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    Manufacturing System Design Considering Stochastic Product Evolution and Task Recurrence

    Source: Journal of Manufacturing Science and Engineering:;2009:;volume( 131 ):;issue: 005::page 51012
    Author:
    Jeonghan Ko
    ,
    S. Jack Hu
    DOI: 10.1115/1.4000095
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The conventional approaches to manufacturing system design and line balancing have often focused on a single generation of products, thus leading to new design or rebalancing when new products are introduced or different models are produced in the same line. As the life cycles of product models become shorter and shorter, this new product then new system-design approach is becoming increasingly ineffective due to too frequent production interruption. Therefore, effective solutions to system-design problems should consider the evolution of products over multiple generations and models, and this paper presents such new methods. Mixed-integer programming models are developed for (1) designing manufacturing system configurations that are cost effective for product evolution involving uncertainty and (2) maximizing the recurrences of manufacturing tasks on the same machines throughout product evolution. A decomposition-based solution procedure is also developed to reduce computational complexity. These new methods can provide a stable system-design solution enabling quick product launches with less line change-over for new or different products.
    keyword(s): Machinery , Manufacturing , Design , Optimization , Manufacturing systems , Cycles AND Uncertainty ,
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      Manufacturing System Design Considering Stochastic Product Evolution and Task Recurrence

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    http://yetl.yabesh.ir/yetl1/handle/yetl/141191
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    contributor authorJeonghan Ko
    contributor authorS. Jack Hu
    date accessioned2017-05-09T00:34:02Z
    date available2017-05-09T00:34:02Z
    date copyrightOctober, 2009
    date issued2009
    identifier issn1087-1357
    identifier otherJMSEFK-28235#051012_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/141191
    description abstractThe conventional approaches to manufacturing system design and line balancing have often focused on a single generation of products, thus leading to new design or rebalancing when new products are introduced or different models are produced in the same line. As the life cycles of product models become shorter and shorter, this new product then new system-design approach is becoming increasingly ineffective due to too frequent production interruption. Therefore, effective solutions to system-design problems should consider the evolution of products over multiple generations and models, and this paper presents such new methods. Mixed-integer programming models are developed for (1) designing manufacturing system configurations that are cost effective for product evolution involving uncertainty and (2) maximizing the recurrences of manufacturing tasks on the same machines throughout product evolution. A decomposition-based solution procedure is also developed to reduce computational complexity. These new methods can provide a stable system-design solution enabling quick product launches with less line change-over for new or different products.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleManufacturing System Design Considering Stochastic Product Evolution and Task Recurrence
    typeJournal Paper
    journal volume131
    journal issue5
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.4000095
    journal fristpage51012
    identifier eissn1528-8935
    keywordsMachinery
    keywordsManufacturing
    keywordsDesign
    keywordsOptimization
    keywordsManufacturing systems
    keywordsCycles AND Uncertainty
    treeJournal of Manufacturing Science and Engineering:;2009:;volume( 131 ):;issue: 005
    contenttypeFulltext
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