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研究生:Ivan Kurniawan
研究生(外文):Ivan Kurniawan
論文名稱:顯示卡彈性組裝線之代理人架構模擬模式
論文名稱(外文):Agent-Based Simulation Modeling of a Flexible GPU-Card Final Assembly Line
指導教授:王孔政王孔政引用關係
指導教授(外文):Kung-Jeng Wang
口試委員:郭人介陳怡永
口試委員(外文):Ren-Jieh KuoYi-Yung Chen
口試日期:2020-06-01
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:工業管理系
學門:商業及管理學門
學類:其他商業及管理學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:英文
論文頁數:56
中文關鍵詞:Agent based systemFlexible assembly lineGraphic processing unitSimulation
外文關鍵詞:Agent based systemFlexible assembly lineGraphic processing unitSimulation
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  • 被引用被引用:0
  • 點閱點閱:52
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高科技產品的市場需求始終隨著產品規格的變化而改變,為了在市場中具有競爭力,該產線系統必須兼顧靈活性,並且在面對大量客製化時,產線可以重新配置。彈性裝配線 (flexible assembly line) 可實現高效率的混合性生產,其需要縝密的系統設計與規劃,以利充分利用資源,本案以圖形處理器 (graphic processing unit, GPU) 裝配線為例。由於智能體基的模擬 (agent based simulation, ABS) 富有靈活性及可擴展性,因此本研究採用 ABS模型應用在FAL中。本案擬議框架涵蓋三大部分:實際環境,虛擬環境及評估分析,透過智能體基的模擬模型詳細闡述 GPU裝配線中的排序與調度性能,並使用柏拉圖最適分析解決零件延遲和生產量之間的衝突。
Market demands of high-tech products always evolves over time by product specification. To be competitive, a production system needs to be flexible and reconfigurable as facing mass-customization. Flexible assembly line (FAL) enables mixed production with high efficiency. One example is graphic processing unit (GPU) cards. FAL requires comprehensive system design and scheduling to fully utilize the resources. This study adopts agent based simulation (ABS) modelling for an FAL because of the abilities of ABS in flexibility and scalability. The proposed framework consists of three parts: real environment, virtual environment, and evaluation and analysis. This study elaborates sequencing and scheduling performances in the GPU-card assembly line by using agent-based simulation modelling. Pareto frontier analysis is conducted to resolve conflicts between part tardiness, utilization, throughput.
摘要 i
ABSTRACT ii
ACKNOWLEDGEMENT iii
TABLE OF CONTENTS iv
LIST OF FIGURES vi
LIST OF TABLES vii
CHAPTER 1. INTRODUCTION 1
1.1. Research Background 1
1.2. Research Objectives 2
1.3. Research Limitation 2
1.4. Thesis Structure 2
CHAPTER 2. LITERATURE REVIEW 3
2.1. Flexible manufacturing 3
2.2. Simulation modeling for distributed control 4
2.3. ABS modelling 5
CHAPTER 3. MODELING 8
3.1. Research Framework 8
3.2. Proposed ABS for FAL framework 9
3.3. FAL architecture 10
3.4. Data collection and simulation modeling 12
3.5. Model validation 19
CHAPTER 4. EXPERIMENTS AND DISCUSSION 22
4.1. Statistical Analysis 22
4.2. Pareto Frontier Analysis 23
CHAPTER 5. CONCLUSION 31
5.1. Conclusion 31
5.2. Future Research 32
Appendix 1. The logic flow of agents. 33
Appendix 2. ANOVA analysis 38
References 43
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