臺灣博碩士論文加值系統

在資源有限的條件下，人們逐漸意識到大量製造的方式帶來諸多浪費以及廢棄物的問題，部分的廢棄物仍然具有可使用或有價值的零件，只要透過適當地加工處理就能重複再利用這些零件。本研究探討考量作業關聯度之多人工作站拆卸線平衡問題(disassembly line balancing problem with multi-manned workstations)，應用改良式AND/OR圖(transformed AND/OR graph)作為拆卸作業之間的優序關係圖，進而建構數學規劃最佳化模型，目標為最小化工作站數量、最小化操作員總數及最大化拆卸線之作業關聯度，求得拆卸作業、工作站與操作員的最佳配置。由於拆卸線平衡問題屬於NP-hard問題，本研究發展雙向探索適應性基因演算法(bilateral exploration-adaptive genetic algorithm)與雙向探索基因演算法(bilateral exploration-genetic algorithm)以增進求解效率。最後將演算法應用於大型實務案例，並執行參數敏感度分析，將以上資訊提供給實務案例之管理人員，作為設計拆卸線佈置的決策參考依據。

This thesis studies the disassembly line balancing problem with muti-manned workstations considering task correlation. The transformed AND / OR graph (TAOG) is used as the priority relationship of tasks. An optimized mathematical programming model that aims to maximize the index of task correlation, to minimize the number of operators of disassembly line and to minimize the number of workstations simultaneously is established. As the disassembly line balancing problem is NP-hard problem; Two heuristic algorithms which are based on genetic algorithm(GA) and adaptive genetic algorithm(AGA) are developed to keep the efficiency of calculation. The response surface method(RSM) is used to get the most suitable parameters set of algorithms. Then, the algorithms are applied to solve the complex practical case and the sensitivity analysis of parameters is executed. The thesis provides above information as a reference to the manager of practical case.

摘要........................i
Abstract.....................ii
誌謝........................iii
目錄........................iv
表目錄........................vi
圖目錄........................ix
第一章 緒論.....................1
1.1 研究背景與動機...............1
1.2 研究目的.....................2
1.3 研究範圍與假設...............2
1.4 研究流程.....................3
第二章 文獻探討..................6
2.1 拆卸線平衡問題...............6
2.2 拆卸線先行關係與圖表.........13
2.3 作業關聯度..................15
2.4 多人工作站..................17
2.5 基因演算法..................20
2.6 實驗設計-反應曲面法.........24
2.7 小結........................31
第三章 問題定義..................32
3.1 問題定義.....................32
3.2 數學規劃模型..................33
3.3 測試問題.....................36
第四章 演算法開發與測試............45
4.1 建立可行平衡解之流程............45
4.2 演算法開發..................53
4.3 演算法參數優化..................66
4.4 問題測試與驗證..................75
第五章 實務案例.....................85
5.1 案例說明........................85
5.2 啟發式演算法之規劃結果............88
5.2.1 雙向探索適應性基因演算法之運算結果...89
5.2.2 雙向探索基因演算法之運算結果 .........92
5.2.3 實務案例結果小結..................95
5.3 配置結果比較與分析..................95
5.4 參數敏感度分析.....................96
5.4.1 週期時間調整之影響..................97
5.4.2 關係指數調整之影響...............100
5.4.3 工作站操作員數上限調整之影響 ......101
5.4.4 單人工作站與多人工作站差別之影響...104
第六章 結論與建議........................107
6.1 結論.................................107
6.2 建議.................................108
參考文獻 .................................109
附錄A....................................116
附錄B....................................130
附錄C....................................135
附錄D....................................140
Extended Abstract........................150

1.李芷毓 (2020)，考量工作關聯度之平衡問題，國立虎尾科技大學工業工程與管理系，碩士論文。

2.林李旺 (2013)，突破品質水準－實驗設計與田口方法之實務應用，全華圖書，新北市。

3.施欣妤 (2017)，製鞋業型IV生產線平衡問題研究，國立清華大學工業工程與工程管理學系，碩士論文。

4.葉怡成 (2001)，實驗計劃法－製程與產品最佳化，五南圖書，台北市。

5.謝欣宏 (2002)，台鐵司機員排班與輪班問題之研究-以基因演算法求解，成功大學交通管理科學研究所，碩士論文。

6.蘇朝墩 (2009)，六標準差，前程文化，新北市。

7.Agrawal. (1985). The related activity concept in assembly line balancing. International Journal of Production Research, 23(2), 403-421.

