Smart Factory 실현을위한접근전략Providing an open Smart Manufacturing Platform to support real-time, high value applications. Bringing innovation to the manufacturing process

Smart Factory 실현을 위한 접근전략

이창호 박사IBM GBS

Understanding the 4th Industrial Revolution

IBM Capabilities & Offerings

Strategy for Smart Factory Implementation

Selected Client Cases





Several initiatives around the global are aiming to bring innovation

and revolutionize manufacturing, creating what is been called the 4th industrial revolution

How Germany is dealing with the fusion of the online world and the world of industrial production. "Those who are the leaders in the digital domain will take the lead in industrial production."

Leading the USA industrial sector transformation into a networked, information-driven environment Providing an open Smart Manufacturing Platform to support real-time, high value applications.

Bringing innovation to the manufacturing process in Korea, expanding the use of smart factories Developing core technologies related to the Internet of Things, 3-D printing and big data

Innovation in Manufacturing 3.0

Transform China from a manufacturing giant into a world manufacturing power. Priorities include improving manufacturing innovation, integrating IT and OT and promoting

service-oriented manufacturing.

France industrial plan to enable the industrial sector for the next industrial revolution. Assist companies in their transformations towards a world where digital is closing the gap between

industry and services.

UK strategic initiative that aims to revitalize the manufacturing industry. Consists of technology and innovation centers that work as gateways to access the best

manufacturing talent and facilities in the country.

New business processes / new business models

Innovative products, applications and services we cannot dream of today

Servicization – from products to service transformation

Major increase in competitiveness for the companies getting it right

IT will be consumed and adopted as a service

Security the enterprise even more complex

Calls for new Privacy laws

Implications

Increase competitiveness of the country

Digitally enabled industrial economy & mass

customization

Vertical and horizontal integration across the

value chain

Convergence and alignment between IT and OT

Cyber-physical systems

Information security, ownership of the data

Mixed human/robotic workforce &

cognitive capabilities

Shorter product lifecycle

Circular economy

Common Themes

Industry

4.0

Autonomous Systems

Internet of Services

Analytics & Cognitive

Flexible Manufacturing

Internet of Things

Ability to connect and manage

devices

Near real-time data collection

Insights of what is happening

New business models

Internet of Things

Flexible machines

3D printing

Machine to machine

Mixed human / robotics

New standards and protocols

Vertical and horizontal integration

Flexible Manufacturing

New delivery channels and business

models

Integrations across value chains

The API economy

Internet of Services

Embedded in equipments, products and

services

Predict what may happen

Prescribe actions for best outcomes

Self learning

Communicate in natural language

Analytics& Cognitive

Smart and networked products

Ability to communicate thru the Internet

Self diagnose / self awareness

Autonomous Systems

Internet of Things is a key enabler, but Industry 4.0 requires other capabilities

Sources: Acatech: Recommendations for implementing the strategic initiative Industrie 4.0,

April 2013;Gartner: Industrie 4.0- The Ten Things the CIO Needs to Know; Deutsche Bank

Research: “Upgrading of Germany’s industrial capabilities on the horizon “, April 2014





Device & Network Ecosystem

Programming Platform

Analytics

Security

Connectivity

Engineering Platform

Integration

Variation

Compliance

Applications & Solutions

Industry Transformation

Service & Warranty

Industry Insights New revenue opportunities Increase competitiveness

across the value chain Higher profitability

New Business ModelYour Business

Connect to the IoT device

anywhere to IBM cloud,

ingest, organize and store

information securely.

Make use of information to

start getting real time insights

Handle the complexity of

IoT-enabled devices

Keep devices active and

operational in the field

Extensive library:

Asset Health, Energy Analytics,

Project Analytics, Maintenance

Scheduling, Production

Optimization, Inventory

Optimization, Cognitive

Analytics, etc.

Since 2008, when IBM launched the Smarter Planet Strategy, we have been working with thousands of clients around the globe and have created a very comprehensive set of capabilities to drive the industry transformation

Transformation of the Manufacturing Industry

Example: CPS Asset Health (1 of 3)

CPS Asset Health

Real-time Data Exchange

Equipment (sensor) time-series

Vibrations, temperature, pressure, "speed"

variables (rotational, translational, …), etc.

Positional and/or motion data

Event data – e.g., when an accelerator is

triggered; when gear is shifted

"Alerts" (thresholds breached, etc.)


Maintenance Data / Historical Data

Basic asset info (locations, model, age, etc.)

