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    Supervisory Factory Control Based on Real-Time Production Feedback

    Source: Journal of Manufacturing Science and Engineering:;2007:;volume( 129 ):;issue: 003::page 653
    Author:
    Qing Chang
    ,
    Jun Ni
    ,
    Pulak Bandyopadhyay
    ,
    Stephan Biller
    ,
    Guoxian Xiao
    DOI: 10.1115/1.2673666
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: One key characteristic of any process performance is variability; that is, a process rarely performs consistently over time. The bottleneck is one of the main reasons causing the system variability and fluctuation in production. Short-term production analysis and short-term bottleneck identification are imperative to enable manufacturing operations to optimally respond to dynamic changes in system behavior. However, conventional throughput and bottleneck analysis focus on long-term statistic bottleneck identification, which is usually not applicable to a short-term period. An on-line supervisory control method is introduced to search for short-term production constraints with unknown machine reliability distribution and mitigate those constraints to improve system throughput. The control mechanism uses playback simulation of the real production data to identify the bottleneck station, and control parameters of that station to reach a near balanced production line operation by understanding the bottleneck inertia phenomenon. The results ensure the smooth flow of products on the production line and increase the line’s performance.
    keyword(s): Assembly lines , Maintenance , Polishing equipment , Feedback , Machinery , Manufacturing systems , Cycles , Simulation , Failure AND Manufacturing ,
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      Supervisory Factory Control Based on Real-Time Production Feedback

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    http://yetl.yabesh.ir/yetl1/handle/yetl/136316
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    contributor authorQing Chang
    contributor authorJun Ni
    contributor authorPulak Bandyopadhyay
    contributor authorStephan Biller
    contributor authorGuoxian Xiao
    date accessioned2017-05-09T00:24:47Z
    date available2017-05-09T00:24:47Z
    date copyrightJune, 2007
    date issued2007
    identifier issn1087-1357
    identifier otherJMSEFK-28004#653_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/136316
    description abstractOne key characteristic of any process performance is variability; that is, a process rarely performs consistently over time. The bottleneck is one of the main reasons causing the system variability and fluctuation in production. Short-term production analysis and short-term bottleneck identification are imperative to enable manufacturing operations to optimally respond to dynamic changes in system behavior. However, conventional throughput and bottleneck analysis focus on long-term statistic bottleneck identification, which is usually not applicable to a short-term period. An on-line supervisory control method is introduced to search for short-term production constraints with unknown machine reliability distribution and mitigate those constraints to improve system throughput. The control mechanism uses playback simulation of the real production data to identify the bottleneck station, and control parameters of that station to reach a near balanced production line operation by understanding the bottleneck inertia phenomenon. The results ensure the smooth flow of products on the production line and increase the line’s performance.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleSupervisory Factory Control Based on Real-Time Production Feedback
    typeJournal Paper
    journal volume129
    journal issue3
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.2673666
    journal fristpage653
    journal lastpage660
    identifier eissn1528-8935
    keywordsAssembly lines
    keywordsMaintenance
    keywordsPolishing equipment
    keywordsFeedback
    keywordsMachinery
    keywordsManufacturing systems
    keywordsCycles
    keywordsSimulation
    keywordsFailure AND Manufacturing
    treeJournal of Manufacturing Science and Engineering:;2007:;volume( 129 ):;issue: 003
    contenttypeFulltext
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