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研究生:張艾琳
研究生(外文):Chang, Ai-Lin
論文名稱:多績效目標下決定自動化搬運系統最佳車數之決策架構
論文名稱(外文):A Novel Integrated Framework for Multi-objective Vehicle Fleet Sizing of Automated Material Handling System
指導教授:張國浩張國浩引用關係
指導教授(外文):Chang, Kuo-Hao
學位類別:碩士
校院名稱:國立清華大學
系所名稱:工業工程與工程管理學系
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2013
畢業學年度:101
語文別:英文
論文頁數:33
中文關鍵詞:自動化搬運系統工廠自動化模擬最佳化資料包絡分析法車數配置
外文關鍵詞:Automated Material Handling System (AMHS)Factory AutomationSimulation OptimizationData Envelopment Analysis (DEA)Vehicle Allocation
相關次數:
  • 被引用被引用:3
  • 點閱點閱:288
  • 評分評分:
  • 下載下載:32
  • 收藏至我的研究室書目清單書目收藏:0
自動化搬運系統在工廠自動化中扮演著非常重要的角色,而其中之車數決策問題更為導入此系統時之關鍵議題之一。然而,有鑑於自動化搬運系統與製程之複雜性與不確定性〈如:機台之加工時間〉,此系統之車數決策問題已屬不易,若再納入多個績效目標同時考量之情況下,將使問題更趨複雜。本研究係針對此自動化搬運系統中之車數決策問題,提出一整合性之方法,即結合模擬最佳化及資料包絡分析法以求得在多個績效目標下之最佳車數配置。由於利用模擬方式所得之績效指標值近似於隨機環境中之績效指標實際值,因此在第二階段利用資料包絡分析法時,所求得之車數配置方案之績效分數即會非常接近實際情況。最後,利用一實例以驗證所提出方法在實務問題中之有效性及可行性。
Automated Material Handling System (AMHS) plays a key role in factory automation. Vehicle feet sizing is one of the critical issues when designing an effective AMHS. However, due to complexity of AMHS design and uncertainty involved in the production process, e.g., random processing time, vehicle feet sizing is a challenging problem, especially when there are multi-objectives, e.g., minimized cycle times and maximized throughputs are simultaneously desired. In this paper, we propose a novel framework which integrates simulation optimization techniques and Data Envelopment Analysis (DEA) to facilitate the identification of the optimal feet sizes of AMHS under multiple objectives. The trade-os between different objectives can also be demonstrated. A numerical study shows that the proposed framework can outperform the traditional approaches. In addition, an empirical study at the end verifies the effectiveness and the viability of the proposed framework in practical settings.
Contents
1 Introduction 1
1.1 Problem Background . . . . . . . . . . . . . . . 1
1.2 Literature Review. . . . . . . . . . . . . . . . 2
1.3 Research Significance . . . . . . . . . . . . . 4
2 Problem Definition 6
2.1 Description of The Problem . . . . . . . . . . . 6
2.2 Mathematical Formulation . . . . . . . . . . . . 8
3 Solution Methodology 10
3.1 Phase I - Simulation Optimization . . . . . . . 12
3.2 Phase II - Data Envelopment Analysis (DEA) . . 16
4 Numerical Experiment 20
4.1 Comparison of The Proposed Framework and The Analytical Method . . . .. . . .. . . .. . . .. . . .. . . .. 20
4.2 Result . . . . . . . . . . . . . . . . . . . . 22
5 Empirical Study 25
6 Conclusion 29
Arfin, R., P.J. Egbelu. 2000. Determination of vehicle requirements in automated guided vehicle systems: a statistical approach. Production Planning and Control 11(3) 258-270.
Beamon, B.M., A.N. Deshpande. 1998. A mathematical programming approach to simultaneous unit-load and feet-size optimisation in material handling systems design. The International Journal of Advanced Manufacturing Technology 14(11) 858-863.
Billingsley, P. 1995. Probability and Measure. John Wiley and Sons, New York.
Bozer, Y.A., C. Myeonsig, M.M. Srinivasan. 1994. Expected waiting times in single-device trip-based material handling systems. European Journal of Operational Research 75 200-216.
