| Summary: | 碩士 === 國立交通大學 === 工業工程與管理學系 === 99 === The manufacturing of ingot－wafer process in solar energy factory includes two bottlenecks, named crystal-growing workstation and wafer-slicing workstation, which belongs to make-to-stock and make-to-order. The process time and setup time on crystal-growing workstation are very long. The wafer-slicing workstation owns multiple-type machines which are in batch processing. For each macine in each machine type, the process time and throughput rate for an order is different. To be an effective manufacturing system and to improve competitiveness, the solar energy factory needs to make production plan properly for each period appropriately so as to satisfy the demand of orders. Thus, this thesis develops a master production scheduling (MPS) system for the solar energy factory for the manufacturing environment.
The MPS system includes rough cut capacity planning module and bottleneck scheduling module. The rough cut capacity planning module is used to calculate the capacity supply of each bottleneck workstation and the time needed by all orders. Based on the result of rough cut capacity planning, the bottleneck scheduling module constructs the integer programming model for the wafer-slicing workstation, which considers the machines load, setup time, quantity of each order, release time and due date, to generate the production schedule on each machine and the production amount for each order, with minimizing number of tardy orders as the objective.
According to the result of cases analysis, this system can attain optimal solution. Furthermore, by planning multi-planning periods in a horizon simultaneously, it can reduce the number of setup times and the setup time between periods. In addition, the thesis also proposes another scheduling system which pursue earlier period can produce as far as possible enables later period to have surplus produces energy for urgent orders of customers. Hence, the production scheduling system proposed in this thesis can allocate the best production quantity of each order on each machine in each planning period in effectively time.
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