Crafting (http://www.contourcrafting.org/).
Figure 7: Range of sizes involved in Additive Manufacturing and its potential limits
The Institute of Photonics at the University of Eastern Finland and Dutch company LUXeXceL
are cooperating to develop what they call Printoptical Technology. It is claimed to be an AM
method for the production of optical quality components, such as lenses, without any need for
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
146
post-processing (http://www.uef.fi/en/home). At Printed Electronics 2013 – Germany, the
American company Optomec presented their process Aerosol Jet 3D to print a radio frequency
antenna and electrical power distribution for propellers and LED directly printed on the wings
of an unmanned air vehicle (UAV). The wings were fabricated using FDM process
(http://www.optomec.com/site/latest_news/news123). This is a potential for the consumers to
customize and demand online their electronic products in the future.
In the consumer market, it has appeared specialized companies offering customer-ordered
designs. You can choose hundreds of customizable and not customizable designs upload
your own or even sell it. The client can choose from plastic to ceramic or metal materials.
There are no equipments and tools for mass production and everything is produced in the
state-of-the-technology AM machines. That is the case of the Shapeways located in New York
(http://www.shapeways.com/), Thingverse (http://www.thingiverse.com/) and others.
Theoretically they can produce anything, from art to mechanical parts, jewelry, bags, glasses,
etc. It become clear a new way to produce any consumer products in a distributed high added
value way.
Figure 8 shows a Formula SAE competition car from the Mechanical Engineering Department
of the State University of Campinas (UNICAMP) that competed in 2008 with many tailored
parts made in CTI Renato Archer using the Selective Laser Sintering (SLS).
Figure 8: Formula SAE competition car using SLS tailored parts
Figure 9 shows a picture from the Brazilian National Institute of Space Research (INPE) that
is implementing the project Brazilian Decimetric Array (BDA) composed of a set of 26
antennas in a “T shape” configuration in the city of Cachoeira Paulista (Brazil) to monitor the
southern sky providing solar radio images for application to space weather forecasting. It is
innovative final use o AM with parts produced in polyamide using SLS process. This is the
first application of AM proposed by one of the 18 international partners. The parts are covering
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
147
the antenna and embedding all the electronics with forced ventilation from the underground to
keep temperature constant in all antennas.
Figure 9: (a) Array of antennas in a “T shape”; (b) design of antenna’s covers and housing for
electronics and (c) SLS parts mounted in one antenna
Another innovative use of AM in space was tested in 2007 when CTI Renato Archer sent a
chamber built to support a chemical reaction experiment at microgravity aboard the
International Space Station (ISS). The chamber was a complex experiment integrating
mechanical, electrical and fluidic systems with lightweight constraints defined by the space
program managers. Selective Laser Sintering (SLS) was the AM choice to build the chamber
in polyamide (Maia et al, 2008). The experiment is shown in Figure 10.
Figure 10: Left side: parts of the chamber to run experiment onboard of ISS. Right side: Brazilian
Astronaut Lieutenant Marcos Pontes during flight in ISS with the chemical reaction experiment in the
center of the photo
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
148
7 Additive Manufacturing and the Future of Logistics
Material development will make the difference for the use and expansion of AM into
production. In terms of logistics, machines will be transported once to their places, designs
can be transported by Internet but materials and its variety will be the most significant item in
terms of transportation, mainly if they will be produced in big industries, for the sake of
efficiency gains, instead of small ones locally distributed. Then, the global energy use and
greenhouse gas emissions will be involved in material displacement.
Therefore, a possible reduction in the logistics activities may be possible, since consumer
products can be locally produced in the site they are wanted reducing costs of transportation
and stocking. The products will flow directly from the producers to customers without retailers,
meaning fewer inventories. The task force will move from assembling lines to the new jobs in
small facilities. This new model will create opportunities for the development of new
management models and systems, new production models and controls and consumers
distribution even in more remote places.
According to United Network for Organ Sharing – UNOS (http://www.unos.org), a non-profit
organization in the USA, that manage a very complex net of information to optimize donation,
procurement and allocation of organs, a heart, for example, can be kept outside the body from
4-6 hours what makes a logistic, beyond biological and compatibility issues, very complex and
time dependent. The AM approach for organ bioprinting promises in the future to eliminate
waiting list and produce locally the necessary organs for transplantation.
Although AM is becoming an economically significant technology, it will be most improbable
that it can replace the mass production of parts or components, at least in the short to medium
term scenario. However, its flexibility and increasing offer of materials can be a great
opportunity for specific production or small series as well as mass customization. In the short-
term, the most appealing areas for the AM expansion are the aerospace industry, due to its
complexity with small series production, and healthcare, due its highly customized solutions
to fit a specific patient need. Assistive technologies for impaired people are experiencing a
fast growing but are still in development stage.
The implications of AM for logistics could be massive, both for the upstream supply chain and
for downstream customer order. AM will affect component suppliers, since the processes will
run in a single facility and retailers, because orders could come directly from consumers to
the near factory. It can potentially reduce warehousing, shipping and increase mass
customization (Manners-Bell and Lyon, 2012). American Department of Defense (DoD) is
seriously investing in AM to reduce costs of warehousing and transportation of spare parts to
the battlefield.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
149
8 Conclusions
Additive Manufacturing has its root in the process for quickly developing products with the
basis in the first processes of rapid prototyping in the eighties. It is still consistently used in
the product development process but it is expected that AM can revolutionize the way
production and business are done today. AM is unquestionable in a fast-pace progress and
developed countries are strongly investing in the new production paradigm referred as the
“Third Industrial Revolution“ (http://www.economist.com/ node/21553017). This new paradigm
of production is expected to grow in the next decades. SMEs can potentially be the major
beneficiary of the new technology. The main aspects that can benefit SMEs are the local
production of highly customized products, facilitate logistics, and increase flexibility with lower
costs. The logistic industry can be strongly affected by AM but competitive companies in
business will find opportunity for the development of new applications and systems for
managing production, distribution, customer relationship, partner relationship, product-life
cycle, and many others. This new way to produce and trade will open up opportunities for
software developments and the way customer can interacts with producers.
Movement toward free software and hardware associated to the expiring patents of the main
commercial processes created the “customer additive manufacturing” market with affordable
and popular solutions bringing 3D printers to homes in the last 5 years. Nowadays there is an
explosion of small companies offering very cheap DIY kits or mounted low-end machines for
makers or hobbyists. On the other hand, new horizons on the open-design direction with
people exchanging experiences and design solutions via Internet, like the today’s open-source
software and hardware, will dramatically affect industry and its intellectual property policy in
the way it is done today.
