臺灣博碩士論文加值系統

隨著台灣半導體產業的蓬勃發展及分工趨向專業化，半導體測試廠的競爭將更顯劇烈。測試廠為增加競爭力，無不加強生產管理來面對。而建構產能規劃系統便是提供生產管理者解決生管問題重要工具之一。
本研究所發展之無限產能規劃系統可解決半導體測試廠之產能規劃問題。吾人建構之產能規劃系統可分為四個模組：（1）在製品指派模組、（2）批量投料模組、（3）產能堆疊模組、（4）產能平衡模組。在製品指派模組首先收集在製品之資訊，包含測試批目前加工站別、批量數量…等。而後針對主生產排程所設定之需求，依產品之週期時間預估測試批於各加工站開工及完工時間。當在製品之數量不能滿足主生產排程所設定之需求時，便使用批量投料模組進行投料。測試批之開工及完工時間計算完成後，利用產能堆疊模組堆疊機台及治具於各天之產能。若生產資源各天產能堆疊狀況不盡理想時，可使用產能平衡模組以修改測試批開工時間之方式，平衡生產資源之產能。
本研究以Visual Basic為工具，發展一套產能規劃軟體的雛形。並根據工業界實際的資料以驗証本產能規劃系統。藉由實驗設計檢驗產能規劃系統之績效，實驗的結果顯示所發展之產能規劃系統在平衡生產資源各天產能不均現象時，具有不錯的績效。

Semiconductor manufacturing in Taiwan is growing very fast. In Final Test area, improved capacity planning is one way to increase productivity and competitiveness.
In this research, a capacity planning system is proposed for a IC test plant. Four modules are developed：WIP-Pulling Module, Lot Release Module, Workload Accumulate Module, and Workload Balance Module. WIP-Pulling Module is used to caculate lot start time and finish time to meet master production schedule (MPS) using WIP information such as current operation and batch size. When WIP quantity is insufficient, Lot Release Module is called. After calculating the lot start time and finish time, Workload Accumulate Module is used to accumulate the workload of machine and jig in each day. If the workload of machine and jig are unbalanced, Workload Balance Module is used to balance these manufacturing resources.
A prototype capacity planning software is developed in Microsoft Visual Basic and industrial data are used to test the performance of the capacity planning system. Based on the design of experiments, simulation results show that the capacity planning system is effective and efficient to balance the workload of manufacturing resources including machine and jig.

中文摘要I
英文摘要II
誌謝III
目錄IV
圖目錄VII
表目錄IX
第一章緒論1
1.1 研究背景與動機1
1.2 研究目的4
1.3 研究範圍與限制5
1.4 研究方法與步驟6
1.5 章節概要8
第二章文獻探討9
2.1 台灣半導體測試工業近況9
2.2 半導體測試製程之介紹13
2.2.1 記憶體晶圓測試13
2.2.2記憶體成品測試17
2.3 測試廠生產管理的特性23
2.4 國內外產能規劃研究之探討27
2.4 產能規劃方法之分類31
第三章 產能規劃演算法之建立37
3.1 問題描述37
3.2 問題基本假設40
3.3 符號定義41
3.4 在製品指派模組43
3.4.1 在製品指派觀念44
3.4.2 在製品指派演算法51
3.5 批量投料模組52
3.5.1 批量投料觀念53
3.5.2 批量投料演算法54
3.6 產能堆疊模組55
3.6.1 產能堆疊觀念55
3.6.2 機台產能堆疊演算法57
3.6.3 治具產能堆疊演算法58
3.7 產能平衡模組58
3.7.1 產能平衡觀念59
3.7.2 機台產能平衡演算法60
3.7.3 治具產能平衡演算法61
第四章演算法實驗設計63
4.1 輸入資料說明64
4.1.1 產品資料65
4.1.2 產品流程資料65
4.1.3 主生產排程資料66
4.1.4 在製品分佈資料67
4.1.5 機台資料68
4.1.6 治具資料68
4.2 績效衡量指標69
4.2.1 瓶頸生產資源各天使用率之平均標準差70
4.2.2 瓶頸生產資源使用率超過100％之累計天數70
4.2.3 瓶頸生產資源使用率超過100％時之累計使用率70
4.3 實驗設計71
第五章 實驗結果與討論72
5.1 瓶頸機台各天使用率之平均標準差74
5.2 瓶頸機台使用率超過100％之累計天數76
5.3 瓶頸機台使用率超過100％時之累計使用率79
5.4 瓶頸治具各天使用率之平均標準差81
5.5 瓶頸治具使用率超過100％之累計天數84
5.6 瓶頸治具使用率超過100％時之累計使用率86
第六章 結論與未來展望89
6.1 結論89
6.2 未來展望90
參考文獻92
附錄95
自傳97

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