Statistical testing quality and its Monte Carlo simulation based on fuzzy specification limits

Authors

1 Department of Statistics, Faculty of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, Iran

2 Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran

Abstract

This paper presents two approaches for testing quality to make a
decision based on the extended process capability indices. Common methods
in measuring quality of the manufactured product have widely focused on the
precise specification limits, but in this study the lower and upper specification
limits 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 how
well the Monte Carlo simulation approach can be used for non-normal data.
Finally, the real application of the proposed methods is investigated in a real
case study.