the journey to the - clnv.s3. · pdf file•conclusion agenda. ge overview. ... variances...
TRANSCRIPT
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
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
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
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.
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