The Journey to the

GE Brilliant FactoryJimmie Beecham – GE Healthcare

Chuck Stickney - Cisco

BRKIOT-1101

• GE Overview

• GE Healthcare Brilliant Factory Approach

• Panel Discussion

• Question and Answer

• Conclusion

Agenda

GE Overview

General Electric

• Founded by Thomas Edison in 1878

• $150bn Revenue

• Build, Cure, Move, Power

• Divesting from Entertainment, Consumer, and Financials

One of the World’s Most Iconic Brands

Jeff ImmeltGeneral Electric Chairman and CEO

GE Software

• Leveraging the software power of GE

• Innovation center in the Silicon Valley

• GE Predix

• Cisco IoX – the Predix enabled router

Data Analytics

Cisco

IOS

Predix Apps

GE Machine Services

IoX

Embedded

ComputeAccessible

Interfaces

Embedded

Storage

The Industrial Internet

• Internet of Things

• GE and Cisco Strategic Alliance

• Founding Members of the Industrial Internet Consortium

• Along with AT&T, IBM, and Intel

Manufacturing meets Big Data

Jimmie Beacham

11

Understanding the digital threads

Customer

FactoryDistribution

Sales/Com

Sourcing

Materials

Logistic

Engineering

QARA

Factory

Finance

Holds

FMI

Variable costs

Base costs

Net Variable

Variances

Productivity

Inventory

SCOT

Forecasting

Demand flow down

Pricing

Capability

Delivery

Orders

Backlog

Shipping methods

Packaging

Costs

Service

Install

Repairs

Maintenance

Design inputs/outputs

Product Compliance

BOMS

Scheduling

Labor

Quality

Equipment

Delivery

Cost

Quality

Inventory

12

Demystifying Brilliant Factory

Brilliant Supply Chain

Brilliant Factory

Brilliant Lines

Brilliant Machines

Digital threads… data lakes Full supply chain optimizationAutomated decision making

Eyes into the suppliers Ears to the customers Full facility optimization

Adaptive feedback loopsPredictive quality Labor and material visibility

Predictive maintenance SPC where criticalOEE Visibility

Brilliant Products PLM linkage to Supply Chain Predictive serviceUse and performance is visibleV

irtu

al

Mfg

Se

nso

r E

na

ble

dF

ac

tory

O

pt

SC

O

pt

Must be conscience of the hierarchy of data…Data Information Knowledge Decisions

13

GEHC MFG Landscape… >80 Plants 3 ApproachesPla

nt

Types

Chara

cter

ist

ics

1

System Assy

2

Component MFG

3

Chemical Process

• Single piece flow

• Low/High Volume

• General Assembly

• High test content

• Supplier dependent

• Single & batch flow

• Medium Volume

• Hi-Tech machining

• Test & Inspection

• More vertically Integrated

• Batch flow

• High Volume

• Hi-Tech Process

• In line control

• Highly reg. suppliers

• Test data trending

• Eyes into supplier

• Inventory sensitive

• Long lead times

• SPC/OEE critical

• Quality sensitive

• High overhead costs

• Long design cycle

• OEE critical

• Auto process correction

• Visual inspection

• Heavy QC requirements

Dynam

ics

Building the Brilliant foundation

14

Brilliant Factory

People

Lea

n &

6σ

Mfg

Te

ch

Fle

xib

ility

• Process experts• Controls expertise• Data driven culture

Business Need

Mobilizing the Brilliant Factory

15

Brilliant Factory Model

Visualization model

1. Leverage Pilots to show proof of concept.

2. Create standards that are saleable and

flexible.

3. Show people how Brilliant can change the

game.

4. Help cut the red tape… especially in heavily

regulated industries.

Lessons learned

16

1. A Brilliant Factory can not be an IT only initiative… Need MFG defining requirements early in the process.

2. Process expertise… Need to know what data you need to capture and monitor.

3. Use business cases to get started but don’t drown in analysis paralysis.

Lessons learned (cont….)

17

4. The network needs to be flexible and more robust then any of your equipment.

5. Drive as much standardization as you can…don’t relearn from the same mistakes.

6. Lean & 6σ lines can become brilliant lines.

Interactive - Interview

Participant Questions

Thank you

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