Hamilton Institute

Team Building andInnovation in Research

Peter E. Wellstead The Hamilton Institute, Ireland

Hamilton Institute

Hamilton Institute

Overview

• How Research and Innovation Works History Management Approaches Motivation

• Systematic Procedures for Research Innovation The Context Team Building Project and Product Models

• Cases Studies Automotive Control Systems (1970-90) Pole Assignment Adaptive Control (1976-84) Two Dimensional Systems Research (1980-2004) Systems Biology (2004 - ?)

• Conclusions

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History - Innovation:Agriculture – Henry of Arden, the three field system

Textiles – Flemish Silk Masters and Dominican Weavers

1st Industrial Revolution – Mechanisation of Manufacture

2nd Industrial Revolution – Mechanisation of Information Processing

History – ‘Masters of Innovation’:Thomas Edison – ‘The Patent Factory’

Sydney Camm – Aircraft design

The Lunar Societies – Innovation in the Industrial Revolution

How Research and Innovation Works

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Objectives1. At the highest level we are research managers and need a

view, based upon historical observation, that can be applied to predict futures. (Level 1: Strategic)

2. At the operational level, we want constructive approached designed to enable research and innovation to work (Level 2: operational).

3. At the recruitment level, we want ways of selecting people that can flourish in a research and innovation environment (Level 3: recruitment).

How Research and Innovation Works

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Objectives1. The questions are:

- How do we provide an information framework equivalent to a ‘master of innovation’?

- And how do we provide a management framework which allows team members to incrementally contribute to innovation?

2. Level 1: Strategic: Use lessons of history and methods for predicting innovation cycles applied to your own interest area.

3. Level 2: Operational: Use the lessons from ‘masters of innovation’ and adapt and adopt for your research programme

4. Level 3: Human Dimension: The single most crucial factor in research success, look at how the best people do it and copy.

How Research and Innovation Works

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Leve1 1: Strategic- We review the modelling innovation as a historical

cycle.

- Pick up the key themes.

- Transpose them to our context.

- And attempt to predict areas or applications that are ripe for innovation.

How Research and Innovation Works

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Strategic: Theories of Research and InnovationKondratieff – Wave theory of economics

Schlumpeter – Business cycles

Utterbeck – the dynamics of innovation

Kuhn – structure of scientific revolution

Christenson – disruptive innovation

Forester –modelling of economic systems

Kostoff – technology road maps

Modelling of Innovation

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Operational: Organising for Innovation- We review how key innovators operate

- Note requirement for teams in innovation projects

- Review some existing methods for innovation enabling

- Discuss the role of engineering modelling methods with innovation enabling tools

How Research and Innovation Works

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Operational: Team BuildingA key first step is team building such that the people satisfy

a number of criteria or metrics:

1. Technology metrics

- Skills, background, technical aspirations

2. Organisational metrics

- Understanding of organisational structures and functions.

3. Project metrics

- Understanding of project objectives and context

4. Team metrics

- Role within a team, role of her/his skills

Modelling for Innovation

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Operational: Team Functioning

The ProblemSoftware engineers don’t talk to electrical engineers

Electrical engineers don’t talk to Mechanical engineers,

Mathematicians don’t talk to anybody.

A SolutionGeneralised system modelling methods that cover all

technologies within a project form a common language and computer simulation is the ‘spoken’ form of that language.

We use mind-maps to draw word bond graphs from which a full engineering bond graph is constructed and implemented in a simulation tool (20Sim, Simulink) etc.

Modelling for Innovation

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Leve1 3: Human Dimension- Note requirement for teams in innovation projects

- Mention some methods that can help you

How Research and Innovation Works

Hamilton Institute

Human Dimension: Team SelectionPersonnel experts have numerous ways of personality

profiling and team personal, that cover the non – technical metrics.

Methods that we have used with success are:

- Mindmapping (Buzan)

- Team Style Inventory (Belbin)

- Functional relation diagrams (Saurono)

- Cause and Effect diagrams (Gillespie and Froggatt)

Most engineers/scientists are sceptical – but these methods have got value so at least read about them.

Modelling for Innovation

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Case Studies

Automotive Control Systems Research (1970-95)

1. VLSI in the 1960’s indicated that digital electronics was getting ready for mass deployment in products

2. The management and control of car engines and chassis was mechanical and unreliable. Commercial pressures for improved reliability and quality

3. I saw an opportunity for digital control systems research for automotive applications.

4. Programme – in 1975 form research link with component supplier – 20 year joint programme of innovation – including adaptive engine management (now standard on all cars) – electric controlled power steering (now 50M$ company run by former research students).

5. Stopped in 1995 – all significant and easy innovations done, now part of control research mainstream

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Case Studies

Pole Assignment Adaptive Control (1976-84)1. Analogue adaptive control discredited in1950’s

2. Digital online estimation emerging (1960’s)

3. 1973, Peterka in Prague combined digital estimation with online adjustment of digital controllers – modern adaptive control was born.

4. Flood of activity in optimal adaptive control in Europe – mainly Sweden, UK.

5. I saw a need for non-optimal adaptive control and developed the pole assignment based self-tuner and other derivatives.

6. Stopped in 1984 with main easy results obtained, and moved on as the topic went mainstream.

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Case Studies

Two Dimensional Systems Research (1980-2004)

Systems Biology (2004 - ?)

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Team Building andInnovation in Research

Conclusions