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Selecting machines and buffers in unreliable assembly/disassembly manufacturing networks

Author

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  • Nahas, Nabil
  • Nourelfath, Mustapha
  • Gendreau, Michel

Abstract

This paper formulates an optimal design model for assembly/disassembly manufacturing networks. The objective is to maximize production rate subject to a total cost constraint. Machines are chosen from a list of products available on the market, and sizes of the buffers are chosen within a predetermined range. Each machine type is characterized by its total cost of ownership, failure rate, repair rate and processing time. The buffers are also characterized by their total cost of ownership coefficients associated with the buffer size. To estimate assembly/disassembly network performance, a decomposition-type approximation is used. The optimal design model is formulated as a combinatorial optimization one in which the decision variables are buffers and types of machines. A genetic algorithm is proposed as an optimization technique. Numerical examples are used to highlight the benefit of selecting simultaneously the buffers and the machines.

Suggested Citation

  • Nahas, Nabil & Nourelfath, Mustapha & Gendreau, Michel, 2014. "Selecting machines and buffers in unreliable assembly/disassembly manufacturing networks," International Journal of Production Economics, Elsevier, vol. 154(C), pages 113-126.
    • Handle: RePEc:eee:proeco:v:154:y:2014:i:c:p:113-126
    DOI: 10.1016/j.ijpe.2014.04.011
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    References listed on IDEAS

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    1. Staley, Dan R. & Kim, David S., 2012. "Experimental results for the allocation of buffers in closed serial production lines," International Journal of Production Economics, Elsevier, vol. 137(2), pages 284-291.
    2. Michel Gendreau & Alain Hertz & Gilbert Laporte, 1994. "A Tabu Search Heuristic for the Vehicle Routing Problem," Management Science, INFORMS, vol. 40(10), pages 1276-1290, October.
    3. Ouzineb, Mohamed & Nourelfath, Mustapha & Gendreau, Michel, 2008. "Tabu search for the redundancy allocation problem of homogenous series–parallel multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 93(8), pages 1257-1272.
    4. J. MacGregor Smith & Sophia Daskalaki, 1988. "Buffer Space Allocation in Automated Assembly Lines," Operations Research, INFORMS, vol. 36(2), pages 343-358, April.
    5. Shi, Chuan & Gershwin, Stanley B., 2009. "An efficient buffer design algorithm for production line profit maximization," International Journal of Production Economics, Elsevier, vol. 122(2), pages 725-740, December.
    6. Stanley Gershwin & Mitchell Burman, 2000. "A decomposition method for analyzing inhomogeneous assembly/disassembly systems," Annals of Operations Research, Springer, vol. 93(1), pages 91-115, January.
    7. Stanley Gershwin & James Schor, 2000. "Efficient algorithms for buffer space allocation," Annals of Operations Research, Springer, vol. 93(1), pages 117-144, January.
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    Cited by:

    1. Sabry Shaaban & Rodrigo Romero-Silva, 2021. "Performance of merging lines with uneven buffer capacity allocation: the effects of unreliability under different inventory-related costs," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(4), pages 1253-1288, December.
    2. Romero-Silva, Rodrigo & Shaaban, Sabry & Marsillac, Erika & Laarraf, Zouhair, 2021. "The impact of unequal processing time variability on reliable and unreliable merging line performance," International Journal of Production Economics, Elsevier, vol. 235(C).
    3. Andrea Bacchetti & Stefano Bonetti & Marco Perona & Nicola Saccani, 2018. "Investment and Management Decisions in Aluminium Melting: A Total Cost of Ownership Model and Practical Applications," Sustainability, MDPI, vol. 10(9), pages 1-36, September.
    4. Guan Wang & Yang Woo Shin & Dug Hee Moon, 2016. "Comparison of three flow line layouts with unreliable machines and profit maximization," Flexible Services and Manufacturing Journal, Springer, vol. 28(4), pages 669-693, December.
    5. Liang, Wei & Zhang, Zeqiang & Yin, Tao & Zhang, Yu & Wu, Tengfei, 2023. "Modelling and optimisation of energy consumption and profit-oriented multi-parallel partial disassembly line balancing problem," International Journal of Production Economics, Elsevier, vol. 262(C).

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