The main current industrial applications are the markets for customized, short-run items, such
as dental products, hearing aids, and jewelry, but some applications will highly impact lifestyle
like the healthcare and aerospace industry. In order to fulfill the challenging requirements of
economical and advanced applications AM has to grow in directions like: printing large
volumes and large objects economically; expand the range of printable materials; reduce the
costs of printable materials with higher durability and quality; monitoring of quicker processes
to guarantee reproducibility and surface finishing; and printing of multimaterials like those for
electronics. Legal responsibility will be a great concern demanding regulations and standards
for processes and materials testing.
9 References
ASTM (2012). http://www.astm.org/Committee/F42.htm
Delgado, J.S., C.A.R. Laureti, A.A. Camilo, J.V.L. Silva, L. Serenó, J. Ciurana (2012).
Mandible Reconstruction Using an Additive Manufacturing Technology In:
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
150
Proceedings of the 1st International Conference on Design and Processes for
Medical Devices PROMED. (Ceretti (Ed)), 275-278. Neos Edizione srl, Rivoli.
Lions, B. (2012). Additive Manufacturing in Aerospace. Examples and Research Outlook. In:
The Linking Engineering and Society Bridge. (Latanision R.M. (Ed)). 13-19,
National Academy of Engineering.
Lipson, H. and M. Kurman (2013). Fabricated: The New World of 3D Printing. Wiley.
Manners-Bell, J. and K. Lyon (2012). The implications of 3D printing for the global logistic
industry. Transport Intelligence. 1-5.
McKinsey (2012). McKinsey Global Institute Report Manufacturing the future: The next era of
global growth and innovation.
Maia et al (2008) Maia, I.A., M.F. Oliveira, P.Y. Noritomi, J.V.L. Silva. Application of Rapid
Manufacturing to build artifacts for using in microgravity environment. An
International Space Station case. Virtual and Rapid Manufacturing. (Bártolo (Ed)),
559-562, Taylor and Francis Group, London.
Noritomi, P.Y., T.A. Xavier, J.V.L. Silva (2011). A comparison between BioCAD and some
known methods for finite element model generation. Innovative Developments in
Virtual and Physical Prototyping. (Bártolo (Ed)), Taylor and Francis Group,
London, 685-690.
Ovsianikov, A. and B. Chichkov (2012). Three-Dimensional Microfabrication by Two-Photon
Polymerization Technique Computer-Aided Tissue Engineering, Methods in
Molecular Biology, 868, 311-325.
Pereira T.F., M.A.C. Silva, M.F. Oliveira, I.A. Maia, J.V.L. Silva, M.F. Costa, R.M.S. M. Thiré
(2012). Effect of process parameters on the properties of selective laser sintered
Poly(3-hydroxybutyrate) scaffolds for bone tissue engineering. Virtual and Physical
Prototyping, 7, 275-285.
Rezende, R.A., F.D.A.S. Pereira, V. Kasyanov, A. Ovsianikov, J. Torgensen, P. Gruber, J.
Stampfl, K. Brakke, J.A. Nogueira, V. Mironov, J.V.L. Silva (2012). Design,
physical prototyping and initial characterisation of Lockyballs. Virtual and Phys.
Prototyping,7, 287-301.
Silva, J.V.L., C.E. Saura, M. Bergerman, M.C. Yamanaka (1999). Rapid Prototyping -
Concept, Applications, and Potential Utilization in Brazil. In: 15th Intern.
Conference on CAD/CAM, Robotics and Factories of the Future.
Silva, J.V.L., T.A.P. Martins, P.Y. Noritomi (2012). Scaffold Informatics and Biomimetic
Design: Three-Dimensional Medical Reconstruction. Methods in Molecular Biology.
1edition, Humana Press, 91-109.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
151
Wohlers, T. (2012) Wohlers Report: Additive Manufacturing and 3D Printing State of
Industry, Wohlers Associates.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
152
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
153
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
154
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
155
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
156
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
157
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
158
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
159
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
160
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
161
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
162
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
163
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
164
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
165
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
166
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
167
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
168
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
169
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
170
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
171
172
MSc. Eng. Erwin Karl Franieck
Erwin Franieck was born in 1961 in São Paulo. Mechanical engineer
graduated at the Universidade Estadual de Campinas in 1985. In 1986
started his professional career as product development engineer for
the “Gasoline Systems-GS” Business unit at Robert Bosch Ltda,
where he was responsible for the implementation of laboratories for
functional analysis and electronic injection system component’s
calibrations. In 1991 he was transferred to the systemists unit,
becoming responsible for the mechatronic system integration,
managing the fuel feeding, ignition and torque control of the motor for
the vehicles and motors from 1992 to 1999. During this time, he
worked in several pioneer innovation projects, among them was the
Flex Fuel injection system. In 2001 he went on to participate at the
company’s headquarters, in Stuttgart, on the structuring of the
globalized business units, strengthening the connections between
these units among continents. In 2003, after returning to Brazil,
became responsible for the department of product development’s
engineering and expanded the fuel’s pump market share from 25% in
2003 to over 90% in 2008 by making use of the quick industrialization
of the flex fuel systems. In 2010 he was invited to manage an ISEC
(International Simultaneous Engineering Center) project of a new
technology responsible for coordinating both the project team as well
as the manufacturing team until the starting of production in 3 large
OEMs. Mr. Franieck later on returned to Brazil in 2013 where he
became responsible for the engineering directorate of the GS unit.
Once becoming director of the engineering unit, Erwin coordinated not
only the product development team in Brazil, but also the development
laboratories, accumulating during these 28 year of experience dozens
of patents. Mr. Franieck is currently focusing on the dissemination of
the Design for Six Sigma’s methodology, flexible management of
projects and integration of the value chain of new products which are
based on 3D files.
Robert Bosch Ltda.
The Business Unit Gasoline Systems (GS-
LA) is the greatest business unit of Robert
Bosch Brazil, located in Campinas,
completing 60 years of Brazil in 2014. With
revenue of R$900 Mi, GS-LA has an
engineering team of approximately 200
engineers working on product development
and research for 30 years in Brazil. As one of
the business units with greatest potential for
innovation in automotive segment, acting in
the development of products for admission
system, exhaust, supply and dosage of fuel
besides sensors and the electronic
processors units; GS regularly presents new
technological launches with the launches of
each OEM. The technological bases for
developments in Brazil present 3 basic
pillars: The Central Unit of “Corporate
Research - CR” in Germany, where basic
researches are made, the Centers of
Competencies (CoC) for certain
technologies, as fuels, polymeric materials,
metals, etc, situated in many locations (GS-
LA is CoC for alternative renewable fuels),
and the research institutes in Brazil.
