faculteit technologie management 1 linear & nonlinear wip clearing in supply chain operations...
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/faculteit technologie management
Linear & Nonlinear WIP Clearing in Supply Chain Operations Planning
Barış Selçuk, Jan C. Fransoo and A. (Ton) G. De Kok
5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
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/faculteit technologie management
5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
PU1I0 PU2I1 PU3I2 I3 Customers
SCOP
L1 L2 L3
OPU1 OPU2 OPU3
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/faculteit technologie management
5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
Clearing functions in the literature
• Graves (1986), "Fixed lead time"• Karmarkar (1989), "Saturating"
– Zäpfel and Missbauer (1993), Missbauer (2002)
– Asmundsson et.al. (2005)
• Billington et.al. (1983), Hackman and Leachman (1989), "Combined"
μ
α
Fixed Capacity
Fixed Lead Time
Combined
Saturating
WIP
Thr
ough
put
Clearing Function: The mathematical representation of expected throughput over a time period as a function of the work-in-process (WIP) over that period.
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Three different WIP clearing assumptions
5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
tan ,tan
,
WIP if WIPThroughput
otherwise
Traditional Linear (TL):
212
D
WIPThroughput
dWIP
Long Term Nonlinear (LTN):
1
0 ! !
k kWIP
k k WIP
Throughput k e WIP ek k
Short Term Nonlinear (STN):
SCOP
OPU
PU, Exp(μ)R F Customers2, Dd
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Supply Chain Operations Planning (SCOP)
,W t t
5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
SCOP
OPU
PUR F Customers
Demand forecasts , , ,I t t B t t
1 1
1 1 0 0
. , , , ,T T L T L T
f w r qs s s s
Min h I t t s h W t t s c R t t s c Q t t s
,R t t
, 1 , 1 , , , ,I t t s B t t s I t t s B t t s R t t s L d t t s
, 1 , , ,W t t s W t t s R t t s Q t t s
1
0
, , ,t s L
k
W t t s R t t s Q t t s k
, , ,nQ t t s f W t t s R t t s
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/faculteit technologie management
5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
Operations Planning Unit (OPU)
,W t t
SCOP
OPU
PUR F Customers
Demand forecasts , , ,I t t B t t
,R t t
( , ), , , ,w t t i t t b t t( , )r t t
1
1 1 0
, , , , ,f w r qs s s
Min h i t t s M b t t s h w t t s c r t t s c q t t s
, 1 , 1 , , , ,i t t s b t t s i t t s b t t s q t t s R t s L t s L
, 1 , , ,w t t s w t t s r t t s q t t s
, , ,nq t t s f w t t s r t t s
Advanced:
, , ,r t t R t tSimple:
, ,w t t W t t
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/faculteit technologie management
5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
Experimental design
STNLTN
TL
L=4
Factors Treatments
Clearing Function: TL, LTN, STN
Operational Planning: Simple, Advanced
Utilization: 80%, 90%
Demand Uncertainty: 10%, 50%, 100%
# of Treatments: 36
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/faculteit technologie management
5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
Results: Costs
Utilization: 80%, Operational planning: Simple
Utilization: 90%, Operational planning: Simple
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/faculteit technologie management
5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
Results: Costs
Utilization: 80%, Operational planning: Advanced
Utilization: 90%, Operational planning: Advanced
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/faculteit technologie management
5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
Results: Costs
Conclusions:
• STN is the best choice for a lower total cost. STN provides lowest WIP while indifferent in echelon inventory for the majority of the cases.
• For modelling the short term behaviour in the shop STN clearing function is favorable to TL and LTN clearing functions. SCOP model has a better anticipation of the operational dynamics of the manufacturer in the near future.
• Advanced operational planning is better off only for STN, but not for TL and LTN.
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/faculteit technologie management
5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
Results: Delivery performance
Utilization: 80%, Operational planning: Simple
Utilization: 90%, Operational planning: Simple
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/faculteit technologie management
5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
Results: Delivery performance
Utilization: 80%, Operational planning: Advanced
Utilization: 90%, Operational planning: Advanced
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/faculteit technologie management
5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
Results: Delivery performance
Conclusions:
• For simple operational planning function, STN provides the best delivery performance while TL provides the worst.
• For advanced operational planning function, TL provides the best delivery performance while STN provides the worst.
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5th Int'l Conference on "Analysis of Manufacturing Systems – Production Management", Zakynthos Island, Greece
Future Research
• Development of models and providing analysis for multi-stage manufacturing.
• Development of a lead time adaptive approach for supply chain operations planning.– Single-stage manufacturer and distributor.
– Multi-stage manufacturing.
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