臺灣博碩士論文加值系統

拆裝規劃指的是探討產品的拆裝(拆卸)流程，拆裝流程指的是零件之間拆卸的排序。廣義而言，為了移除某一個零件，所有擋住拆解路徑的零件都必須移除。
基因演算法用於拆裝規劃已行之有年，其優點便是容易根據問題來調整設計，產生創意，故深受許多研究者喜愛。區間間隔法原本是用於求解排程規劃問題的方法，優點是能快速地排出順序解，本研究將此方法用於求解拆裝規劃的問題上。
本研究分為四個階段，首先修正傳統基因演算法，改善傳統基因演算法之缺點，第二階段使用修正後基因演算法及區間間隔法求解其他研究之範例，驗證其演算能力。第三階段，以區間間隔法及親和力函數結合修正後基因演算法，改善修正後基因演算法之缺點。第四階段為了更進一步加強演算法求解的能力，加入Block機制，改善結合後基因演算法之缺點，並使用檯燈為範例說明演算法過程，最後以印表機測試所有演算法之效率。

Disassembly planning is to explore the disassembly process of a product. The disassembly process means that the order ranks about dismantled parts for this product. In addition, the disassembly process of blocked components sometimes should be removed in order to remove for a certain part. In recently years, genetic algorithms (GAs) were very popular used for determining disassembly planning problem. They are easy to be designed and can be generated more creative ideas. Moreover, Forward phase heuristics (FPH) were used to solve the disassembly planning problem. FPH method can quickly determine the sequential order for disassembly planning, originally was used on the scheduling problems. In this study, example of Kongar and Gupta (2006), table lamp and laser printer were used as examples to verify the proposed assessment methodology. The research is divided into four phases. First, the traditional GAs were modified to fit the problem of disassembly planning. Second, the GAs and FPH were used to solve the test examples. Third, FPH, affinity function and GAs were incorporated to explore the problems of disassembly planning. Finally, in addition to the third phase of proposed algorithms were included, the block mechanism was added to enhance the efficiency of algorithms. Through the test examples, the algorithm efficiency was found to gradually get better according to the four stages.

摘要 i
ABSTRACT ii
目錄 iii
表目錄 iv
圖目錄 v
一、前言 1
二、拆裝規劃之建構 4
2.1 範例說明 5
2.2 區間間隔調換法 20
2.3 修正式基因演算法 21
三、區間間隔調換法 25
3.1 Kongar and Gupta範例 25
3.2 檯燈 26
3.3 印表機 26
四、修正式基因演算法 28
4.1 Kongar and Gupta範例 28
4.2 檯燈 30
4.3 印表機 30
五、混合修正式基因演算法 32
5.1 挑選機制 33
5.2 親和力函式 33
5.3 檯燈 33
5.4 印表機 37
六、混合引導式基因演算法 37
6.1 相似矩陣 39
6.2 Block機制 41
6.3 檯燈 41
6.4 印表機 43
七、結果與討論 44
參考文獻 48
附錄 50

[1] 孟令鵬，2007，「應用人工免疫演算法求解Connector為基組裝規劃問題」，國立勤益科技大學工業工程與管理研究所，碩士論文。
[2] 施欣宜，2005，「改良式基因演算法求解複雜限制式之組裝規劃探討」，大葉大學工業工程研究所，碩士論文。
[3] 張銀和，2004，「引導式基因演算法應用於Connector為基之組裝規劃」，大葉大學工業工程研究所，碩士論文。
[4] 郭婉儀，2013，「產品生命週期下整合模組化與拆裝規劃之研究」，國立勤益科技大學工業工程與管理研究所，碩士論文。
[5] M.A. Ilgin, S.M. Gupta, 2010, “Environmentally conscious manufacturing and product recovery (ECMPRO): A review of the state of the art” Journal of Environmental Management, Vol.91, pp.563–591.
[6] C.B. Kalayci, O. Polat, S.M. Gupta, 2014, “A hybrid genetic algorithm for sequence-dependent disassembly line balancing problem”, Annals of Operations Research, pp. 1–34.
[7] T.L. De Fazio, D.E. Whitney, 1987, “Simplified generation of mechanical assembly sequences”, IEEE Journal of Robotics and Automations, Vol.3, pp.640–658.
[8] E. Kongar, S.M. Gupta, 2006, “Disassembly sequencing using genetic algorithm”, International Journal of Advanced Manufacturing Technology, Vol.30, pp. 497–506.
[9] M. Gen, R. Cheng, 1997, Genetic Algorithms & Engineering Design, New York: John Wiley & Sons, Inc.
[10] S. Ghandi, E. Msaehian, 2015, “Review and taxonomies of assembly and disassembly path planning problems and approaches”, Computer-Aided Design, Vol.67-68, pp.58-86.
[11] D.E. Goldberg, 1989, Genetic algorithms in search, optimization and machine learning, Reading, New York: Addison-Wesley.
[12] H. Fujimoto, M. F. Sebaaly, 2000, “A new sequence evolution approach to assembly planning”, Transaction of the ASME Journal of Manufacturing Science and Engineering, Vol.122, pp. 198–205.
[13] H. Srinivasan, R. Figueroa, R. Gadh, 1999, “Selective disassembly for virtual prototyping as applied to de-manufacturing”, Robotics and Computer-Integrated Manufacturing, Vol.15, pp.231-245.
[14] F.H. Barron, B.E. Barrett, 1996, “Decision Quality Using Ranked Attribute Weights”, Management Science, Vol. 42, pp1515-1523.
[15] J.R. Li, L.P. Khoo, S.B. Tor, 2005, “An object-oriented intelligent disassembly sequence planner for maintenance”, Computers in Industry, Vol.56, pp. 699–718
[16] A.J.D. Lambert, S.M. Gupta, 2005, Disassembly Modeling for Assembly, Maintenance, Reuse and Recycling, CRC press: London.
[17] T.F. Go, D.A. Wahab, M.N.Ab. Rahman, R. Ramli, A. Hussain, 2012, “Genetically optimised disassembly sequence for automotive component reuse”, Expert Systems with Applications, Vol.39, pp.5409–5417.
[18] H.E. Tseng, C.C. Chang, J.D. Li, 2008, “Modular design to support green life-cycle engineering”, Expert System with Applications, Vol.34, pp.2524-2537.
[19] H.E. Tseng, J.D. Li, Y.H. Chang, 2004, “A connector-based approach to assembly planning using genetic algorithms”, International Journal Production Research, Vol.42, pp.161-171.
[20] H.E. Tseng, C.E. Tang, 2006, “A sequential consideration for assembly sequence planning and assembly line balancing using the connector concept”, International Journal of Production Research, Vol.44, pp.97-116.
[21] H. Wang, D. Xiang, G. Duan, 2008, “A genetic algorithm for product disassembly sequence planning”, Neurocomputing, Vol.71, pp.2720–2726.