在半導體封裝製程中，焊線工作站加工時間長因而配置了許多機台，且為生產線中的瓶頸所在。由於機台數量多，採購的時間點不一致，造成機台能力的差異，因此焊線工作站為典型的等效平行機台問題。平行機台加工站的排程規劃為生產力提升的重要因素。在典型的最佳化排程規劃中，對實際系統做了過多的假設或簡化，造成模式與真實系統間的落差。若採用以模擬為基礎的智慧搜尋法，也常因為模擬時間過長無法滿足即時性的需求。因此本研究，將發展一套以減少運算求解時間之模擬為基礎的啟發式演算法，期望符合真實系統之需求且可快速得到排程建議。

　　本研究中，發展了三個以模擬為基礎之啟發式排程演算法，分別為推式演算法、拉式演算法以及群組化機台拉式演算法。並模擬在不同生產情境下，不同演算法對於系統績效的反應及表現，這些績效分別為服務率、平均機台利用率、系統流程時間、產品平均流程時間、產品平均等待時間。隨後使用層級分析法決定各系統績效的權重，並使用多目標決策方法中的順序偏好法將此五個績效綜合考量，找出最適合的排程演算法。其分析結果表示，拉式演算法表現的績效優於其他兩個演算法，為本研究中推薦使用之排程方法。

　There are not only many machines installed in the work station of wire bonding of the semiconductor packing process, but also the bottleneck in this production line. The capabilities of the machines are different because of a lot of machines in the station, and times of purchased machines were different. Therefore, the wire bonding station is the classic uniform parallel machine problem. Schedule planning for parallel machines becomes the important factor of the improvement of production. In scheduling problem algorithms, the classic optimum schedule planning simplified the variables and conditions of process environment make the gap between model and real system. Furthermore, the simulation-based heuristic of intelligent search can not satisfied the requirement of in time for simulation. Therefore, this research will develop simulation-based heuristic algorithms to satisfy the requirement of immediately suggestion of scheduling.

　In this research, we develop three simulation-based scheduling heuristics, there were push algorithm, pull algorithm, and grouping machines of pull algorithm. We simulated different conditions of production, to observe the responses of different algorithms for objectives of service level, average utilization, flow time, average time in system, average queue time. Afterwards, this research used the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) to estimate this five objectives and computed the weight by AHP (Analytic Hierarchy Process) to find the satisfied scheduling algorithm. The result showed that the representation of pull algorithm were better than other two algorithms, and became the proposed scheduling method in this research.

　邱松茂，（民90年），UC封裝模具低沾黏表面處理技術，金屬工業35卷4期37～43頁。
　姜林杰祐、張逸輝、陳家明、黃家祚，(民90年)，系統模擬eM-Plant（SiMPLE++）操作與實務，華泰文化事業公司，台北。
　夏逸華，（民93年），IC封裝測試產業發展與趨勢分析，台商電子報專題分析，中華經濟研究院，台北(Downloadable from http://news.cier.edu.tw/Y04/1001/101.htm )
　莊達人， (民87年)，VLSI製造技術，高立圖書有限公司，台北。
　黃俊勛，（民94年），2004年台灣IC製造業回顧與展望，產業評析，工業技術研究院資訊中心，台北(Downloadable from http://www.itis.org.tw)
　經濟部投資業務處，（民93），台灣半導體現況與前景，產業資訊，經濟部投資業務處，台北(Downloadable from　http://hirecruit.nat.gov.tw/chinese/html/taiwan_08_02.htm)
　圖片由ASE Inc.提供，Downloadable from：http://www.asecl.com.tw/L&TQFP.htm
　蔡杭助，（民91年），結合基因演算法與離散事件模擬求解即時性平行機台之派工規劃問題，國立成功大學製造工程研究所，碩士論文。
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