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Operational Performance Evaluation Model for Food Processing Machinery Industry Chain

Author

Listed:
  • Huiqi Zhang

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100091, China)

  • Kuen-Suan Chen

    (Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 411030, Taiwan
    Department of Business Administration, Chaoyang University of Technology, Taichung 413310, Taiwan
    Department of Business Administration, Asia University, Taichung 413305, Taiwan)

  • Chun-Min Yu

    (Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung 411030, Taiwan)

  • Qiansha Zhang

    (School of Business Administration, Guangxi University of Finance and Economics, Nanning 530007, China)

  • Wei Lo

    (School of Business Administration, Guangxi University of Finance and Economics, Nanning 530007, China)

Abstract

This study aims to create a performance evaluation model for the food processing machinery industry. The goal is to help food processing plants improve both process quality and competitiveness. Additionally, component failures may disrupt the continuous operation of the food processing machine, potentially resulting in insufficient production and delays in delivery, which in turn leads to cost losses. For the sold food processing machinery, decreases in the average number of failures within a unit of time, the average repair response time when a failure occurs, and the average repair duration are three crucial factors in minimizing the total expected loss due to machine failures. Based on these three important factors, this study established the following evaluation indices: (1) the processing performance index, (2) the repair reporting performance index, and (3) the maintenance performance index. These indices serve as tools for assessing the performance of the three key operational aspects. This study employed a radar chart to construct the evaluation model, which can directly compare the critical values with the point estimates of three indices. Consequently, this approach can judge whether the operational performance has achieved the required level. This can maintain the simplicity and usability of point estimates while reducing the risk of misjudgment due to sampling errors.

Suggested Citation

  • Huiqi Zhang & Kuen-Suan Chen & Chun-Min Yu & Qiansha Zhang & Wei Lo, 2024. "Operational Performance Evaluation Model for Food Processing Machinery Industry Chain," Mathematics, MDPI, vol. 12(21), pages 1-11, October.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:21:p:3361-:d:1507296
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    References listed on IDEAS

    as
    1. Oh, Eun-Teak & Chen, Kuo-Min & Wang, Lu-Mei & Liu, Ren-Jye, 2015. "Value creation in regional innovation systems: The case of Taiwan's machine tool enterprises," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 118-129.
    2. Canbolat, Pelin G., 2020. "Bounded rationality in clearing service systems," European Journal of Operational Research, Elsevier, vol. 282(2), pages 614-626.
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