Maintenance-related outcomes Repair history

Preventive & Unscheduled

Fluid analysis

Inspection reports

INSIGHTS

Sub-assembly / component lifetime wear indicators

Leading failure indicators

Engine alerts

Overload / over speed alerts

Example: CPS Worker Safety (2 of 3)

CPS Asset Health


Environment-sensing

Temperature

Noise

Oxygen deficiency

Carbon monoxide

INSIGHTS



Engine alerts


Permit to work

Use of safety equipment

Unsafe condition of equipment

Fatigue

Alertness

Fall / Injury

CPS Worker

Accelerometer

Speed-X

Speed-Y

Speed-Z

Bio-sensing

Heart rate

Body temperature

GPS Sensor

Location

Worker equipped with wearables

Real-timeData Exchange

Example: CPS Production Optimization (3 of 3)

CPS Asset Health

INSIGHTS



Engine alerts


Permit to work

Use of safety equipment

Unsafe condition of equipment

Fatigue

Alertness

Fall / Injury

Production real-time status

Equipment utilization

Best time to perform maintenance

Worker productivity CPS Worker

Worker equipped with wearables

CPS Production Optimization

Orders

Customer

Order quantity, price, due date

Production routing

Production data

Production status

Inventory (WIP, FG..)

Equipment status

Workstation status…




Cloud-based, as a ServiceDynamic / Self Configured Processes

Closed LoopCognitive Value Chain / Human Collaboration

CPS-1

CPS-2

CPS-n

Watson

Cloud-based, as a ServicePre-Defined / Automated Processes

Closed LoopHuman Supervision

CPS-1

CPS-2

CPS-n

On- Premise, OwnedProvide insights

Open LoopHuman Required for Action

▲ Specialized Model 1 ▲ Specialized Model 2

IBM Vision & Strategy to realize full potential of

IoT and Industry 4.0






Think about the reason why we need to implement smart factory Future change drivers always comes from customers

Start from your Customers & Markets

There is no one-size-fits all smart factory model to all the plants Every plants need to build their own use cases to cope with the market dynamics

Focus on Use Case & Operational Model

Think big, start small and scale fast!

People

Process

Technology

Design the big picture to harmonize the use cases Build small success cases aligned with big picture.

Think

BIG

Start

Small

Scale

FAST

Smart Manufacturing, IBM’s term for integrating operations, improves visibility and speed and accuracy of decision making

Visibility – know what’s happening

– Digitize everything; measure everything

Smarter Manufacturing speed and accuracy in

decision making

– Improved decision support; Improved collaboration

– Improve prediction and optimization

Smart Manufacturing offers a

customizable strategy and

breakthrough technology based

on an integrated information

framework that allows

connecting aging and newer

facilities, allowing for visibility

across the entire fleet of

chemicals plants

• Health, Safety, Security, Environment (HSSE)• Reliability of equipment and process• Product Quality• Increasing velocity of demands on the plant• Cost control• Energy Optimization / CO2 Minimization• Inherent process complexity – non-linear changes• Margin Maximization – Economic optimization• Address aging workforce, scarce skill sets and increasing reliance on contractors• Address increasing supply chain speed and complexity

Market & Industry Drivers

Requires…

Fundamental misalignments of Plant Operation

Planning and Scheduling (P&S) Decision Time Scales: Days and Weeks

Organization: centralized

Paradigm: Change to follow market

Misalignment 1: between Planning &

Scheduling and Operations Operations and the Real World Decision time scales: real time