173
Bosch Engineering System – A Robust Design
Process and 3D Model Applied in the
Complete Product Development Chain
Abstract
Bosch Engineering System (BES) is an integrated system for product development, based
on the deep knowledge of the product and on the cause-effect relationship between
product requirements and their functional characteristics, promoting the pursuit of
competencies in the centers of excellence in each technology and usage of development
tools and product simulation with full domain of them. Besides taking care of the involved
engineers’ competencies, the BES evokes the management to participate by managing
the team based on “content driven leadership”. We are going to approach an example of
Robust Design applied at RBLA. With one robust design available and also a clear idea of
the involved manufacturing processes we pursuit to automate the generation of production
data. Based on a 3D file elaborated in an adequate way including tolerances for the
manufacturing process in 3D, (i.e.: injected parts must foresee the split line and the draft
angle, etc.) through usage of PLM tools and simulations (i.e.: Mold-flow) we obtain one
geometry ready to initiate the tooling design. With this data, the responsible to develop the
tooling can automatically correct the contraction of the injected part obtaining the mold
geometry to be machined, transferred in an automatic way to the machines which will
produce the tooling. Once the tooling is ready, the try-out is started, injecting the first parts.
With tridimensional measurements through 3d scanning, it is possible to have a cloud of
the measured points and then comparing them with the product 3D file, automatically
evaluating if the samples dimensions are correct according to the tolerances. With the data
from the measurement, it is possible to use them to automate the correction of the tooling,
without been necessary to measure each dimension separately. This is a huge advantage
in time and recursions in the projects. Finally after the tooling correction, new
measurement and approval with less recurrence, the own 3D file can be used to document
into the quality control of the involved parts, registering in 3D e visualizing these files in
3D viewers already available. This is already a reality which brings competitiveness,
velocity and elimination of fails and recursions in the industrialization of the product.
Keywords
BES; Design for Six Sigma; DFSS; DRBFM; DOE; Simulation; PLM; 3D Scanner; 3D
dimension; Lean Development Process.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
174
1 Robust Design Process
“A development process for designing robust products” is a mandatory discipline for all
enterprises in the automotive branch or others related to the products in the high value
assemblies systems. The challenges involved to keep the development process of new
products as a success factor in our days, are increasing quickly. Some causes of that can be
attributed due reduced product life cycle, increased warranty period to 5 years, complex
market regulation for environments (gas emissions, fuel consumption, CO2 limits, self
diagnosis, etc.), integration of several mechatronics systems, expand bio fuels technology,
electrification, among others.
There are mainly two ways to innovate in a market: one is to make evolutionary innovations
according to market´s demands and the other is to come up with a disruptive innovation, that
is, with completely new features and ideas. Tesla, a new car maker brand, bases their
products on a disruptive innovation by producing electric & connected cars with better
aerodynamics, user friendly interfaces with Internet etc., while also making use of evolutionary
innovations. This combination has granted Tesla a significant market share on the U.S.
Looking at Tesla as an example, an important question companies need to make and be able
to answer is: “How do I keep myself competitive on the market?”.
There is no pretension to present in this few pages a solution for this challenge, but to give a
summarized view from a big player on this market, Robert Bosch GmbH.
The structuring of the product’s development process, foresees an integration of areas and
functions, which are considered primordial for the execution and completion of the project (as
shown in figure 1). With this figure we can set the structure in order to attend the local demands
in a flexible way, while making sure not to lose the focus on experience and global know how.
An integration of each individual’s characteristics and team work dimensions have to be clear
structured and aligned in very competent portions to consider adequately the demands of
each type of project.
The Figure 1 shows the main dimensions of system development, integrating matricial
management teams to the product development process.
This sub-structure on Figure 1, called BES (Bosch Engineering System) can be connected
with other sub-structures like: Bosch Production system (BPS), Bosch Sales & Marketing
System (BSS) & Bosch Human Resources System (BHS), implemented worldwide in an
integrated business System.
The combination of relevant knowledge (KM) in competence centers integrating a global
Network and an idea generation process (IM), will stimulate the generation of ideas that are
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
175
rated and incorporated in each location, according to the targets of each regional business
unit.
Figure 1: Product Engineering System
Systematic design development with passion for engineering and identification with Company
Vision: “Technology for Life” are considered as essential success factors. To reinforce the
effectiveness of this affirmation, a competence management, which warranties the knowledge
and resources involved in each system are under the domain of the participants of these
project teams.
Some basic rules for the development team are to be considered in the early phase of work,
in order to investigate the alternatives and solutions for the requirements:
1 Establish a frame work and structure for content-driven engineering and content-driven
leadership at management teams.
2 Coordinate all engineer methods/ applications needs, (QFD, DFSS, DRBFM, DRBTR,
Powerful 3D Interface for CAD/CAE/CAM, etc).
3 Stimulate engineer work through focus on technical models with a deep understanding
of cause-effect relationships before going to the final design.
4 Stimulate the team to bring innovative solutions mainly in evolutionary form, managing
ideas that are not applicable at this moment, but will be registered in an Ideation system
for future projects.
The expected effects after application of the aforementioned set of rules are well known, and
can be summarized in Figure 2, while bringing a deeper knowledge of the functions of “the
Design Elements” (DE). One of the most important consequences is the effective reduction of
recursions during release phase, increasing the first pass yield quota, avoiding problems after
the start of production (SOP).
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
176
Figure 2: Start the development effort in early phase
Experience shows us that, an empirical approach at the start of designing new products is one
of the most common failures in the landscape of field claims. “Show me how your project starts
and I can tell you how it will finish.” Gero Lomnitz.
The analysis of field incidents shows that the most important reasons of field crisis are related
to:
1 Poor evaluation on requirements for each application.
2 Inappropriate test methods tools.
3 Poor evaluation of changes in the product/process.
4 Poor risk evaluation on Management from business units.
5 No usage of simulation tools.
The main efforts in the early phase of projects require a deeply understanding of product and
system requirements, which unfolds each and every product’s functions showing its main
components / sub-systems and helps in the thorough search and finding of the Modules and
Design elements in order to ensure the best solution for the achievement of the requirements.
