Microsoft Word supply chain-latest-2c doc



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Chang

 
 
Figure 2: Diagram of an example supply chain simulation model. 
 
 
Table 2: Example data requirements for supply chain model 
Area Data 
required 
Manufacturing Process and time information 
Manufacturing process data (process time, queue 
time, setup time, number of machine in each 
process, alternate route) 
Calendar data (shift information, holiday 
information, preventive maintenance information) 
Machine data (Number of machine, mean time to 
failure, mean time to repair, alternate resources data, 
preventive maintenance time) 
Bill of material structure
Inventory control policies information 
Safety stock level, reorder point
Inventory level of finished products, raw material 
and intermediate parts 
Any stock location in shop floor 
Procurement and logistics information
Supplier lead-time 
Supply lot size 
Supplier capacity 
Procurement horizon 
Procurement time 
Demand information 
Due date 
Priority 
Start and end data 
Demand pattern 
Policies/Strategies information 
Order control policies, dispatch policies 


Y. CHANG et al: SUPPLY CHAIN MODELLING 
I. J. of SIMULATION Vol. 2 No. 1 ISSN 1473-804x online, 1473-8031 print 
29
Some of the questions the users might have are 
as follows: 
· 
Which supplier policy is achieving best 
delivery performance under given 
demand pattern? 
· 
Which supplier policy is most robust 
under demand fluctuation? 
· 
Which is the most cost saving inventory 
policy under given demand pattern ? 
· 
How would profit can be impacted by 
adding xx % more capacity? 
· 
What is the trade-off between delivery 
performance and inventory cost when 
building more inventory?
· 
What is the impact of information 
accuracy on the manufacturing 
performance (e.g. cycle time, order fill 
rate) 
Many researchers are investigating the 
possibility of creating a simulation-based real 
time scheduling system that will be able to 
monitor the system status and make decisions in 
real-time. To have the capability, it is desirable 
to have (1) capability to interface with legacy 
databases to obtain information (2) hardware and 
software processing capability to run simulation 
within very short time- at least, pseudo in real 
time (3) capability to interface with the control 
system to assign tasks and receive feedback on 
system status and performance.

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