| Summary: | 碩士 === 中原大學 === 工業與系統工程研究所 === 100 === Semiconductor market is highly affected by globalization, and equipment products become very diverse to meet various customer requirements. Therefore, the sales forecasting for customized equipment products has become easy to have errors. While forecasting errors happened, such as the number was incorrect or rush order occurred, the manufacturer would consider disassembling work-in-process (WIP) of the similar products in the plant to fulfill the rush order. Although the rush order can be delivered on time in this way, the regular order might become late and the total production cost would increase.
In this study, to solve inaccurate forecasting or excess demand problems, a mathematical programming model was developed to minimize total production cost for a semiconductor equipment plant. The assembly process was modeled as a flow line with four consecutive workstations, and components were assembled or disassembled in each station. This model would decide whether and how many to disassemble WIP of similar products to meet the excess demand based on the goal of minimizing the total production cost. The position of customer order decoupling points (CODPs), the penalty cost for tardiness, and delivery lead time were considered as significant factors in this model and their effects were analyzed.
The minimum total cost was found with the CODP positioning after the fourth workstation and sensitivity analysis was applied to that model. Based on the results, this study found that while the CODP moved to the customer side, the disassembled number of WIP decreased. The penalty cost of rush order for tardiness has most significant effects on the total cost, and it is suggested that the disassembled number of WIP should be the decision variable. If the rush order arrives, the penalty cost for tardiness and delivery lead time are inputted into the mathematical programming model, and the disassembled number of WIP will be solved to minimize the total cost.
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