Continuing with the product’s development process, as can seen on Figure 3, based on the
Design Elements, a cooperation process between the “Engineering System” and “Production
System” is started, working to find the better relation among Function Design Process
Robustness. A strong project management leader is important in order to ensure the
smooth cooperation among the involved work teams and the structures, considering the time
and budget constraint.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
177
Figure 3: Management of Product Requirement
2 Robust Simulations
“The robust simulation of reality due to the virtual technology” is an essential concept in
the product development process today. This reality can be defined as the physical and
chemical phenomena that a product is subjected during operation or during the manufacturing
process. In the current scenario of automotive engineering, the robust simulation consists in
applying computational numerical methods (CAE: Computer-aided engineering) combined
with mathematical optimization methods.
Figure 4: Definition of a Simulation Model to represent the products functions
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
178
The utilization of a CAE method requires the creation of a parameterized mathematical model
able to represent the functions of the product satisfactorily, as shown in Figure 4. Generally,
a product has different functions in different physical domains. In this case, systems composed
of different models should be created in order to represent all of the products functions, as
illustrated in Figure 5.
Figure 5: System Simulation – A composition of different models
A system or model has normally a lot of parameters or variables that influence the
performance of the product. The simulation of all possible combinations of these variables is
unfeasible. Therefore, it is customary to use mathematical optimization methods, such as DOE
(Design of Experiences) or EA (Evolutionary Algorithms). The efficiency of these methods can
be defined as the ability to determine an optimal configuration of parameters with the lowest
number of simulations process.
The GAs (genetic algorithms) can be cited as an example of robust simulation [1]. This is a
method of EA that belongs to the field of artificial intelligence. In this case, the evolution of
generations of genetically different individuals is used to represent the search for a great
product, as shown in Figure 6.
Each product is represented as an individual, where a group of individuals is defined as a
generation. The new individuals of a new generation are created through a crossover between
individuals (combination of parameter values between different products configurations) and
/ or mutation of individuals (random modification of parameter values of a product). The
individual with higher fitness (product with the best performance) has a statistically greater
chance of passing on their genes through the generations. Thus, the optimal product is
determined to be the best individual of the last generation.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
179
Figure 6: Genetic Algorithms – An Example of a robust simulation method
Currently, the robust simulation is increasingly present in product development processes,
mainly due to increased computing performance. This type of simulation favors the
understanding of the functions of the product and helps in taking decision regarding the
geometrical design or choice of materials.
In manufacturing processes, such as injection molding, it is also possible to choose the best
parameters of injection that generate lower costs and lower manufacturing time. Figure 7
shows an example of a performance comparison between different injections molding process
configuration.
Figure 7: Moldflow 3D Warpage Analysis Results with different injection points configurations
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
180
Besides seeking the great product, the robust simulation aims to reduce the cost and time to
develop a new product. The development engineer can interpret this simulation process like
a “robust virtual test bench” where the repetition of a "virtual experiment" is quick and
cheap.
3 Robust Design Based on Design for Sixt Sigma (DFSS)
“A DFSS approach demands deep understanding of requirements at Design Element” Here
we will make a brief description - based on a textbook example - about the basic elements,
for which deep knowledge of the interrelation among them for each Design Element is of
crucial importance.
We have 3 basic Elements that are interrelated:
1 Load - What is acting on the product
Sum of the mechanically, chemically, thermally and
electromagnetically induced loads externally applied
on the product.
2 Stress – What the Design Element
(DE) senses
Local effect of the load within the
design element* with respect to the
considered damage / failure
mechanism.
E.g. mechanical stress, induced
voltage, temperature distribution, mass transfer during a chemical reaction.
3 Strength – What the DE can endure
Maximum stress endurable by a design
element for a specified amount of stress and
for the damage-/failure mechanism under
consideration.
Calculation of stress from
measured load
Conversion of stress into amount of stress
Amount of stress
Lifetime curve
Sterength for amount of stress and damage/failure mechanism
Lifetime under this amount of stress
Str
ess
[MP
a]
Lifetime (number of load cycles)
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
181
3.1 Damage Mechanism – How the DE Fails
A damage mechanism includes all processes in the design element considering the duration
and intensity of the stress combination leading to a gradual change of its properties.
All damage mechanisms are classified in the categories of Cracking, Aging, Corrosion,
Biological material damage and Wear. This describes the processes resulting in failure (=
irreversible loss of function).
The Stress-Strength Interference Model of Reliability. The Robustness in this case, is
represented as being the distance between the statistical distribution of the Stress-curve in
relation to the Strength-curve. Thus, a design element fails if, at the failure location (i.e.
locally):
A stress occurs which exceeds the product’s strength,
There is poor strength at that location.
Based on this understanding, for more complex real life situations, it is important to assess
the solutions by making use of tools of best practice, lessons learned, etc, while also looking
for alternatives and using decision tools in order to pick the best solution. After the alternative
is chosen, it is necessary to define the parameters of the Design Elements.
For the elaboration of the cause and effect model, the knowledge about the interaction
between the parameters regarding the Design elements is essential. In the model presented
on the diagram in Figure 8, we can see the triad: Simulation, Calculation and Experiment
provide results that enable the adjustment und comprehension about all phenomenons
involved in the Design Elements.
The development activities will work to find the better solution to increase the strength of the
product/system in order to support the new requirement.
Calculation / Theory Study
Simulation
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
182
Experiment
Calculation / Theory Study
Figure 8: Diagram Cause-effect Relationship
4 Real Case: Improve Strength to Support New Requirement
Let us consider a typical application in the Brazilian market: we have a specification for the
fuel, nevertheless, we often find cases that do not meet this specification. In this case, a
reassessment of the real facts brings a revision of the requisites for the Fuel Pump product as
well as the emergence of new technologies, as for example a smart generator.
Product / Components study and functions mapped: Change of requirements for wearing on
electrical commutation for a Fuel Pump in ethanol fuel. (New requirements: Intelligent
alternator with variable voltage and bio fuel with higher conductivity). Electrical Arcing on
commutation area = f (residual energy; dielectric resistance; voltage) [2, 3].
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
183
1 Residual energy = f(commutation angle)
2 Dielectric Resistance = f(fuel conductivity (µS/m))
3 Energy = f (voltage)
Simulation: The Calculation/Theory output pointed the voltage and commutation angle
as the most relevant influence on spark energy under the new requirement (increase
stress).
