Modern Manufacturing Engineering ›› 2018, Vol. 450 ›› Issue (3): 5-10.doi: 10.16731/j.cnki.1671-3133.2018.03.002

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Statistical process control of carbon footprint with Bayesian theory

Wang Xiuzi1,Li Renwang1,Cao Yanlong2,Chen Kunchang1   

  1. 1 Faculty of Mechanical Engineering & Automation,Zhejiang Sci-Tech University,Hangzhou 310018,China;
    2 College of Mechanical Engineering,Zhejiang University,Hangzhou 310027,China
  • Received:2016-11-28 Online:2018-03-20 Published:2018-07-19

Abstract: On the basis of Manufacturing Execution System (MES),the carbon footprint in the process of manufacturing workshop is researched and the calculation method of carbon emissions at the station level is proposed.In order to realize the real-time monitoring of carbon footprint at the station level,the carbon emissions is regarded as an important quality characteristics of statistical process control,and the statistical process control model of carbon footprint based on the Bayesian theory is puted forward.The model is applied to the MES of a instrument manufacturing enterprise and the effectiveness is demonstrated.

Key words: job shop, carbon footprint at the station level, Bayesian theory, statistical process control, real-time monitoring

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