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Definition of FTL with bypass lines and its simulator for buffer size decision

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  • Yamamoto, Hidehiko
  • Abu Qudeiri, Jaber
  • Marui, Etsuo

Abstract

The production engineer's decision regarding buffer size in a flexible transfer line with bypass lines (FTL-B) is one of the most important factors in maximizing production efficiency and minimizing production cost. In this paper, we define FTL-B. According to the definition, we propose a new gene arrangement, referred to as the multiple distribution method (MDM). We also present a production simulator system (PSS) which consists of a genetic algorithm (GA) system and a discrete simulator to decide a buffer size for any FTL-B. An application example was developed and after a number of operations based on the GA system and discrete simulator, the sizes of all buffers for the FTL-B could be determined. The results of the study can be used to improve the production plant and production engineers can use the results in their decisions for buffer size when they develop the FTL-B.

Suggested Citation

  • Yamamoto, Hidehiko & Abu Qudeiri, Jaber & Marui, Etsuo, 2008. "Definition of FTL with bypass lines and its simulator for buffer size decision," International Journal of Production Economics, Elsevier, vol. 112(1), pages 18-25, March.
    • Handle: RePEc:eee:proeco:v:112:y:2008:i:1:p:18-25
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    References listed on IDEAS

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    1. Frederick S. Hillier & Kut C. So & Ronald W. Boling, 1993. "Notes: Toward Characterizing the Optimal Allocation of Storage Space in Production Line Systems with Variable Processing Times," Management Science, INFORMS, vol. 39(1), pages 126-133, January.
    2. C Alabas & F Altiparmak & B Dengiz, 2002. "A comparison of the performance of artificial intelligence techniques for optimizing the number of kanbans," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(8), pages 907-914, August.
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    Cited by:

    1. Federico Nuñez-Piña & Joselito Medina-Marin & Juan Carlos Seck-Tuoh-Mora & Norberto Hernandez-Romero & Eva Selene Hernandez-Gress, 2018. "Modeling of Throughput in Production Lines Using Response Surface Methodology and Artificial Neural Networks," Complexity, Hindawi, vol. 2018, pages 1-10, January.
    2. Ramli, Rizauddin & Yamamoto, Hidehiko & Qudeiri, Jaber Abu, 2009. "Tool path of lathe machine in flexible transfer lines by using genetic algorithms," International Journal of Production Economics, Elsevier, vol. 121(1), pages 72-80, September.
    3. Bertazzi, Luca, 2011. "Determining the optimal dimension of a work-in-process storage area," International Journal of Production Economics, Elsevier, vol. 131(2), pages 483-489, June.

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