Residual energy = f (commutation angle, Voltage)
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
184
Experiment (Design of Experiment): The definition of the experiment that reproduces the
failure mode is a fundamental step for the assessment of the actions and verification of
their respective effectiveness. For this, as seen in Figure 9, the awareness of the failure
mode and the influence of the new requisites are essential for defining all the details of
the experiment.
Figure 9: DoE: Design of Experiment: Test definition to check the robustness of The Design Element
Targets for the DoE:
1 Implementation of a failure reproduction method
2 Control of stress during the tests.
3 Finding the relationship of the design elements and strength curve.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
185
Figure 10: Example of Results for influeny of 3 Parameters (Fuel Conductivity, Voltage, commutation
angle) on Life time during the DoE
Conclusion: The deep understanding of the phenomena, checked with appropriated
simulation tool and confirmed during DoE tests, gives the development team a basis for a
correct decision of proper design element parameter (commutation design), minimizing the
risks of recursions during release phases or after SOP.
5 CAD-CAE-CAM Tooling Supporting Design 3D
After defining the Proper Design Element parameters and limits necessary to achieve the
requirements, the complete design element starts to be fixed. This is made by thinking on the
complete product development cycle since the concept phase, passing through discussion
with production process and assurance of appropriated quality level. An integration of several
internal and external areas of product and process development (that in most cases are not
under the same business unit) is required.
Throughout the different phases of a Project, the transferred documents and data (drawings
and product specifications) between the countless departments (purchase, process planning,
manufacture, quality control and documentation) is most usually made via 2D documents.
Nevertheless, a re-edition of these drawings and specifications is needed in each transferring
phase of the documents in order to attend the necessary needs of each department. The issue
arises due to the fact that only some primordial characteristics concerning the manufacturing
process like plastic Injection Molding, cold forged metals, metal molding, etc. are considered
in the first 2D design. As a result of that, due to deeper discussions concerning the
manufacturing process, many new details demanding attention arise on subsequent phases
of the project that were previously not accounted for. In order to solve this detail issues, it is
usually necessary to review the initial project and sometimes even, in some cases, to modify
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
186
the project itself. This generates extra work, delays and resources wastage in an already
advanced stage of the project.
As a result of that, this leaves the engineer on one side, with the time constraint to release the
drawing to start the tooling preparation, and on the other side, the tooling maker, that will have
a lot of problems to achieve the requirements. Others involved are the quality control
department and the production department that must find a way to check if the parts are in
accordance to the drawings and how the process control must be managed to warranty the
product requirements.
A lot of recursions are expected during the development cycle, basically because the product
drawing is not focused on process, but on the functional elements.
CAD/CAE/CAM software have powerful solutions to check the 3D drawing according to the
process. If the product engineer not only has to be responsible for the functional requirements,
but also for the production requirements of a given product, he will have a lot of software
modules in hands that can support him on how to correct the design in an early phase of the
project according to the process demands. The computer aided 3D design can be used to
define not only the complete geometry of produced parts, but also the dimensioning including
dimensional tolerances, geometrical tolerances, drawing notes, specifications, etc. At the NX
CAD/CAE/CAM software, used at Bosch there is a PMI module (Product Manufacturing
Information) that follows several norms for 3D Digital product definition, which allows to include
in the 3D Design all PM information linked to the related dimension or surface.
Considering the 3D data with PMI as a full documented file, that can be exchanged in an open
3D format (.JT extension) and used in all kind of CAD software, it is permitted to exchange
the 3D Design and PMI among all involved areas, substituting with higher efficiency the 2D
drawings and specifications.
Each company has to establish some rules for using this kind of powerful resource, and keep
some internal standards, to speed up the exchange of information among the departments
and product life cycle.
A management of this UX (User experience) software is enabled through Teamcenter
Engineering (TCEng.) application. Among many function, it is used to create a workflow in the
3D drawing release process, which can include a lot of checks about the maturity of the
drawing. A powerful checkmate named HD3D has a customization for plastic parts, named
DFMA, that will require the trend line for the tooling and check automatically the minimal
radius, angles, wall thickness, etc.; controlling the release of the 3D-drawings for the
production system.
Another SW tool to guide the 3D design work for plastic parts, named Mold Part Validation
(MPV) helps the engineer to apply commands appropriated for plastic parts, simplifying
changes, accelerating the development time, with a proper overview about the process
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
187
necessities. With the design of the features in 3D, it is possible to define combined surfaces
as a complex format, that is, as one group of dimensions with the similar or same tolerance
and surface requirement. These can substitute a lot of non critical dimensions per the 3D
complex format, without a lot of dimensions.
The new equipment for measurement via White light or 3D laser measurement, delivers a 3D
cloud of points integrated in a surface that can be compared with theoretical 3D data, and
reduces the necessity measurement interpretation and individual dimensional measurement.
An example of application of 3D drawing with PMI and 3D Measurement in Figure 11 shows
the potential in time improvement for projects and products to reach market maturity.
Figure 11: 3D Scanner Blue light with precision of 0,030 mm
The usage of the 3D GD&T and the 3D scanner, in comparison with Standard 3D Optical
measurement results in a significant reduction of measurement time for complex parts, as
presented in the Figure 9.
By using PMI, Scanner and CMM, we are able to reduce the quantity of dimension by ~68%
(from 248 to 78) and the entire missing details can be taken from the model, see the note:
The accordingly usage of 3D tools in all phases of development for intermediate complexity
plastic parts for example, will significantly improve the project’s Time to Market. A first increase
in time, in order to do the design freeze including the demands of processes in an early phase,
will be more than compensated by reducing the recursions, and improving the timing for each
round of tooling try-out.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
188
Figure 12: Reduction of measurement time using 3D Programming and #D Scanner
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
189
Conclusion: Innovation is a key success of factor on current product development process on
automotive industry. Pressure on time and costs combined with increasing level of complexity
of products and its interaction led to constant adoption of so called state-of-art methods and
tools to assure robust design and support organization all over development chain through
manufacturing. Engineers count even more with established IT-tools to obtain a virtual 3D
model prototype which can foresee and predict potential product improvements and based on
that perform design changes accordingly. In addition the information flow is streamlined once
the same 3D model is used throughout organization from concept till inspection. This
systematic approach results in effective reduction of recursions during release phase,
minimizing costs and increasing product quality.
