Fuzzy Testing Method of Process Incapability Index

Author:

Chen Kuen-Suan123,Huang Tsun-Hung1,Lin Jin-Shyong4,Kao Wen-Yang5,Lo Wei6

Affiliation:

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

2. Department of Business Administration, Chaoyang University of Technology, Taichung 413310, Taiwan

3. Department of Business Administration, Asia University, Taichung 413305, Taiwan

4. Department of Mechanical Engineering, National Chin-Yi University of Technology, Taichung 411030, Taiwan

5. Office of Physical Education, National Chin-Yi University of Technology, Taichung 411030, Taiwan

6. School of Business Administration, Guangxi University of Finance and Economics, Nanning 530007, China

Abstract

The process capability index is a tool for quality measurement and analysis widely used in the industry. It is also a good tool for the sales department to communicate with customers. Although the value of the process capability index can be affected by the accuracy and precision of the process, the index itself cannot be differentiated. Therefore, the process incapability index is directly divided into two items, accuracy and precision, based on the expected value of the Taguchi process loss function. In fact, accuracy and precision are two important reference items for improving the manufacturing process. Thus, the process incapability index is good for evaluating process quality. The process incapability index contains two unknown parameters, so it needs to be estimated with sample data. Since point estimates are subject to misjudgment incurred by the inaccuracy of sampling, and since modern businesses are in the era of rapid response, the size of sampling usually tends to be small. A number of studies have suggested that a fuzzy testing method built on the confidence interval be adopted at this time because it integrates experts and the experience accumulated in the past. In addition to a decrease in the possibility of misjudgment resulting from sampling error, this method can improve the test accuracy. Therefore, based on the confidence interval of the process incapability index, we proposed the fuzzy testing method to assess whether the process capability can attain a necessary level of quality. If the quality level fails to meet the requirement, then an improvement must be made. If the quality level exceeds the requirement, then it is equivalent to excess quality, and a resource transfer must be considered to reduce costs.

Funder

Guangxi Philosophy and Social Sciences Research Project

National Natural Science Foundation of China

Publisher

MDPI AG

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