8.Agrawal, S., & Tiwari, M. K. (2008). A collaborative ant colony algorithm to stochastic mixed-model U-shaped disassembly line balancing and sequencing problem. International journal of production research, 46(6), 1405-1429. doi: 10.1080/00207540600943985

9.Akagi, F., Osaki, H., & Kikuchi, S. (1983). A method for assembly line balancing with more than one worker in each station. The International Journal of Production Research, 21(5), 755-770.

10.Akgündüz, O. S., & Tunalı, S. (2010). An adaptive genetic algorithm approach for the mixed-model assembly line sequencing problem. International Journal of Production Research, 48(17), 5157-5179.

11.Avikal,S., & Mishra, P. K. (2012). A new U-shaped heuristic for disassembly line balancing problems. Pratibha: International Journal of Science, Spirituality, Business and Technology, 1(1), 2277-7261.

12.Aydemir, A., & Turkbey, O. (2013). Multi-objective optimization of stochastic disassembly line balancing with station paralleling. Computers & Industrial Engineering, 65(3), 413-425. doi: 10.1016/j.cie.2013.03.014

13.Bentaha, M. L., Battaïa, O., & Dolgui, A. (2012). A stochastic formulation of the disassembly line balancing problem. In IFIP International Conference on Advances in Production Management Systems (pp. 397-404). Springer, Berlin, Heidelberg.

14.Bentaha, M. L., Battaïa, O., & Dolgui, A. (2014). Disassembly line balancing problem with fixed number of workstations under uncertainty. IFAC Proceedings Volumes, 47(3), 3522-3526.

15.Bentaha, M. L., Battaïa, O., & Dolgui, A. (2015). An exact solution approach for disassembly line balancing problem under uncertainty of the task processing times. International Journal of Production Research, 53(6), 1807-1818.

16.Brennan, L., Gupta, S. M., & Taleb, K. N. (1994). Operations Planning Issues in an Assembly/Disassembly Environment. International Journal of Operations & Production Management, 14(9), 57-67. doi: 10.1108/01443579410066767
17.Bukchin, J., Darel, E., & Rubinovitz, J. (1997). Team-oriented assembly system design: A new approach. International Journal of Production Economics, 51(1-2), 47-57.

18.Bukchin, J., & Masin, M. (2004). Multi-objective design of team oriented assembly systems. European Journal of Operational Research, 156(2), 326-352.

19.Buxey, G. M. (1974). Assembly line balancing with multiple stations. Management science, 20(6), 1010-1021.

20.Cevikcan, E., Aslan, D., & Yeni, F. B. (2019). Disassembly line design with multi-manned workstations: a novel heuristic optimisation approach. International Journal of Production Research, 58(3), 649-670. doi: 10.1080/00207543.2019.1587190

21.Cevikcan, E., Durmusoglu, M. B., & Unal, M. E. (2009). A team-oriented design methodology for mixed model assembly systems. Computers & Industrial Engineering, 56(2), 576-599.

22.Çil, Z. A., Mete, S., & Serin, F. (2020). Robotic Disassembly Line Balancing Problem: A Mathematical Model and Ant Colony Optimization Approach. Applied Mathematical Modelling, 86, 335-348.

23.Dimitriadis, S. G. (2006). Assembly line balancing and group working: A heuristic procedure for workers’ groups operating on the same product and workstation. Computers & Operations Research, 33(9), 2757-2774.

