植物工廠訂單派送之系統模擬｜國立臺灣科技大學博碩士論文系統

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研究生：	李蕊佳 Rizka - Hadiwiyanti
論文名稱：	植物工廠訂單派送之系統模擬 A Simulation Study of Dispatching Rule in Plant Factory
指導教授：	楊朝龍 Chao-Lung Yang
口試委員:	郭彥甫 Yan-Fu Kuo 林樹強 Shu-Chiang Lin
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：	2012
畢業學年度：	100
語文別：	英文
論文頁數：	101
中文關鍵詞：	植物工廠、訂單派送策略、生產管理、系統模擬
外文關鍵詞：	dispatching rule, order picking policy, operation management
相關次數：	點閱：416 下載：10
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植物工廠是一種新式的農作物生產方式，透過對生產環境因素如溫度、溼度、光線、水分及營養物的控管，加速植物生長的效能及提升作物品質。由於作物生長不受季節及地區限制，作物可全年供應。本研究將植物工廠視為一個以接單生產為基礎的生產工廠。訂單的內容包泛作物種類、議定價格、數量及交期。本研究旨在探討當植物工廠產能相對滿載之情形下，如何透過有效的接單方案（order releasing policy）及訂單發送（order dispatching rule）來有效提升植物工廠之營收。本研究以系統模擬的方式，建構出一個小型的植物工廠接單生產的模式。透過系統模擬研究各種訂單處理機制，並設計一較佳的決策分析機制以決定是否接單及如何消化已接受之訂單。所提出的方案將作物合約價格、數量、及到期日作為考慮接單之要件。系統模擬結果顯示所提出的接單方案可有效地提升植物工廠的營收。

A plant factory is a crop production facility in which the cultivation elements for plant growth, such as temperature, humidity, light, and nutrients are controlled. Thus crops of different seasons can be effectively supplied year-round. In this research, a plant factory is considered as an order-based production system to receive crop orders of various types, prices, quantities, and due dates from food retailers or restaurants. It is crucial to identity appropriate order handling rules for maximum profitability. Several order releasing policies and dispatching rules for order handling were studied. A simulation model was developed to investigate the facility utilization and system performance. A combination of order picking policy and dispatching rule considering crop contracting price, order quantity, and order tardiness is proposed to enhance the profitability of a plant factory. The simulation results show the proposed method can obtain higher revenue under different operating scenarios.

誌	謝	v
論	文 摘 要	v
ABSTRACT	vi
CONTENTS	vii
FIGURES	ix
TABLE	x
CHAPTER 1 INTRODUCTION	1
CHAPTER 2 LITERATURE REVIEW	7
2.1 Plant Factory	7
2.1.1 Comparison with Other Planting System	8
2.1.2 Plant Factory Characteristics	9
2.2 Dispatching rule	10
2.3 Simulation	11
2.3.1 Flexsim Simulation Software	13
2.4 Previous Research	16
CHAPTER 3 RESEARCH METHODOLOGY	20
3.1 Terminology	20
3.2 Conceptual Model	22
3.2.1 Order Picking Policy	22
3.2.2 Dispatching rule	24
3.3 Simulation Model	24
3.3.1 Simulation Model in Flexsim	25
3.3.2 Parameter for Evaluation	27
3.3.3 Input Data Model	28
3.3.4 Performance Measure	29
CHAPTER 4 EXPERIMENTATION	31
4.1 Preliminary Study	31
4.2 Experimental Design	33
4.2.1 Experimental Setting	34
4.2.2 Parameter Settings	34
4.3 Result and Analysis of Simulation	35
4.3.1 Performance Measure Analysis	35
4.3.2 Statistical Analysis	42
CHAPTER 5 CONCLUSIONS AND FUTURE RESEARCH	50
5.1 Conclusions	50
5.2 Limitation	52
5.3 Further Research	53
REFERENCES	55
Appendix A. Revenue of all combinations	59
Appendix B. Revenue comparison for each combination	67
Appendix C. Revenue comparison of order picking policy	70
Appendix D. Revenue comparison of dispatching rule	76
Appendix E. ANOVA results	80
Appendix F. Pairwise comparison results using Tukey’s method	84

                                

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