6 References
[1] Michalewicz, Z.
Genetic algorithms + data STRUCTURES = evolution programs, 3rd ed.
Springer, New York, 1996.
[2] Sawa, K.; Wei, C. C.; Ueno, T.
Erosion by Arc Discharge at Carbon Contacts in Various Automotive Fuels, Holm
Conf. on Electrical Contacts, IEEE 59th, pp.1-6, 2013.
[3] Sawa, K.
Arc Discharge and Contact Reliability in Switching and Commutating Contacts,
Electrical Contacts, Proc. 51st IEEE Holm Conf., pp.10-21, 2005
190
MSc. Eng Waldir Gomes Gonçalves
Waldir Gomes Gonçalves graduated in Naval Engineering, and has a
Master degree in Aeronautical engineering with specialization in
composite structures. Working in the product development
engineering for more than 25 years, has participated in several
Embraer product developments, and headed many engineering
areas: Structures and Materials, CAE/CAD and PLM, Product Support
engineering, the Commercial Aviation engineering, the Embraer
Defense and Security Engineering and currently the KC-390 Product
Development Engineering.
Embraer S.A.
Embraer is one of the world’s leading aircraft
manufacturers, a position achieved through
the commitment to full customer satisfaction.
Throughout its 45-year history, Embraer has
been involved in all aspects of aviation. In
Addition to design, development,
manufacturing, sales and technical support
for commercial, agricultural and executive
aviation, Embraer also offers integrated
solutions for defense and security and
services.
191
Processo de Desenvolvimento de Produtos
Aeronáuticos
Resumo
O Processo de Desenvolvimento de Produtos (PDP) Aeronáutico se destaca como
vantagem competitiva. Para desenvolver um sistema sócio técnico de alta performance
são necessários vencer diversos desafios associados à aplicação eficaz dos princípios do
Lean Development. Por meio de uma gestão de processos, gestão integrada de
programas, desenvolvimento enxuto do produto e da gestão do processo produtivo a
empresa desenvolveu um PDP Aeronáutico com práticas integradas. A aplicação destas
práticas é demonstrada no estudo de caso do Desenvolvimento do KC-390. Este é o
desafio que a EMBRAER S.A. vem trilhando nos últimos sete anos.
Palavras chave
Desenvolvimento Enxuto do Produto; Sistema Sócio Técnico; Lean Development.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
192
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
193
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
194
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
195
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
196
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
197
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
198
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
199
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
200
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
201
202
Mauro Conceição
Mauro da Conceição é Tecnólogo em Processos de Produção e
Gestor Global de Kow-How Management da Magneti Marelli Cofap,
com MBA em Conhecimento, Tecnologia e Inovação pela FIA –
Fundação Instituto de Administração e Especialização em
Gerenciamento de Projetos.Funcionário da Marelli há 24 anos,
atualmente é responsável pela administração e suporte aos
Processos de Gerenciamento de Ciclo de Vida do Produto no Brasil,
Europa, Estados Unidos e Joint-Ventures, incluindo administração e
suporte a todos os softwares de Engenharia, incluindo as ferramentas
de CAD e implantação de melhores práticas em
modelamento.Também foi coordenador do Projeto SABER na
Diretoria de P&D, que identificou e mapeou os processos críticos para
o desenvolvimento de Produto, gerando um diagnóstico do nível de
maturidade em relação às práticas de Gestão do Conhecimento.
Magneti Marelli Cofap
Fundada em 1951, a antiga Cofap Cia
Fabricadora de Peças, foi comprada em
1997 pelo Grupo Magneti Marelli.Hoje, a
Magneti Marelli Cofap é uma das divisões da
Magneti Marelli, multinacional italiana da
Grupo Fiat, que além da Linha de negócios
de amortecedores, possui as divisões de
Iluminação, Powertrain, Eletrônica,
Exaustão, Plásticos e AfterMarket, somando
no total aproximadamente 38000
colaboradores ao redor do mundo.No Brasil,
é líder no fornecimento de amortecedores
automotivos para as grandes montadores,
com mais de 70% de Market share.
Atualmente possui centros técnicos de
aplicação no Brasil, Estados e Itália, além
das unidades produtivas no Brasil (Lavras e
Mauá), Polônia (Bielsko), Estados Unidos
(Pulaski) e Joint-Ventures na Índia e China..
203
PLM na Magneti Marelli Cofap:
Compartilhando um Caminho, Dificuldades e
Desafios na Implantação Globalizada
Resumo
Em 2004 foi iniciada a implantação do Projeto PLM (Product Lifecycle Management) na
Magneti Marelli Cofap, unidade de Amortecedores do Grupo Magneti Marelli. O que se
pretende abordar neste caso de implantação é além de mostrar entregáveis e detalhes
técnicos da funcionalidade de um software, também trazer experiência sobre o ambiente
de implantação, o impacto das mudanças em uma organização que deixou de ser
nacional a partir da aquisição para a Magneti Marelli e as lições do aprendizado e boas
práticas que podem ser adotadas em projetos cuja configuração é de alto risco, pelo
escopo amplo, pela longa duração e diferentes culturas envolvidas.
Palavras chave
PLM; Implantação; Integração CAD-PLM; Workflow
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
204
1 A Tecnologia em Evolução
Amortecedores são pouco conhecidos, não possuem design atraente, ficam ocultos embaixo
do automóvel, porém são itens de segurança, com comportamento fluidodinâmico complexo,
cuja aplicação pode ser em veículos pesados, automóveis de passeio até o segmento
Premium para Maseratti, Ferrari com sistemas de amortecimento variável.
É necessário entender esta dimensão, porque a complexidade e variabilidade de portfólio
acabam por se tornam também variáveis que iram demandar um controle cada vez mais
confiável em relação gestão de mudança e busca de informação.
2 Histórico
Tudo começou como Cofap, quando na década de 50 Abraham
Kasinsky fundou a Cia. Fabricadora de Peças, que se tornou a
maior fabricantes de autopeças do Brasil, mas durante o processo
de abertura de mercado iniciada na era Collor e os problemas de
sucessão foi adquirida pela Magneti Marelli em 1997,
multinacional italiana que buscava integrar ao grupo a expertise
na fabricação de amortecedores.
