بالانس خط دمونتاژ مبتنی بر مدل کانو و روش های تصمیم گیری چند معیاره فازی (مورد مطالعه: خط بازیافت ضایعات الکترونیکی)

نوع مقاله: مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد مدیریت صنعتی، گروه مدیریت صنایع، دانشکده مدیریت و حسابداری، دانشگاه شهید بهشتی، تهران

2 دانشیار، گروه مدیریت صنایع، دانشکده مدیریت و حسابداری، دانشگاه شهید بهشتی، تهران

چکیده

خط دمونتاژ قطعات گزینه مناسبی برای برای کاهش مشکلات زیستمحیطی ناشی از ضایعات تولیدشده است.
هدف مسئله بالانس خط دمونتاژ قطعات، هماهنگ کردن فعالیتهای خط دمونتاژ است به نحوی که کل زمان
لازم در هر یک از ایستگاههای کاری تقریباً یکسان باشد. هدف اصلی فرآیند دمونتاژ قطعات استفاده مجدد از
اجزا و کاهش اثرهای نامطلوب روی محیط زیست است. این مقاله از رویکردی مبتنیی بیر میدل کیانو، تحلییل
سلسله مراتبی فازی، تاپسیس اصیلا شیده ، پرومتیی اسیتفاده کیرده و همینیین بیا بکیارگیری روابیط تقیدمی
AND/OR توالی وظایف را بدست می آورد. وظیفهها بر اساس اولویت و روابط تقدمی به ایستگاهها واگذار
میشوند. مورد مطالعه خط بازیافت با استفاده از هر دو روش تاپسییس اصیلا شیده و پرومتیی میورد بررسیی
قرارگرفته است. هر دو روش نتایج یکسان )کاهش دو ثانیه ای در چرخه( را نشان داده اند. با ایین و جیود روش
پرومتی نسبت به روش تاپسیس اصلا شده، رویه آسان تر ولی فرایند طولانی تری دارد.

کلیدواژه‌ها


عنوان مقاله [English]

Disassembly Line Balancing Based on the Kano Model and Fuzzy MCDM Methods, the Case: e-Waste Recycling Line

نویسندگان [English]

  • Mina Riahee 1
  • Mostafa Zandieh 2
چکیده [English]

Recovering, recycling, and remanufacturing end-of-life products (disassembly line) are appropriate methods of reducing the environmental impact associated with wastes. A disassembly line is a viable option for doing so. The objective of the disassembly line balancing problem (DLBP) is to coordinate disassembly line activities so that total operating times of workstations are nearly equal. The disassembly process mainly aims to reuse components in end-of-life products and thus reduce adverse environmental effects. This paper employs an approach based on the Kano model, Fuzzy AHP, M-TOPSIS, and PROMETHEE. Furthermore, using AND/OR precedence relationships, the optimal sequence of disassembly is obtained. Tasks are assigned to workstations according to priority and precedence relationships. An illustrative example of the proposed method is solved using both M-TOPSIS and PROMETHEE. Both methods lead to a decrease of two seconds in total cycle time. Despite yielding equal results, PROMETHEE is superior to M-TOPSIS in terms of complexity and ease of use. However, it takes longer to complete.

کلیدواژه‌ها [English]

  • Disassembly Line Balancing
  • Precedence Relations
  • Kano Model
  • Fuzzy-AHP
  • M-TOPSIS and PROMETHEE
 

 

 

. راد، ع؛ منصور، س؛XU ، Y وفاطمی، م.(1392) بازیابی تجهیزات الکتریکی و الکترونیکی بر اساس ابعاد محیط زیستی، اقتصادی و اجتماعی توسعه پایدار. تهران، کنفرانس انژری و محیط زیست

 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.

 Altekin F.T., Akkan C. (2011). Task-failure-driven rebalancing of disassembly lines. International Journal of Production Research, 46(10), 1-22

 Altekin F.T., Kandiller L., Ozdemirel N.E. (2008). Profit-oriented disassembly-line balancing. International Journal of Production Research, 46(10), 2675–2693.

 Athawale V.M., Chakraborty S. (2010). Facility Location Selection using PROMETHEE II Method. In Proceedings of the 2010 International Conference on Industrial Engineering and Operations Management, Dhaka, Bangladesh, 78-98.

