半導體製造業的製造系統特色包括耗費設備成本大、製程步驟數多與機器設備複雜，而依據製程設備、技術與產品需求，決定工廠內機台類別與數量的產能規劃程序在此稱為機台組態規劃。半導體廠中通常有上百種不同類型的機台，總機台數更可達到數百台，再加上製程複雜等特色，因此易發生過多的設備投資將造成產能閒置及資金積壓，亦無益於產出量的提升；過少設備投資則會使產出不如預期，而造成收益上的損失及影響生產績效，一般研究大多探討在一個固定的生產環境中，管理方式與系統參數對生產績效的影響，甚少研究專注於機台種類與數量的配置。因此，本研究以模擬為基礎的啟發式方法來調整機台組態，期望得到符合實際系統需求及具較適效益的機台組態決策。
　　本研究主要目的在考慮單一產品下，根據機台組態變動方式與瓶頸指標選擇搭配下，調整出數個不同的機台組態解，並以投資成本、效用函數及改變投料量方式來分析比較數種機台組態解的優劣，衡量的產出績效分別為週期時間、平均在製品量、等候時間、產出量及個別機台的利用率。

　The characters of the manufacturing system in semiconductor manufacturing are high-cost of equipment, plenty of manufacturing procedure, and complex of tool portfolio. Tool portfolio planning is a capacity planning with making decision of the category and quantity of machines in a wafer fab according to the technology and demand of product. There are usually more than one hundred different kinds of machines in a fab. According to hundreds of machines and complex of manufacturing procedure, the over-investing for tools under a fab where releasing amount of wafer is fixed will raise let machines idle, sit on capital and not be helpful to the throughput. On the other hand, the lack of investment for equipments will result in the insufficient throughput, the lost of benefit and terrible performance of manufacturing. The last researches generally probe into the case of the performance of manufacturing caused by management and factors of system. Less research does that case focus on the decision of tool portfolio. Therefore this thesis is to develop a simulation-based heuristics to adjust the tool portfolio in order to make the most beneficial decision about tool portfolio and manufacture sufficient throughput.
　The goal of this research is to find out many different tool portfolios by arrangement in pairs of the adjustment of tool portfolio and the choices of bottleneck according single product in fab. These tool portfolios would be analyzed and compared with some performance index, including investment, utility function and inference by changing input of material. These performance indices are cycle time, average work in process, queuing delay, throughput and the utilization of individual tools.

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