臺灣博碩士論文加值系統

本研究以最小化製造成本與加權延誤成本為目的，探討平行車削機台之排程問題。車削作業(turning operation)為製造產業中常見之一機械製造作業。通過改變其作業參數，作業員能夠操控車削作業的工作時間。在實際工作環境中，一工件之車削作業往往需要多次車削才能完工。此類車削作業我們稱之為多層車削作業(multi-pass turning operation)。多層車削作業本身為一混整數非線性規劃問題(Mixed Integer Nonlinear Programming; MINLP)。由於車削作業的排程本身為可控時間排程問題(controllable processing time scheduling),這使得考慮多層車削作業的排程問題變得不易求解。本研究根據車削作業本身的特性，提出一二階段方法來求解此問題。第一階段先求解多層車削作業的最佳化參數，並在第二階段時以基因演算法(Genetic Algorithm)完成其排程演算。根據模擬結果顯示，本研究所提出之二階段方法能在合理的時間內求得比相關研究更為佳的解。

This paper studies the scheduling problem of turning process in identical parallel machine environment. Scheduling of turning machine is a case of controllable processing time scheduling since the processing time of turning operation can be adjusted by alter the cutting speed, feed rate and depth of cut. The determination of subdivision of depth of cut is another decision problem to be solve in turning operation. Since the determination of subdivision of depth of cut is a MINLP problem itself, the combination of the two problem make the scheduling problem of turning machine very hard to solve. Our research objective is to build an effective approach to solve the minimization of the manufacturing cost and weighted tardiness cost in scheduling of parallel turning machine with multi-pass turning. The robustness of the methodology and computationally efficient are guaranteed under different scenario settings.

誌謝 II
ABSTRACT IV
CONTENTS V
LIST OF FIGURES VII
LIST OF TABLES X
Chapter 1 Introduction 1
1.1 Research Background 1
1.1.1 Optimization of Turning Operation 1
1.1.2 Determination of Subdivision of depth of cut 3
1.1.3 Scheduling of Turning Machine 4
1.2 Research Objective 4
1.3 Organization of the Thesis 5
Chapter 2 Literature Review 6
2.1 Optimization of multi-pass turning operation 6
2.2 Parallel Turning Machine Scheduling 7
Chapter 3 Problem Formulation and Methodology 8
3.1 Effect of Cutting Parameter on Cost Component in Turning Operation 8
3.1.1 Machining Time Property 9
3.1.2 Tool life Property 9
3.1.3 Power Consumption Property 13
3.2 Parallel Machine Scheduling Model for Multi-pass Turning Operation 18
3.2.1 Nomenclature and assumptions 18
Chapter 4 Multi-pass Turning Operation Scheduling with Machining Conditions’ Solution Set Feedback System 25
4.1 First-stage: Optimization of Turning Operation 25
4.1.1 Production Cost Minimization Model 25
4.1.2 Processing Time Minimization Model 26
4.2 Optimality of minimum number of cut 27
4.2.1 Validation of the methodology 29
4.2.2 Effectiveness Comparison of the methodology 35
4.3 Building of Machining Conditions’ Solution Set Feedback System 37
4.3.1 Scheduling Model 37
4.3.2 Comparison of Solution Sets 38
4.4 Construction of Genetic Algorithm 39
4.4.1 Chromosome Design 40
4.4.2 Operations and Parameters Setting 40
Chapter 5 Experiment Result and Analysis 44
5.1 Experiment Settings 44
5.1.1 Methodology for Comparison 44
5.1.2 Experimental Factors Design 45
5.1.3 Parameters Settings 47
5.2 Experimental Result for Single pass case 48
5.3 Experimental Result for Multi-pass case 53
Chapter 6 Conclusion and Future Research 60
6.1 Conclusion 60
6.2 Future Research Direction 60
Reference 61
Appendix A: pseudo code for GA 64

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