Charnes, A., W.W. Cooper, Rhodes E. 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2(6) 429-444.
Egbelu, P.J. 1987. The use of non-simulation approaches in estimating vehicle requirements in an automated guided vehicle based transport system. Material Flow 4 17-32.
Fu, M.C. 2002. Optimization for simulation: theory vs. practice. INFORMS Journal on Computing 14 192-215.
Hong, L.J., L.N. Nelson. 2006. Discrete optimization via simulation using compass. Operations Research 54(1) 115-129.
Huang, C.-J., K.-H. Chang, J.T. Lin. 2012. Optimal vehicle allocation for an automated materials handling system using simulation optimisation. International Journal of Production Research 50(20) 5734-5746.
Hutchinson, G.K. 1983. The design of an automated material handling system for a job shop. Computers in Industry 4(2) 139-146.
Jimenez, J.A., M. Bell, C. Adikaram, V. Davila, R. Wright, A. Grosser. 2010. Amhs factors enabling small wafer lot manufacturing in semiconductor wafer fabs. Proceedings of the 2010 Winter Simulation Conference. 2575-2585.
Kobza, J.E., Y.-C. Shen, R.J. Reasor. 1998. A stochastic model of empty-vehicle travel time and load request service time in light-traffic material handling systems. IIE Transactions 30(2) 133-142.
Kong, S.H. 2007. Two-step simulation method for automatic material handling system of semiconductor fab. Robotics and Computer-Integrated Manufacturing 23 409-420.
Koo, P.H., J. Jang, J. Suh. 2005. Estimation of part waiting time and feet sizing in agv
systems. international journal of flexible manufacturing systems. IIE Transactions 16(3) 211-228.
Kurosaki, R., N. Komada, H. Wantanabe, H. Yano. 1997. Amhs for 300 mm wafer. IEEE International Symposium on Semiconductor Manufacturing Conference D13-D16.
Lin, J.T. 1990. Microcomputers determine how many agvs are needed. Industrial Engineering 22(30) 53-56.
Lin, J.T., F.-K. Wang, Y.-M. Chang. 2006. A hybrid push/pull-dispatching rule for a photobay in a 300-mm wafer fab. Robotics and Computer-Integrated Manufacturing 22(1) 47-55.
Lin, J.T., F.-K. Wang, C.-J. Yang. 2005. The performance of the number of vehicles in a dynamic connecting transport amhs. International Journal of Production Research 43(11) 2263-2276.
Lin, J.T., F.-K. Wang, P.-Y. Yen. 2004. The maximum loading and the optimum number of vehicles in a double-loop of an interbay material handling system. Production Planning and Control 15(3) 247-255.
Mackulak, G.T., P. Savory. 2001. A simulation-based experiment for comparing amhs performance in a semiconductor fabrication facility. IEEE Transactions on Semiconductor Manufacturing 14(3) 273-280.
Maxwell, W.L., J.A. Muckstadt. 1982. Design of automatic guided vehicle systems. IIE Transactions 14(2) 114-124.
Newton, D. 1985. Simulation model calculates how many automated guided vehicles are needed. Industrial Engineering 17(2) 68-78.
Qui, L., W.-J. Hsu, S.-H. Huang, H. Wang. 2002. Scheduling and routing algorithms for agvs: a survey. International Journal of Production Research 40(3) 745-760.
Rajotia, S., K. Shanker, J.L. Batra. 1998. Determination of optimal agv eet size for an fms. International Journal of Production Research 36(5) 1177-1198.
Scheel, H. 2001. Undesirable outputs in e_ciency valuations. European Journal of Operational Research 132(2) 400-410.
Smith, J.S. 2003. Survey on the use of simulation for manufacturing system design and operation. Journal of Manufacturing Systems 22(2) 157-171.
Vis, I.F.A., R. De Koster, K.J. Roodbergen, L.W.P. Peeters. 2001. Determination of the number of agvs required at a semi-automated container terminal. Journal of the Operational Research Society 52 409-417.
Wang, F.-K., J.T. Lin. 2004. Performance evaluation of an automated material handling system for a wafer fab. Robotics and Computer-Integrated Manufacturing 20 91-100.

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