Fuzzy Evaluation Model for Operational Performance of Air Cleaning Equipment  
Author Chun-Min Yu


Co-Author(s) Kuen-Suan Chen; Chi-Han Chen; Yi-Xuan Chen


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. Therefore, the main purpose of this industry-university research project is to propose a comprehensive model for evaluating, analyzing and improving the operational performance of the air cleaning equipment. Firstly, three operational performance evaluation indexes, such as the number of dust particles, the number of colonies, and microorganisms, are established, and their characteristics are discussed. Secondly, the 100(1 − α )% upper confidence limits of these three operational performance evaluation indexes are deduced to construct a fuzzy testing model. Meanwhile, the accumulated value of φ is used to derive the evaluation decisionmaking value. Finally, the evaluation decision-making values and the index requirement values of the three operational performance evaluation indicators are collected and mapped on the radar chart to form a fuzzy radar evaluation chart for the operational performance of the air cleaning equipment. Since the fuzzy radar evaluation chart can control these three operational performance indexes at the same time, it is very convenient to manage and easy to promote. The model proposed by this project can help companies identify the key quality characteristics that need to be improved. At the same time, we cooperate with the engineers of the partner manufacturers to analyze the reasons for poor performance based on the evaluation data, propose improvement strategies, and accumulate improvement experience to form a knowledge base for intelligent improvement. 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.


Keywords Operational performance evaluation index; Upper confidence limit; Fuzzy testing model; Fuzzy radar evaluation chart; Sustainable development.
    Article #:  RQD28-80

Proceedings of 28th ISSAT International Conference on Reliability & Quality in Design
August 3-5, 2023