 Avikal S., Mishra P. K., Jain R. (2013). An AHP and PROMETHEE methods based environ-ment friendly heuristic for disassembly line balancing problems. interdisciplinary environmental review, 14(1), 69–85.

 Avikal S., Mishra P.K., Jain R. (2014). An fuzzy AHP and PROMETHEE methods basedheuristic for disassembly line balancing problems. International Journal of Production Research, 152(5), 1306–1317.

 Bentaha M.L., Battaïa O., Dolgui A. (2014). A Sample Average Approximation Method for Disassembly Line Balancing Problem under Uncertainty. Computers and Operations Research, 51(1), 111–122.

 Bentaha M.L., Battaïa O., Dolgui A. (2014). Disassembly Line Balancing and Sequencing under Uncertainty. Procedia CIRP 15, 239–244.

Bentaha M.L., Battaïa O., Dolgui, A. (2014). Lagrangian Relaxation for Stochastic Disassembly Line Balancing Problem. Procedia CIRP 17, 56–60.

 Berger C., Blauth R., Boger D., Bolster C., Burchill G., DuMouchel W., Pouliot F., Richter R., Rubinoff A., Shen A., Timko M., Walden D. (1993).  Kano’s methods for understanding customer-defined quality, central quality management jornal. 2 (4), 2–36.

 Brucker K. De, Verbeke A., Macharis C. (2004). The applicability of multi-criteria analysis to the evaluation of intelligent transport systems (ITS), research in transportation economics 8, 151–179.

Buckley J.J. (1985). Fuzzy Hierarchical Analysis, Fuzzy Set and Systems. 17, 233–247.

 Chaudha A., Jain R., Singh A.R., Mishra P.K. (2011).  Integration of Kano’s model into quality function deployment (QFD), International Journal of Advanced Manufacturing Technology, 53, 689–698.

 De Brucker K., Verbeke A., Macharis C. (2004). The applicability of multicriteria-analysis to the evaluation of intelligent transport systems (ITS). Research in transportation economics 8(1), 151–179.

 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 problems, Internati

 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 Problems. International Journal of Advanced Manufacturing Technology, 48(1), 761–771.

 Doumpos M., Zopounidis C. (2004). A Multi-criteria Classification Approach Based on Pair-wise Comparison. European Journal of Operational Research, 158(1), 378–389.

 Gungor A., Gupta S.M. (1999). Issues in environmentally conscious manufacturing and product recovery: a survey. Computers and Industrial Engineering, 36(4), 811-853.

 Gungor A., Gupta S.M. (2002). Disassembly line in product recovery. International Journal of Production Research, 40(11), 2569-258

 Gungor. A., Gupta, S.M. (2001). A solution approach to the disassembly line problem in the presence of task failure. International Journal of Production Research, 39(7), 1427-1467.

Gupta S.M., Lambert A.J.D. (2008). Methods for optimum and near optimum disassembly sequencing, International Journal of Production Research, 46 (11) 2845–2865.

 Gupta S.M., Taleb K.N. (1996). An algorithm to disassemble multiple product structures with multiple occurrence of parts. Proceedings of the International Seminar on Reuse, (pp. 153-162). Eindhoven The Netherlands.

 Hajkowicz S., Higgins A. (2008). A Comparison of Multiple Criteria Analysis Techniques for Water Resource Management. European Journal of Operational Research, 184(1), 255–265.

 Homem de Mello, L.S., Sanderson A.C. (1990).  And/or graph representation of assembly plans, IEEE transactions on robotics and automation. 6, 188–199.

 Ilgin M.A., Gupta S.M. (2010). Comparison of economic benefits of sensor embedded products and conventional products in a multi-product disassembly line, Computers and Industrial Engineering, 59 (2010) 748–763.

 Ilgin M.A., Gupta, S.M. (2010). Comparison of economic benefits of sensor embedded products and conventional products in a multi-product disassembly line, Computers and Industrial Engineering, 59, 748–763.

 Kalayc C.B., Gupta S.M. (2011). A hybrid genetic algorithm approach for disassembly line balancing. Proceedings of the 42nd Annual Meeting of Decision Science Institute , Boston, MA, US, 100-111.

 Kalayc C.B., Gupta S.M. (2011). A simulated annealing algorithm for balancing a disassembly line. Proceedings of the Seventh International Symposium on Environmentally Conscious Design and Inverse