Plant dynamics: real time

Organization: Distributed

Paradigm: Stable operations

Operate for Stable performance Stay far away from constraints; reduce alarms

Reduce operational changes

Reduced set of operational parameters

Plant Autonomy Paradigm:Plant meets profit obligations in its own way

High performing plants can reach their full potential

Processes optimized for local conditions and culture

Knowledge transferred via assignment rotation

Global optimization not possible

Operate for Economic Optimum Push the units to their constraints

Flexible operations to meet changing

economics

Increased set of operational parameters

Corporate Standardization Paradigm: Global standardization / optimization

Standard processes and infrastructure reduces

costs and facilitates cross-plant comparisons

Global optimization possible

Misalignment 2: between Operations

Stability and Economic Optimization

Misalignment 3: between autonomous

plants and need for standardization

Decisions not integrated

Sub-optimal plans

Plans not followed

Driving to economic

optimum difficult

Margin maximization and

safety misaligned

Natural “tension” between

two modes

Large gaps between plants

Knowledge transfer

inhibited

Market Dynamics

Market Dynamics

Results

Addressing the fundamental misalignments of Plant Operation

Misalignment 2: between Operations

Stability and Economic Optimization

Misalignment 3: between autonomous

plants and need for standardization

Misalignment 1: between Planning &

Scheduling and Operations

Addressing Misalignment 1Increase accuracy

Increased planning and scheduling model accuracies

Coordinate operations

Controls to unit optimums

Understands unit effects on other units

Faster decisions / more flexible operations

Increased planning frequency

Increased operations flexibility

Addressing Misalignment 2Improve predictions

What-if analyses, on demand

Improved modeling capability

Improve knowledge of the optimum

Local and global optimization

Effect of one unit on others

Improve operations ability to push constraints

Improved process control and RTO

Detailed and consistent “safe production” parameters

Addressing Misalignment 3 Collaborative Environments to establish Best Practices

Standard Performance Measurement systems

Advanced Knowledge Management Systems

Advanced visibility into operations across the enterprise

Addressing the fundamental misalignments of Plant Operation

Plant Operation misalignments Principles of Smart Factory for Operation Model Development

Addressing Misalignment 1

Increase accuracy

Increased planning and scheduling model accuracies

Coordinate operations

Controls to unit optimums

Understands unit effects on other units

Faster decisions / more flexible operations

Increased planning frequency

Increased operations flexibility


Improve predictions

What-if analyses, on demand

Improved modeling capability

Improve knowledge of the optimum

Local and global optimization

Effect of one unit on others

Improve operations ability to push constraints

Improved process control and RTO

Detailed and consistent safety parameters


Collaborative Environments to establish Best Practices

Standard Performance Measurement systems

Advanced Knowledge Management Systems

Advanced visibility into operations across the enterprise

Prediction Make Equipment Smarter via smart sensors and software

Enhance Process Modeling to enable prediction

Visibility Turn data into contextual information leading to quicker, smarter actions

Information available at all levels Enhance visibility throughout

Collaboration Bring the jobs to the experts

Leverage remote expertise

Increase speed of response & reduced cost through virtual presence

Optimization Enhance Process control Leverage existing models

Build additional capabilities to enable unit and refinery-wide optimization on demand





Case: Cognitive Engineering & Construction at a Major EPC Firm

CPS Predictive Analytics

Results

Increase bid win rate

Better project estimation

Immediate identification of events that can cause

impacts in project execution

Improved ability to deliver projects on-budget and

on-time

Reduced risks

Eliminate margin erosion

CPS Prescriptive Analytics

Watson

CPS Cognitive Analytics

Suppliers

Purchase Order Status

Production Status

Completion Date

Shipping Status

ETA, Deliver Confirmation

Project Systems &

Historical Data

Materials Management

Project Schedules

Contracts, Documentation

On-going Projects

Project History

Fabrication Yards

Materials Inventory

Fabrication Status

Completion Date

Shipment Status

Shipping Companies

Design Loads

Load Vessels

Track Shipment

ETA

Delivery Confirmation

Construction

Equipment

Equipment status

(empty, loading,

dumping, hauling etc.)

Fuel and tire consumption

Construction Site

Employee safety monitoring

Equipment availability

Material availability

Personnel availability

Resources utilization

Task execution status

Weather Forecast

Weather conditions (e.g., wind,

precipitation, temperatures,

humidity

Historical Data Real-time Data Exchange Real-time Data Exchange Real-time Data Exchange Real-time Data Exchange

Realtime Data Exchange

Case: Cognitive Advisor for Cement Plant Operations

CPS Cognitive Analytics

Results

Expert level support to plants to maximize

performance

Decrease energy cost

Increase production capacity

Eliminate forced shutdown

Decrease maintenance cost

Reduce exposure to knowledge leak

Reduce exposure to critical emergence situation

CPS Real Time Insights

Real Time Local Special

Conditions

Plant maintenance history

Location (climate, ambient

temperature, locally sourced

materials, etc.

CPSMachine Learning

Watson

Ready-Mix Plants Logistics ClientsQuarries Terminals

Cement Plants

Historical Data

Realtime Data Exchange

Real Time Operating Variables

Input materials (granularity, type, humidity, fuel mix, etc)

Operating variables (temperatures, milling times)

Energy consumed

Quality of output material

200 variables


Historical Data

Plant Information Documents

Plant processes

Operating manuals

Understanding of machine behavior

(milling time for each type of machine)

Test results (grindability, mineralogy)

Documents

Historical Data

Expert

Expert Knowledge

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The Fourth Industrial Revolution Industry 4.0cc

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