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An improved genetic algorithm for the machine-part cell formation problem

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  • Manash Hazarika

    (Assam Engineering College)

Abstract

Cellular manufacturing system (CMS) deals with the set of procedures used by the company to drive the production facilities and to manage production efficiently by solving the technical and logistic problems encountered in the factory, and ensuring that products meet quality standards. The CMS is well thought-out as an efficient production approach to make batch manufacturing as efficient and productive as possible. The CMS relies on the theory of group technology (GT) for grouping dissimilar machines in machine cells and grouping parts into part families to take the benefit of their similarities in design and production process. It reduce total intercellular pass as well as to make the most of the number of operations within a machine cell. This paper presents a meta-heuristic genetic algorithm to resolve machine cell formation problem (CFP) in CMS and paying concentration on maximizing grouping efficacy (GC) by reducing outside elements and void elements in diagonal blocks. Computational work was carried out on 36 standard problems from the literature. The outcome confirms that the proposed meta-heuristic in terms of GC has shown to produce solutions are either enhanced or aggressive with other accessible algorithms.

Suggested Citation

  • Manash Hazarika, 2023. "An improved genetic algorithm for the machine-part cell formation problem," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 206-219, February.
    • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:1:d:10.1007_s13198-021-01615-9
    DOI: 10.1007/s13198-021-01615-9
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    References listed on IDEAS

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    4. Hachicha, Wafik & Masmoudi, Faouzi & Haddar, Mohamed, 2006. "Formation of machine groups and part families in cellular manufacturing systems using a correlation analysis approach," MPRA Paper 3975, University Library of Munich, Germany, revised 04 Jan 2007.
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