24.Ding, L. P., Feng, Y. X., Tan, J. R., & Gao, Y. C. (2010). A new multi-objective ant colony algorithm for solving the disassembly line balancing problem. The International Journal of Advanced Manufacturing Technology, 48(5-8), 761-771.

25.Duta, L., Filip, F. G., & Caciula, I. (2008). Real time balancing of complex disassembly lines. IFAC Proceedings Volumes, 41(2), 913-918.

26.Feldmann, K., Trautner, S., & Meedt, O. (1998). Innovative Disassembly Strategies Based on Flexible Partial Destructive Tools. IFAC Proceedings Volumes, 31(7), 1-6. doi: 10.1016/s1474-6670(17)40247-3

27.Güngör, A., & Gupta, S. M. (2002). Disassembly line in product recovery. International Journal of Production Research, 40(11), 2569-2589.

28.Ghosh, S., & Gagnon, R. J. (2007). A comprehensive literature review and analysis of the design, balancing and scheduling of assembly systems. International Journal of Production Research, 27(4), 637-670. doi: 10.1080/00207548908942574

29.Gungor, A., & Gupta, S. M. (1999). Disassembly line balancing. In Proceedings of the 1999Annual Meeting of the Northeast Decision Sciences Institute (pp. 193-195).

30.Gungor, A., & Gupta, S. M. (2001). A solution approach to the disassembly line balancing problem in the presence of task failures. International Journal of Production Research, 39(7), 1427-1467. doi: 10.1080/00207540110052157

31.Haupt, R. L., & Ellen Haupt, S.E. (2004). Practical genetic algorithms. Wiley, New York.

32.Hezer, S., & Kara, Y. (2015). A network-based shortest route model for parallel disassembly line balancing problem. International Journal of Production Research, 53(6), 1849-1865.

33.Kalayci, C. B., & Gupta, S. M. (2013). Simulated annealing algorithm for solving sequence-dependent disassembly line balancing problem. IFAC Proceedings Volumes, 46(9), 93-98.

34.Kalayci, C. B., Hancilar, A., Gungor, A., & Gupta, S. M. (2015). Multi-objective fuzzy disassembly line balancing using a hybrid discrete artificial bee colony algorithm. Journal of Manufacturing Systems, 37, 672-682.

35.Kalayci, C. B., Polat, O., & Gupta, S. M. (2016). A hybrid genetic algorithm for sequence-dependent disassembly line balancing problem. Annals of Operations Research, 242(2), 321-354.

36.Kellegöz, T. (2017). Assembly line balancing problems with multi-manned stations: a new mathematical formulation and Gantt based heuristic method. Annals of Operations Research, 253(1), 377-404.

37.Kellegöz, T., & Toklu, B. (2012). An efficient branch and bound algorithm for assembly line balancing problems with parallel multi-manned workstations. Computers & Operations Research, 39(12), 3344-3360.

38.Kellegöz, T., & Toklu, B. (2015). A priority rule-based constructive heuristic and an improvement method for balancing assembly lines with parallel multi-manned workstations.
International Journal of Production Research, 53(3), 736-756.

39.Khorasanian, D., Hejazi, S. R., & Moslehi, G. (2013). Two-sided assembly line balancing considering the relationships between tasks. Computers & Industrial Engineering, 66(4), 1096-1105.

40.Kim, Y. K., Kim, Y. J., & Kim, Y. (1996). Genetic algorithms for assembly line balancing with various objectives. Computers & Industrial Engineering, 30(3), 397-409.

41.Koc, A., Sabuncuoglu, I., & Erel, E. (2009). Two exact formulations for disassembly line balancing problems with task precedence diagram construction using an AND/OR graph. IIE Transactions, 41(10), 866-881. doi: 10.1080/07408170802510390

42.Kucukkoc, I., Li, Z., & Li, Y. (2019). Type-E disassembly line balancing problem with multi-manned workstations. Optimization and Engineering, 21(2), 611-630. doi: 10.1007/s11081-019-09465-y

43.Lambert, A. F., & Gupta, S. M. (2004). Disassembly modeling for assembly, maintenance, reuse and recycling: CRC press.

