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    End-of-Life Decision Making With Uncertain Product Return Quantity

    Source: Journal of Mechanical Design:;2012:;volume( 134 ):;issue: 010::page 100902
    Author:
    Sara Behdad
    ,
    Deborah Thurston
    ,
    Aida Sefic Williams
    DOI: 10.1115/1.4007394
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The management of end-of-life electronic waste (e-waste) attracts significant attention due to environmental concerns, legislative requirements, consumer interest in green products, and the market image of manufacturers. However, managing e-waste is complicated by several factors, including the high degree of uncertainty of quantity, timing of arrival, and quality of the returned products. This variability in the stream of returned end-of-life (EOL) products makes it difficult to plan for remanufacturing facility materials, equipment, and human resource requirements. The aim of this research is to tackle the uncertainty associated with the quantity of received used products. A stochastic programming model for waste stream acquisition systems (as opposed to market-driven systems) is introduced. The model considers the quantity of returned product as an uncertain parameter and determines to what extent the product should be disassembled and what is the best EOL option for each subassembly. The stochastic model is defined in a form of chance constrained programming and is then converted to a mixed integer linear programming. An example is provided to illustrate the application of the model for an uncertain stream of PCs (minus monitor and keyboard) received in a PC refurbishing company. The remanufacturer must then decide which proportion of disassembled modules should be processed given specific remanufacturing options.
    keyword(s): Decision making , Stochastic programming , Computer programming , Uncertainty , Integer programming AND Model development ,
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      End-of-Life Decision Making With Uncertain Product Return Quantity

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    http://yetl.yabesh.ir/yetl1/handle/yetl/149724
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    contributor authorSara Behdad
    contributor authorDeborah Thurston
    contributor authorAida Sefic Williams
    date accessioned2017-05-09T00:53:02Z
    date available2017-05-09T00:53:02Z
    date copyrightOctober, 2012
    date issued2012
    identifier issn1050-0472
    identifier otherJMDEDB-926069#100902_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/149724
    description abstractThe management of end-of-life electronic waste (e-waste) attracts significant attention due to environmental concerns, legislative requirements, consumer interest in green products, and the market image of manufacturers. However, managing e-waste is complicated by several factors, including the high degree of uncertainty of quantity, timing of arrival, and quality of the returned products. This variability in the stream of returned end-of-life (EOL) products makes it difficult to plan for remanufacturing facility materials, equipment, and human resource requirements. The aim of this research is to tackle the uncertainty associated with the quantity of received used products. A stochastic programming model for waste stream acquisition systems (as opposed to market-driven systems) is introduced. The model considers the quantity of returned product as an uncertain parameter and determines to what extent the product should be disassembled and what is the best EOL option for each subassembly. The stochastic model is defined in a form of chance constrained programming and is then converted to a mixed integer linear programming. An example is provided to illustrate the application of the model for an uncertain stream of PCs (minus monitor and keyboard) received in a PC refurbishing company. The remanufacturer must then decide which proportion of disassembled modules should be processed given specific remanufacturing options.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleEnd-of-Life Decision Making With Uncertain Product Return Quantity
    typeJournal Paper
    journal volume134
    journal issue10
    journal titleJournal of Mechanical Design
    identifier doi10.1115/1.4007394
    journal fristpage100902
    identifier eissn1528-9001
    keywordsDecision making
    keywordsStochastic programming
    keywordsComputer programming
    keywordsUncertainty
    keywordsInteger programming AND Model development
    treeJournal of Mechanical Design:;2012:;volume( 134 ):;issue: 010
    contenttypeFulltext
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