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An innovative approach to managing uncertainty in a highly volatile supply chain
Mathieu ClerkxPhilips SemiconductorsSenior vice presidentSupply chain management and ICT
Ton de KokProfessor of Operations Planning and ControlTechnische Universiteit EindhovenThe Netherlands
Acknowledgements are due to Fred Jansen and Jan van Doremalen (CQM), Erik van Wachem and Winfried Peeters (Philips Semiconductors)
Semiconductors 2Semiconductors
An innovative approach to managing uncertainty in a highly volatile supply chain
• The players• SCM improvement
framework• Process solution• Decision support
solution• Benefits and impact
SuperiorSupply Chain
Decision Making
Semiconductors 3Semiconductors
Philips ElectronicsWorld’s 10th largest electronics corporation
• Active in consumer electronics, medical systems, lighting, semiconductors, domesticappliances and personal care
• Multinational workforce of 164,000 employees
• Sales 2003: € 29 billion
• Sales and service in 150 countries
• R&D expenditure 2003: € 2,6 billion
• Over 100,000 patent rights
Semiconductors 4Semiconductors
DiffusionAssembly/
testing
OPU
FLEX
PCB
Finishedproduct Retail
WWW
Players Supply Chain Network
• Volatile, highly uncertain demand• Rapid evolution process and product technologies
20 weeks
Philips Semiconductors• Manufacturer of integrated
circuits (ICs)
• Focus on solutions for connected consumer applications
• A top 10 supplier; 2003 revenues€ 4,5 billion
Contract manufacturers• Manufacturing PCB’s and
flex unit outsourced
• Electronic Manufacturing Services (EMS)
• Original Design Manufacturers (ODM)
Philips Optical Storage• A significant player in optical
storage market
• A leading player in automotive and DVD recordable applications
• 2003 revenues€ 1,4 billion
Semiconductors 5Semiconductors
An innovative approach to managing uncertainty in a highly volatile supply chain
• The players• SCM improvement
framework• Process solution• Decision support
solution• Benefits and impact
SuperiorSupply Chain
Decision Making
Semiconductors 6Semiconductors
demand
Componentsupplier
How manywafers to set-up?
How manyICs to
produce?
How manyICs to ship,
and to where?
Contractmanufacturers
How much toproduce
with whichsub-contractor?
OEM
How much toassemble and
where?
Multiple, interrelated decisions Made by many independent organizations across the chain
Fragmented decision making
demandBullwhip
Semiconductors 7Semiconductors
4. Speed & focus ofdecision making
“We have todecide extremely
fast ”
The collaborative planning project Addressed four key requirements
3. Recognition of uncertainty
“We live ina volatile &
uncertain world”
“We have to share information and
synchronise decisions”
2. Information transparencyamongst all parties
“Only throughcollaborating with partners will our
supply chain win”
1. Strategic partnerships & collaboration
SuperiorSupply Chain
Decision Making
Semiconductors 8Semiconductors
An innovative approach to managing uncertainty in a highly volatile supply chain
• The players• SCM improvement
framework• Process solution
– Strategic partnerships & collaboration
– Information transparency amongst all parties
• Decision support solution
• Benefits and impact
SuperiorSupply Chain
Decision Making
Semiconductors 9Semiconductors
CollaborativeplanningStrategic
partnership
The nature of the relationship is essential
VMIPriorityService
Customer captive
Marketexchange
Suppliercaptive
Supplier’s specific investments
Customer’s specific investments
PublicE-market
LiabilityExtra stock
Semiconductors 10Semiconductors
Coming from...
WEEK [n]WEEK [n+6]
demand
Semiconductors 11Semiconductors
demand
...to sharing & synchronization between all partners
WEEK [n]WEEK [n+2]
From sequential event propagation towards synchronized supply chain coordinationInformation leadtime reduction : - 4 weeks
Semiconductors 12Semiconductors
demand
...to sharing & synchronization between all partners
Real-life data from eleven ERP systems
…. But data collection is restricted to key components !
