以基因演算法求解作業排程於TFT-LCD組立廠｜國立臺灣科技大學博碩士論文系統

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研究生：	尤春凡 Bayu - Rezki Pratama
論文名稱：	以基因演算法求解作業排程於TFT-LCD組立廠 Operation Scheduling in TFT-LCD Cell Process Using Genetic Algorithm
指導教授：	林希偉 Shi-Woei Lin 陳建良 James C. Chen
口試委員:	陳子立 Tzu-Li Chen
學位類別：	碩士 Master
系所名稱：	管理學院 - 工業管理系 Department of Industrial Management
論文出版年：	2013
畢業學年度：	101
語文別：	英文
論文頁數：	62
中文關鍵詞：	排序、TFT-LCD組立廠、產能規劃系統、多目標遺傳算法、實驗設計
外文關鍵詞：	scheduling, TFT-LCD cell, capacity planning system, multi-objective genetic algorithm, experimental design
相關次數：	點閱：328 下載：5
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TFT-LCD組立廠特徵在於作為平行機調度問題，順序相關的設置時間、多步驟的生產、多目標於彩色濾光片和陣列廠之間的限制。在拉式生產和產能有限的假設基礎上，本研究應用產能規劃系統（CPS）於TFT-LCD組立製程作業調度架構上。提出了一種改進的多目標遺傳算法（MOGA）生產訂單調度決策，同時最大限度地減少機器的工作量平衡，完工時間和延遲。改進的MOGA認為優先規則，從簡單的調度規則作為基礎，產生的解決方案。設置精細完整的MOGA調節參數使用兩因子實驗設計和計算實驗進行評估的意義和計算的穩健性與其他方法進行比較，並採用全因子實驗設計的初步實驗。所有的性能指標都轉化成一個單一的指數進行比較（總體性能）。在總體性能方面，改進的MOGA性能明顯優於其他方法，因此可以合理的知道改進的MOGA是較優的排序方法。

TFT-LCD cell process is characterized as a parallel-machine scheduling problem with multiple products, sequence-dependent setup times, multi-step production, multi-objective, and matching constraints between color filter and array line. On the basis of pull philosophy and the assumption of finite capacity, this research applies the capacity planning system (CPS) framework to deal with the operation scheduling in TFT-LCD cell process environment. A modified multi-objective genetic algorithm (MOGA) is proposed to produce the order dispatching decision which simultaneously minimizes the machine workload balance, makespan, and lateness. Modified MOGA considers the priority rule from the simple dispatching rule as a prior knowledge when generates the solution sets. The preliminary experiment is applied to set the fine MOGA tuning parameter using two-level factorial experimental design and the computational experiment is conducted to evaluate the significance and the robustness of proposed algorithm performance compared with other competitive algorithms using full factorial experimental design. All of the performance indices are transformed into a single index (overall performance) by using desirability function. With respect to overall performance, modified MOGA performances are significantly better than other competitive algorithms, thus modified MOGA can be reasonably concluded to achieve steadily better solution.

ABSTRACT	i
ACKNOWLEDGEMENT	ii
CONTENT	iii
LIST OF FIGURES	v
LIST OF TABLES	vi
Chapter 1 Introduction	1
1.1 Background	1
1.2 Thesis Objectives	4
1.3 Justifications	4
1.4 Organization of Thesis	5
Chapter 2 Literature Review	6
2.1 Current Research about Scheduling in TFT-LCD Industry	6
2.2 Dispatching rule	7
2.2.1 Heuristic method	7
2.2.3 Meta-heuristic method	8
Chapter 3 Problem Definition and Methodology	10
3.1 Overview of TFT-LCD Cell Process	10
3.2 Methodology of Capacity Planning System (CPS) using modified MOGA	11
3.2.1 Capacity Planning System (CPS)	15
3.2.2 Modified MOGA	22
Chapter 4 Result and Analysis	30
4.1 Simulation Environment	30
4.2 MOGA Tuning Parameters	31
4.3 Analysis of Experimental Design	34
4.3.1 Experimental Design Factors and Responses	34
4.3.2 Result and Discussion	38
4.4	Performance Analysis of Original MOGA and Modified MOGA	43
4.4.1 Performance Analysis of Significant Responses	43
4.4.2 Performance Analysis of Significant Factors	47
Chapter 5 Conclusion and Future Research	50
5.1 Conclusion	50
5.2 Suggestion	50
Bibliography	52
Appendix	55
Appendix 1 - MOGA parameter setting	55
Appendix 2 - Paired T result	57

                                

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