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    Co-Optimization of Supply Chain Reconfiguration and Assembly Process Planning for Factory-in-a-Box Manufacturing

    Source: Journal of Manufacturing Science and Engineering:;2022:;volume( 144 ):;issue: 010::page 101006-1
    Author:
    Nwodu
    ,
    Arriana;Pasha
    ,
    Junayed;Jiang
    ,
    Zhengqian;Guo
    ,
    Weihong;Dulebenets
    ,
    Maxim;Wang
    ,
    Hui;Minor
    ,
    Kayla
    DOI: 10.1115/1.4054519
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Factory in a box (FiB) is an emerging technology that meets the dynamic and diverse market demand by carrying a factory module on vehicles to perform on-site production near customers’ locations. It is suitable for meeting time-sensitive demands, such as the outbreak of disasters or epidemics/pandemics. Compared to traditional manufacturing, FiB poses a new challenge of frequently reconfiguring supply chain networks since the final production location changes as the vehicle carrying the factory travels. Supply chain network reconfiguration involves decisions regarding whether suppliers or manufacturers can be retained in the supply chain or replaced. Such a supply chain reconfiguration problem is coupled with manufacturing process planning, which assigns tasks to each manufacturer that impacts material flow in the supply chain network. Considering the supply chain reconfigurability, this article develops a new mathematical model based on nonlinear integer programming to optimize supply chain reconfiguration and assembly planning jointly. An evolutionary algorithm (EA) is developed and customized to the joint optimization of process planning and supplier/manufacturer selection. The performance of EA is verified with a nonlinear solver for a relaxed version of the problem. A case study on producing a medical product demonstrates the methodology in guiding supply chain reconfiguration and process planning as the final production site relocates in response to local demands. The methodology can be potentially generalized to supply chain and service process planning for a mobile hospital offering on-site medical services.
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      Co-Optimization of Supply Chain Reconfiguration and Assembly Process Planning for Factory-in-a-Box Manufacturing

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    contributor authorNwodu
    contributor authorArriana;Pasha
    contributor authorJunayed;Jiang
    contributor authorZhengqian;Guo
    contributor authorWeihong;Dulebenets
    contributor authorMaxim;Wang
    contributor authorHui;Minor
    contributor authorKayla
    date accessioned2022-08-18T13:01:21Z
    date available2022-08-18T13:01:21Z
    date copyright5/25/2022 12:00:00 AM
    date issued2022
    identifier issn1087-1357
    identifier othermanu_144_10_101006.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4287283
    description abstractFactory in a box (FiB) is an emerging technology that meets the dynamic and diverse market demand by carrying a factory module on vehicles to perform on-site production near customers’ locations. It is suitable for meeting time-sensitive demands, such as the outbreak of disasters or epidemics/pandemics. Compared to traditional manufacturing, FiB poses a new challenge of frequently reconfiguring supply chain networks since the final production location changes as the vehicle carrying the factory travels. Supply chain network reconfiguration involves decisions regarding whether suppliers or manufacturers can be retained in the supply chain or replaced. Such a supply chain reconfiguration problem is coupled with manufacturing process planning, which assigns tasks to each manufacturer that impacts material flow in the supply chain network. Considering the supply chain reconfigurability, this article develops a new mathematical model based on nonlinear integer programming to optimize supply chain reconfiguration and assembly planning jointly. An evolutionary algorithm (EA) is developed and customized to the joint optimization of process planning and supplier/manufacturer selection. The performance of EA is verified with a nonlinear solver for a relaxed version of the problem. A case study on producing a medical product demonstrates the methodology in guiding supply chain reconfiguration and process planning as the final production site relocates in response to local demands. The methodology can be potentially generalized to supply chain and service process planning for a mobile hospital offering on-site medical services.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleCo-Optimization of Supply Chain Reconfiguration and Assembly Process Planning for Factory-in-a-Box Manufacturing
    typeJournal Paper
    journal volume144
    journal issue10
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.4054519
    journal fristpage101006-1
    journal lastpage101006-13
    page13
    treeJournal of Manufacturing Science and Engineering:;2022:;volume( 144 ):;issue: 010
    contenttypeFulltext
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