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A credit-based dynamical evaluation method for the smart configuration of manufacturing services under Industrial Internet of Things

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  • Wang Shijie

    (Northwestern Polytechnical University)

  • Zhang Yingfeng

    (Northwestern Polytechnical University)

Abstract

Most scheduling problems are required to follow rigid metrics, such as the maximum completion time, earliest deadline first, etc., ignoring the flexibility of manufacturing services (MSs) and the effects of their historical data hidden in millions of manufacturing activities. The historical data serves as a powerful basis for describing the comprehensiveness or credibility of the MS itself with the help of Industrial IoT enabling all equipment to communicate and take preventive actions. Similar to the bank credit for individuals, MSs should also have their own referential credit values when choosing the most suitable service for a specific manufacturing task. This paper summarizes the MS attributes from six aspects with sufficient sub-attributes. The fuzzy Analytic Network Process combined with the Cross-Entropy method is employed to evaluate the credit of MSs in the complex manufacturing network system. Such service scoring mechanism (SSM) can personify a comprehensive credit evaluation of services, where, a smart service configuration mode based on credit is proposed for carrying out the supply–demand matching with the help of the data-security technology. Subsequently, a credit-based manufacturing mode is derived under SSM. Numerical examples are carried out to demonstrate the validity of the matching mode. The result may assist manufacturers to allocate their manufacturing tasks in real time in a “credit” way and make quicker decisions in exceptional circumstances, while making the chosen service truly competent enough to finish the work, so as to further improve the customer satisfaction.

Suggested Citation

  • Wang Shijie & Zhang Yingfeng, 2021. "A credit-based dynamical evaluation method for the smart configuration of manufacturing services under Industrial Internet of Things," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 1091-1115, April.
    • Handle: RePEc:spr:joinma:v:32:y:2021:i:4:d:10.1007_s10845-020-01604-y
    DOI: 10.1007/s10845-020-01604-y
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    References listed on IDEAS

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