Challenges
• Create information transparency • Synchronize many independent IT systems• Ensure data consistency• Well disciplined and synchronized work flow• Guarantee data security and authorization
Semiconductors 13Semiconductors
Overall timeline
July 2001 Apr 2002 Now!Aug 2000
Proof of Concept phase (15 finished products)
Implementation phase
( > 50 finishedproducts)
Maintenance mode
Implemen tation
new release
Software enhan
cements
Implementation new accounts
Pilot
Commercialsoftware
Roll-out Implemen
tationmanual
Ton de Kok, Professor of Operations Planning and ControlTechnische Universiteit EindhovenThe Netherlands
Semiconductors 15Semiconductors
An innovative approach to managing uncertainty in a highly volatile supply chain
• The players• SCM improvement
framework• Process solution• Decision support
solution– Recognition of uncertainty– Speed & focus of decision making
• Benefits and impact
Semiconductors 16Semiconductors
Framing the problem
Stochastic dynamic demand•Sales plans over multiple periods•Short product life cycles
Multi-itemMulti-echelon
Mixed BOM structure•Item in multiple parents•Item has multiple children
Hard material constraints•Should be taken into account
explicity
Soft capacity constraints•Assume infinite capacity
Stochastic dynamic supplyof materials
•Stochastic lead times•Stochastic yield
Semiconductors 17Semiconductors
Two modelling routes towards APS
Deterministicmodel
Model solution
SCPsolution
Stochasticmodel
Policy
SCPsolution
Real worldproblem
Semiconductors 18Semiconductors
How much inventory given customer service levelsMulti-item, multi-echelon, stochastic stationary demand
StochasticN-echelon
system
Optimal SBS-policy
StationarySBS-policy
10-20% less inventory
investment
LinearProgramming
problem
Safety stockki
Simplexalgorithm
Too much inventory held
upstream
Periodic review,BOM, added value,
service level
Semiconductors 19Semiconductors
Determining control parametersMulti-item, multi-echelon, stochastic stationary demand
Periodic review,BOM, added value,
service level
StochasticN-echelon
system
Optimal SBS-policy
StationarySBS-policy
Safety stocks follow from
stochastic model
LinearProgramming
problem
Safety stockki
Simplexalgorithm
Hard to set appropriate safety
stocks
Semiconductors 20Semiconductors
Sensitivity to cost parameters
Verysensitiveto cost
parameters
LinearProgramming
problem
Safety stockki
Simplexalgorithm
Robust solutions
StochasticN-echelon
system
Optimal SBS-policy
StationarySBS-policy
Conclusions based on experimental study in De Kok (2001) and De Kok and Fransoo (2003)
Multi-item, multi-echelon, stochastic stationary demand
Periodic review,BOM, added value,
service level
Semiconductors 21Semiconductors
SpeedMulti-item, multi-echelon, stochastic dynamic demand
StochasticN-echelon
system
Optimal SBS-policy
DynamicSBS-policy
SECONDS
LinearProgramming
problem
Safety stockki
Simplexalgorithm
HOURS Periodic review,BOM, added value,
service level
Semiconductors 22Semiconductors
Remaining modeling issues
• Planned lead times• Weekly update of WIP and stocks• Safety lead time
Stochastic lead times
• Weekly update of WIP and stocks• Safety lead timeStochastic yield
• SBS policy structure• Weekly update salesplans• Safety lead time
Stochastic dynamic demand
Semiconductors 23Semiconductors
Unique features and transportability
• SBS policies ensure:– consistency between safety stocks and
operational plans– root cause analysis and corrective actions
through backward pegging – fast re-calculation for interactive problem
solving• Generic multi-item, multi-echelon network
model
Semiconductors 24Semiconductors
An innovative approach to managing uncertainty in a highly volatile supply chain
• The players• SCM improvement
framework• Process solution• Decision support
solution• Benefits and impact
SuperiorSupply Chain
Decision Making
Semiconductors 25Semiconductors
Proof of benefits during ramp-down
0
20
40
60
80
100
120
140
160
2001
42
2001
48
2002
02
2002
07
2002
12
2002
17
2002
22
2002
27
2002
34
2002
39
2002
44
2002
49
2003
04
Week number
Qua
ntity
in 1
000
piec
es
Timely ramp-down to minimise
obsolescence
cumulative demand
cumulative supply
Demand / Supply gap before CP was fully
operational
Echelon stock IC
Dynamic target base stock IC
Semiconductors 26Semiconductors
0
500
1000
1500
2000
2500
3000
3500
4000
2002
24
2002
29
2002
36
2002
41
2002
46
2002
51
2003
06
2003
11
2003
16
2003
24
2003
29
2003
34
2003
39
Week num ber
Qu
an
tity
in 1
00
0 p
iece
s
cum ulativedem andcum ulative supply
Very fast response time
of 2 weeks
Proof of benefits during ramp-up
cumulative demand
cumulative supply
No over-reactions to temporary demand changes
Without compromising
customer service!
Semiconductors 27Semiconductors
€€’s Benefits Collaborative Planning
• Proven benefits• Less obsolescence, lower
inventories and increased sales account for majority recurring benefits
• Fast implementation with new software and well developed implementation manual
• Payback period < 6 months• High demand CP in current
allocation times
5
14
28
3
8
16
0
5
10
15
20
25
30
35
now end 2004 end 2005
mil
lio
n E
uro
benefits inventories
>50
>80
>120
Semiconductors 28Semiconductors
Conclusion
Collaborative Planning really works!
demand