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    A neuro-genetic approach to design and planning of a manufacturing cell

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    Peer reviewed article (185.4Kb)
    Date
    2005
    Author
    Cakar, Tarik
    Yildirim, Mehmet Bayram
    Barut, Mehmet
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    Abstract
    In this paper, we propose a neuro-genetic decision support system coupled with simulation to design a job shop manufacturing system by achieving predetermined values of targeted performance measures such as flow time, number of tardy jobs, total tardiness and machine utilization at each work center. When a manufacturing system is designed, the management has to make decisions on the availability of resources or capacity, in our setting, the number of identical machines in each work station and the dispatching rule to be utilized in the shop floor to achieve performance values desired. Four different priority rules are used as Earliest due date (EDD), Shortest Processing Time (SPT), Critical ratio (CR) and First Come First Serve (FCFS). In reaching the final decision, design alternatives obtained from the proposed system are evaluated in terms of performance measures. An illustrative example is provided to explain the procedure.
    Description
    The full text of this article is not available on SOAR. WSU users can access the article via commercial databases licensed by University Libraries: http://libcat.wichita.edu/vwebv/holdingsInfo?bibId=1379503
    URI
    http://hdl.handle.net/10057/3447
    http://dx.doi.org/10.1007/s10845-005-1657-2
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