Statistical testing quality and its Monte Carlo simulation based on fuzzy specification limits
نویسندگان
1 Department of Statistics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, Iran
2 Department of Statistics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, Iran
3 Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran
doi
10.22111/ijfs.2022.6940چکیده
This paper presents two approaches for testing quality to make adecision based on the extended process capability indices. Common methodsin measuring quality of the manufactured product have widely focused on theprecise specification limits, but in this study the lower and upper specificationlimits are considered as non-precise/fuzzy sets. Based on a general statistical approach using an extended process capability index, the purpose of this study is estimating a critical value to determine whether the process meets the customer requirements. Moreover, a simulation approach to analyze the manufacturing process capability has been suggested for testing quality based on fuzzy specifications by normal data. Meanwhile, this paper discusses howwell the Monte Carlo simulation approach can be used for non-normal data.Finally, the real application of the proposed methods is investigated in a realcase study.
