Integrated procedure of balancing and sequencing for mixed-model assembly lines: A multi-objective evolutionary approach

Reakook Hwang, Hiroshi Katayama

    Research output: Contribution to journalArticle

    28 Citations (Scopus)

    Abstract

    A mixed-model assembly line is a type of production line which is used to assemble a variety of product models with a certain level of similarity in operational characteristics. This variety causes workload variance among other problems resulting in low efficiency and line stops. To cope with these problems, a hierarchical design procedure for line balancing and model sequencing is proposed. It is structured in terms of an amelioration procedure. On the basis of our evolutionary algorithm, a genetic encoding procedure entitled priority-based multi-chromosome (PMC) is proposed. It features a multi-functional chromosome and provides efficient representation of task assignment to workstations and model sequencing. The lean production perspective recognises the U-shape assembly line system as more advanced and beneficial compared to the traditional straight line system. To assure the effectiveness of the proposed procedure, both straight and U-shape assembly lines are examined under two major performance criteria, i.e., number of workstations (or line efficiency) as static criterion and variance of workload (line and models) as dynamic criterion. The results of simulation experiments suggest that the proposed procedure is an effective management tool of a mixed-model assembly line system.

    Original languageEnglish
    Pages (from-to)6417-6441
    Number of pages25
    JournalInternational Journal of Production Research
    Volume48
    Issue number21
    DOIs
    Publication statusPublished - 2010 Nov 1

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    Keywords

    • genetic algorithm
    • job sequencing
    • line balancing
    • mixed-model assembly lines
    • priority-based multi-chromosome

    ASJC Scopus subject areas

    • Industrial and Manufacturing Engineering
    • Management Science and Operations Research
    • Strategy and Management

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