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Fuzzy Evaluation Model for Operational Performance of Air Cleaning Equipment

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  • 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)

  • Tsun-Hung Huang

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

  • Chun-Min Yu

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

  • Hui-E Lee

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

Abstract

Global warming has led to the continuous deterioration of the living environment, in which air quality directly affects human health. In addition, the severity of the COVID-19 pandemic has further increased the attention to indoor air quality. Indoor clean air quality is not only related to human health but also related to the quality of the manufacturing environment of clean rooms for numerous high-tech processes, such as semiconductors and packaging. This paper proposes a comprehensive model for evaluating, analyzing, and improving the operational performance of air cleaning equipment. Firstly, three operational performance evaluation indexes, such as the number of dust particles, the number of colonies, and microorganisms, were established. Secondly, the 100(1 − α )% upper confidence limits of these three operational performance evaluation indexes were deduced to construct a fuzzy testing model. Meanwhile, the accumulated value of ϕ was used to derive the evaluation decision-making value. The proposed model can help companies identify the key quality characteristics that need to be improved. Furthermore, the competitiveness of cooperative enterprises towards smart manufacturing can be strengthened, so that enterprises can not only fulfill their social responsibilities while developing the economy but also take into account the sustainable development of enterprises and the environment.

Suggested Citation

  • Kuen-Suan Chen & Tsun-Hung Huang & Chun-Min Yu & Hui-E Lee, 2024. "Fuzzy Evaluation Model for Operational Performance of Air Cleaning Equipment," Mathematics, MDPI, vol. 12(17), pages 1-12, August.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:17:p:2630-:d:1463434
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    References listed on IDEAS

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    1. Chirumalla, Koteshwar, 2021. "Building digitally-enabled process innovation in the process industries: A dynamic capabilities approach," Technovation, Elsevier, vol. 105(C).
    2. Bhatia, Purvee & Diaz-Elsayed, Nancy, 2023. "Facilitating decision-making for the adoption of smart manufacturing technologies by SMEs via fuzzy TOPSIS," International Journal of Production Economics, Elsevier, vol. 257(C).
    3. Kuen-Suan Chen, 2022. "Fuzzy testing of operating performance index based on confidence intervals," Annals of Operations Research, Springer, vol. 311(1), pages 19-33, April.
    4. Kuo-Ching Chiou, 2023. "Building Up of Fuzzy Evaluation Model of Life Performance Based on Type-II Censored Data," Mathematics, MDPI, vol. 11(17), pages 1-12, August.
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