44.Lee, T. O., Kim, Y., & Kim, Y. K. (2001). Two-sided assembly line balancing to maximize work relatedness and slackness. Computers & Industrial Engineering, 40(3), 273-292.

45.Liang, J., Guo, S., Du, B., Li, Y., Guo, J., Yang, Z., & Pang, S. (2021). Minimizing energy consumption in multi-objective two-sided disassembly line balancing problem with complex execution constraints using dual-individual simulated annealing algorithm. Journal of Cleaner Production, 284, 125418.

46.Liu, J., Zhou, Z., Pham, D. T., Xu, W., Ji, C., & Liu, Q. (2020). Collaborative optimization of robotic disassembly sequence planning and robotic disassembly line balancing problem using improved discrete Bees algorithm in remanufacturing. Robotics and Computer-Integrated Manufacturing, 61, 101829.

47.McGovern, & Gupta. (2007a). A balancing method and genetic algorithm for disassembly line balancing. European Journal of Operational Research, 179(3), 692-708. doi: 10.1016/j.ejor.2005.03.055

48.McGovern, & Gupta. (2007b). Combinatorial optimization analysis of the unary NP-complete disassembly line balancing problem. International Journal of Production Research, 45(18-19), 4485-4511.

49.Moyer, L. K., & Gupta, S. M. (1997). Environmental concerns and recycling/disassembly efforts in the electronics industry. Journal of Electronics Manufacturing, 7(01), 1-22.

50.Mutlu, S., & Güner, B. (2021). A memetic algorithm for mixed-model two-sided disassembly line balancing problem. Procedia CIRP, 98, 67-72.

51.Özcan, U., & Toklu, B. (2009). A tabu search algorithm for two-sided assembly line balancing. The International Journal of Advanced Manufacturing Technology, 43(7-8), 822.

52.Qian, X., & Fan, Q. (2011, November). Solving multi-manned assembly line balancing problem by a heuristic-mixed genetic algorithm. In 2011 International Conference on Information Management, Innovation Management and Industrial Engineering (Vol. 3, pp. 320-323). IEEE.

53.Roshani, A., & Giglio, D. (2015). A simulated annealing approach for multi-manned assembly line balancing problem type II. IFAC-PapersOnLine, 48(3), 2299-2304.

54.Roshani, A., Roshani, A., Roshani, A., Salehi, M., & Esfandyari, A. (2013). A simulated annealing algorithm for multi-manned assembly line balancing problem. Journal of Manufacturing Systems, 32(1), 238-247.

55.Scholl, A. (1999). Balancing and sequencing of assembly lines (No. 10881). Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).

56.Wang, K., Li, X., Gao, L., Li, P., & Gupta, S. M. (2021). A genetic simulated annealing algorithm for parallel partial disassembly line balancing problem. Applied Soft Computing, 107, 107404.

57.Xia, X., Liu, W., Zhang, Z., Wang, L., Cao, J., & Liu, X. (2019). A balancing method of mixed-model disassembly line in random working environment. Sustainability, 11(8), 2304.

58.Yu, J., & Yin, Y. (2010). Assembly line balancing based on an adaptive genetic algorithm. The International Journal of Advanced Manufacturing Technology, 48(1), 347-354.

59.Zhang, Z., Wang, K., Zhu, L., & Wang, Y. (2017). A Pareto improved artificial fish swarm algorithm for solving a multi-objective fuzzy disassembly line balancing problem. Expert Systems with Applications, 86, 165-176.

60.Zhu, L., Zhang, Z., & Wang, Y. (2018). A Pareto firefly algorithm for multi-objective disassembly line balancing problems with hazard evaluation. International Journal of Production Research, 56(24), 7354-7374.

61.Zhu, L., Zhang, Z., & Guan, C. (2020). Multi-objective partial parallel disassembly line balancing problem using hybrid group neighbourhood search algorithm. Journal of Manufacturing Systems, 56, 252-269.