| Configuration of Complex Production Lines for Profit Maximization via Simulation Optimization |
M. Fatih Yegul's Research Page
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This research is motivated by a real-world complex manufacturing system problem. Magna International Inc. (Company), a Canada
based global auto parts manufacturer, has planned to build a new manufacturing plant. The new plant will be built to produce a
specific electric-car component.
The problem Company has brought forward can be formulated as finding the best configuration for a complex flow type manufacturing
system with fixed demand to optimize a given performance measure. The configuration involves a number of different parameters for
certain stations such as number of machines, machine speeds (cycle time), min buffer allocations and number of workers.
It is very important for the Company to reach a throughput level at least equal to annual estimated demand. Besides there are other
performance measures involved such as investment cost for acquiring new equipment, cost related to work-in-process and finished
product (WIP) inventory, labor cost, and cost of lost sales.
Thus the case translates into a profit maximization problem with the optimal configuration of bounded number of machines, labour
requirements, buffer sizes, and machine speeds in an asynchronous, non-homogeneous, series-parallel manufacturing system.
based global auto parts manufacturer, has planned to build a new manufacturing plant. The new plant will be built to produce a
specific electric-car component.
The problem Company has brought forward can be formulated as finding the best configuration for a complex flow type manufacturing
system with fixed demand to optimize a given performance measure. The configuration involves a number of different parameters for
certain stations such as number of machines, machine speeds (cycle time), min buffer allocations and number of workers.
It is very important for the Company to reach a throughput level at least equal to annual estimated demand. Besides there are other
performance measures involved such as investment cost for acquiring new equipment, cost related to work-in-process and finished
product (WIP) inventory, labor cost, and cost of lost sales.
Thus the case translates into a profit maximization problem with the optimal configuration of bounded number of machines, labour
requirements, buffer sizes, and machine speeds in an asynchronous, non-homogeneous, series-parallel manufacturing system.
My special thanks goes to
Simul8 Corporation who
generously provided me with
professional version of Simul8
under free PhD license scheme.
Simul8 Corporation who
generously provided me with
professional version of Simul8
under free PhD license scheme.
Supervised by Prof. Mustafa Yavuz
Department of Mechanical & Mechatronics Engineering
| Overview of the Simulation Optimization Approach |
| Trial |
| Trial |