Antes da aquisição pela Magneti Marelli, a Cofap já possuía um
Centro Técnico de Aplicação em Detroit e uma fábrica recém-
inaugurada na cidade de Kingsport, Tenessee, porém nesta época as demandas da
globalização exigiriam mais.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
205
A meta é estar onde as montadoras se fazem presentes, e para isto, um plano de expansão
foi iniciado, com a implantação de fábricas na Polônia, Índia e China (estas duas via Joint-
Venture), além de mais um Centro Técnico de Aplicação em Torino, próximo da matriz.
3 Por que o PLM?
Em 1997 a MM Cofap já tinha um sistema de
Gerenciamento Eletrônico de Documentos (GED)
em início de implantação.
Em 2002 já não havia no então “arquivo técnico”
mais mapotecas, e os desenhos já eram
acessados via portal web.
3.1 Por que a Demanda então do PLM?
Porém é interessante também abordarmos um cenário que não é estranho quando se discute
implantação de sistemas informatizados para gestão de documentos, de projetos e
processos.
Muitas vezes há um volume razoável de investimentos, em hardware, software, consultorias
para atender as necessidades decorrentes do grande volume de informações que o ambiente
de negócios requer.
Estes recursos são disponibilizados para por fim a especificações duplicadas, diminuir a
quantidade de retrabalhos entre outros, porém é difícil a mensuração dos resultados após um
longo período de implantação de sistemas de gestão, e a culpa acaba sendo do software.
A MM Cofap também não escapou deste paradigma, e mais adiante, falaremos sobre o que
seria uma boa prática quando desejamos implantar software de gestão de Ciclo de Vida de
Produto.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
206
A Cofap se tornou MM Cofap, deixou de ser nacional e agora como multinacional, com novos
Centros Técnicos, novas Plantas novas línguas é necessário transferir o conhecimento, uma
vez que a linha de negócios de amortecedores é a única do grupo com seu lead center de
desenvolvimento baseado no Brasil.
Neste momento os projetos tornam-se globais, e padronizar os processos é um requisito para
redução do tempo de desenvolvimento.
O Projeto PLM chega não só na MM Cofap,
mas em todo o Grupo FIAT, holding da qual a
Magneti Marelli faz parte para suportar estas
atividades.
4 Sobre a Implantação
Sair de GED para PLM é um desafio.
O implantador da solução e o antigo parceiro do sistema legado precisaram desenvolver uma
ferramenta para migrar os dados de um banco de dados para outro.
Foi elaborado um faseamento do Projeto, que apesar de ter sido apresentado pela equipe
italiana no final de 2004, somente foi iniciado o processo de importação no início de 2006,
quando o processo de migração foi definido.
O ano de 2006 não foi um ano tranquilo, enquanto um sistema era implantado, tínhamos um
sistema legado cujo servidor e banco de dados já não suportavam o volume de informações
e com frequentes paradas por falta de espaço em disco.
Seguem abaixo as principais fases definidas para o trabalho de 2006 até 2014:
2006 – Fase 1
Definição de parâmetros e criação programa de importação
Importação de dados e monitoramento
Implantação Consulta Worldwide
1ª versão workflow de documentos
2009 – Fase 2
Implantação Classification
2ª versão workflow de engenharia
Implantação workflow de solicitações de projetos
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
207
Migração Catia V5
Implantação Integração Catia V5 - Teamcenter
2013 – Fase 3
Implantação novo sistema de codificação
Implantação Structure Manager
2014 – Fase 4
Interface Teamcenter - ERP
4.1 A importância da Fase 2
Após a implantação da primeira fase, tínhamos finalmente encerrado uma plataforma de
software e iniciado outra, porém, após um ano de utilização, o estudo mais detalhado do
escopo mostrava que apesar de estarmos com um software para PLM, na realidade
estávamos com o sistema de Gerenciamento Eletrônico de Documentos mais caro do mundo,
pois a funcionalidade mais utilizada continuava sendo o controle de revisões e a consulta
eletrônica de documentação.
Foi contratada uma consultoria de PLM indicado pelo fornecedor de software, e revisamos as
funcionalidades mais necessárias, através de entrevistas com todas as áreas de P&D e
também com as áreas que faziam parte do processo de desenvolvimento do produto.
5 Estrutura Organizacional: Know-How Management
Para suportar e administrar o Projeto PLM, foi necessário revisar a estrutura organizacional
dentro da empresa.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
208
Esta questão também faz parte de discussões em muitas organizações que começaram a
utilizar sistemas de Engenharia, como CAD, CAM, FEA, etc.
Quem administra? Quem implanta? É a área de TI? É um engenheiro, ou técnico com mais
aptidão para Tecnologia de Informação.
A criação do departamento de P&D, subordinado à Diretoria foi definido, utilizando-se como
base a mesma solução adotada pela Unidade de Suspensão da Marelli.
Uma equipe com analistas de sistema, alguns com experiência prévia em Engenharia, e
responsável por administrar os sistemas de gestão de engenharia foi formada, enquanto que
TI, fica responsável por suportar e validar as soluções de infraestrutura de rede, hardware e
adequação as regras de segurança da informação.
Obviamente, grande parte das atividades de Know-How Management é voltada ao suporte e
administração do sistema PLM.
5.1 Entregáveis do Projeto
Atrelado às entregas do Projeto, uma mudança de cultura de trabalho foi, e vem sendo
demandada.
Ao listar a seguir algumas das funcionalidades do software que são utilizadas, não pode ser
omitido que algumas mudanças não vieram para de imediato, economizar tempo, ou
simplificar a vida do usuário final.
Pode-se comparar isto à migração de um software CAD 2D para um CAD 3D, com o conceito
de assemblies, ou então as implantações de ERP, como SAP, que de início trazem um grande
impacto nos procedimentos de trabalho, mas que no longo prazo trazem o retorno.
Devemos interpretar os sistemas de gestão também como práticas de gestão do
conhecimento, enquanto que ao utilizarmos workflows, formulários eletrônicos, recurso de
pesquisa por atributos está estruturando um grande volume de conhecimento que estava fora
de um processo padronizado de trabalho.
Conscientizar os usuários do sistema sobre este período de adaptação é fundamental para
garantir aderência ao Projeto, no nível local e global.
5.2 Integrar CAD ao PLM
Sem dúvida, ainda um dos grandes desafios, ainda não temos 100% do processo de
modelamento integrado, ou seja, utilizando a interface do software PLM como a porta de
entrada para o trabalho no CAD, porém o upload de todos os modelos ocorre com o integrador
da plataforma, o que garante que o reuso destes modelos por outros centros técnicos
ocorrerá sem conflitos por perda de links ou erros de modelamento.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
209
5.3 Classificação por Atributos
Utilizar a classificação por atributos foi um dos recursos do sistema priorizado, devido ao
grande potencial de reduzir efetivamente o lead-time de desenvolvimento do produto e dos
processos de cotação.
