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    Flexible Job-Shop Scheduling for Reduced Manufacturing Carbon Footprint

    Source: Journal of Manufacturing Science and Engineering:;2018:;volume( 140 ):;issue: 006::page 61006
    Author:
    Liu, Qiong
    ,
    Tian, Youquan
    ,
    Wang, Chao
    ,
    Chekem, Freddy O.
    ,
    Sutherland, John W.
    DOI: 10.1115/1.4037710
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In order to help manufacturing companies quantify and reduce product carbon footprints in a mixed model manufacturing system, a product carbon footprint-oriented multi-objective flexible job-shop scheduling optimization model is proposed. The production portion of the product carbon footprint, based on the mapping relations between products and the carbon emissions within the manufacturing system, is proposed to calculate the product carbon footprint in the mixed model manufacturing system. Nondominated sorting genetic algorithm-II (NSGA-II) is adopted to solve the proposed model. In order to help decision makers to choose the most suitable solution from the Pareto set as its execution solution, a method based on grades of product carbon footprints is proposed. Finally, the efficacy of the proposed model and algorithm are examined via a case study.
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      Flexible Job-Shop Scheduling for Reduced Manufacturing Carbon Footprint

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4252022
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    contributor authorLiu, Qiong
    contributor authorTian, Youquan
    contributor authorWang, Chao
    contributor authorChekem, Freddy O.
    contributor authorSutherland, John W.
    date accessioned2019-02-28T11:02:34Z
    date available2019-02-28T11:02:34Z
    date copyright3/13/2018 12:00:00 AM
    date issued2018
    identifier issn1087-1357
    identifier othermanu_140_06_061006.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4252022
    description abstractIn order to help manufacturing companies quantify and reduce product carbon footprints in a mixed model manufacturing system, a product carbon footprint-oriented multi-objective flexible job-shop scheduling optimization model is proposed. The production portion of the product carbon footprint, based on the mapping relations between products and the carbon emissions within the manufacturing system, is proposed to calculate the product carbon footprint in the mixed model manufacturing system. Nondominated sorting genetic algorithm-II (NSGA-II) is adopted to solve the proposed model. In order to help decision makers to choose the most suitable solution from the Pareto set as its execution solution, a method based on grades of product carbon footprints is proposed. Finally, the efficacy of the proposed model and algorithm are examined via a case study.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleFlexible Job-Shop Scheduling for Reduced Manufacturing Carbon Footprint
    typeJournal Paper
    journal volume140
    journal issue6
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.4037710
    journal fristpage61006
    journal lastpage061006-9
    treeJournal of Manufacturing Science and Engineering:;2018:;volume( 140 ):;issue: 006
    contenttypeFulltext
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