O amortecedor tem diversos componentes
que são utilizados em mais de um produto,
principalmente os conjuntos internos de
válvulas, e o registro das similaridades
geométricas e características de matéria-
prima, tem como grande foco o incremento do
reuso de peças e evitar a criação de novos
part numbers para componentes que
eventualmente já existam na base de dados.
5.4 Workflows e Auditoria de Processo
Automatizar um processo do negócio não é atualmente, algo inédito em grandes corporações.
Os processos de gestão de mudança, de acionamento de engenharia e diversos outros
pequenos acionamentos, cuja evidência dependia do e-mail, ou de um registro assinado,
foram substituídos por um workflow dentro do Teamcenter Engineering.
Porém, temos insistido, especialmente com os gestores de P&D, que um grande benefício
não percebido ao automatizar um processo, é o potencial de termos uma fotografia da “saúde”
e do desempenho do negócio.
Quanto tempo demora um fluxo de aprovação de desenho? Quantas rejeições têm em
determinada etapa?
Considerar o workflow sob esta ótica torna-se uma grande justificativa para sua implantação.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
210
6 Engineering Bill of Material
A lista de peças de produto ou Engineering Bill of Material, hoje é criada no software de PLM.
Para fazer isto foi necessário um esforço de padronização, negociações com os
implantadores de SAP, que é o sistema ERP padrão do Grupo FIAT, e ainda demanda
melhorias, no que tange a uma melhor entrega para preparação da M-BOM (Manufacturing
Bill of Material).
A grande conquista na utilização da função Structure Manager foi a implantação de um
template global de produto para entregar as plantas produtivas.
6.1 Distribuição da Informação
Não existe mais em P&D um arquivo técnico, os fluxos de informação notificam via e-mail os
antigos receptores de informação em papel, que acessam o sistema, seja via web browser
ou via Portal para consultar o desenho, norma, procedimento ou relatório de ensaio, e se
necessário, imprimem para utilização.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
211
6.2 Gestão Documental
A característica principal do PLM na MM Cofap é que o uso do sistema não está restrito
apenas aos desenhos da Engenharia de Produto.
Principalmente no Brasil, pela herança do trabalho em células multifuncionais, facilitaram um
intercâmbio com departamentos de qualidade, manufatura e produção.
Isto se reflete quando são gerenciados no banco de dados, além dos documentos de P&D,
também os desenhos de ferramentais, dispositivos da área de Manufatura, os relatórios dos
processos de APQP da área de Qualidade, além das normas de produção.
6.3 Conceitos que se Complementam e as Lições que Aprendemos
Em 2009 P&D conduziu um importante projeto de Gestão do Conhecimento, chamado de
Projeto SABER.
Este projeto mapeou os conhecimentos críticos e práticas de Gestão do Conhecimento
existentes e necessárias para toda a Diretoria de Pesquisa e Desenvolvimento de Produto.
Paralelamente ao iniciarmos o trabalho com a consultoria de PLM para implantarmos mais
funcionalidades existentes no sistema, identificamos que estas funcionalidades eram
respostas a muitas necessidades de compartilhamento, registro e proteção da base de
conhecimento existente em Amortecedores.
Foi a partir disto que Know-How Management utiliza toda oportunidade disponível, para, ao
treinar, identificar necessidades em PLM, trazer os conceitos de Gestão do Conhecimento
agregados ao sistema.
Fomentar uma cultura de Gestão do Conhecimento facilita o processo de implantação do
PLM, uma vez que dão argumentos junto ao público alvo, para entenderem que muitos frutos
serão obtidos também no legado futuro deixado aqueles que irão suceder os seniores que
estão na empresa, e facilitar no processo de enculturação para uma empresa global.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
212
As lições aprendidas não terminaram, Projetos de PLM são projetos de alto risco, sob a ótica
de PMI: são projetos de longa duração, de alto valor de investimento e de escopo muito
amplo.
Precisam ser segmentados.
Muitas vezes, entregas pequenas, seguidas da mensuração do sucesso, municiam os
implementadores para justificarem mais recursos, considerando-se que ainda muitas
organizações consideram as áreas de P&D como custo indireto.
Um ex-diretor de P&D, italiano, cunhou uma frase a respeito disso: “Melhor um ovo hoje, do
que uma galinha nunca”.
Não é uma frase acadêmica, mas traduz muito do que devemos levar em consideração para
obtermos sucesso na utilização de sistemas informatizados no desenvolvimento de produto.
O apoio de um patrocinador forte, como na grande maioria dos projetos, é essencial. PLM
muitas vezes traz implicitamente a mudança de cultura.
Daí uma importante lição aprendida, é que devemos sempre levar em conta qual o grau de
maturidade da minha organização ao propor a utilização de determinada prática ou
funcionalidade de um sistema.
Uma funcionalidade cujo sucesso depende como pré-requisito de uma base completa de CAD
em 3D, se a engenharia ainda utiliza prancheta, suporta a decisão de postergar esta ação e
iniciar outra que foque a implantação de uma plataforma CAD.
Ao planejar os investimentos, devemos trazer junto à área de TI e levar em consideração os
custos agregados para uso da ferramenta.
Sistemas PLM, mesmo baseados na web, não rodam em computadores configurados para
acesso a aplicativos Office.
Se pensarmos em acesso global, banda de rede, servidores de replicação de dados, são
custos que não devem ser desconsiderados, para não extrapolarmos o budget de
investimento, e de despesa.
Finalizando, apesar de parecer óbvio, nem sempre isto acontece: o seu implantador, ou sua
área, ou mesmo a empresa, utilizam práticas e metodologias de gestão de Projeto, como do
PMI?
Esta é uma boa prática, o cronograma, o escopo bem definido, a gestão de tempo eficaz e a
documentação do projeto devem ser levados em consideração como fatores críticos de
sucesso para a implantação do PLM.
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
213
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
214
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
215
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
216
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
217
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
218
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
219
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
220
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
221
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
222
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
223
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
224
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
225
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
226
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
227
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
228
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
229
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
230
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
231
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
232
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
233
19º Seminário Internacional de Alta Tecnologia Inovações Tecnológicas no Desenvolvimento do Produto
234