A general p-value-based approach for testing quality by considering fuzzy hypotheses

被引:3
|
作者
Parchami, Abbas [1 ]
Gildeh, Bahram Sadeghpour [2 ]
Taheri, S. Mahmoud [3 ]
Mashinchi, Mashaallah [1 ]
机构
[1] Shahid Bahonar Univ Kerman, Fac Math & Comp, Dept Stat, Kerman, Iran
[2] Ferdowsi Univ Mashhad, Fac Math Sci, Dept Stat, Mashhad, Iran
[3] Univ Tehran, Coll Engn, Fac Engn Sci, Tehran, Iran
关键词
Boundary of fuzzy hypothesis; weighted density; Taguchi capability index; maximum likelihood estimator; PROCESS CAPABILITY INDEXES; PROBABILITY; DECISION;
D O I
10.3233/JIFS-141680
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In testing the capability of industrial processes, the researcher considers and tests the vague hypothesis "the capability index is low"against the vague hypothesis "the capability index is high". But, two fuzzy concepts low and high are usually formulated by two crisp hypotheses in traditional quality tests. In this paper, we formulate these two fuzzy concepts by considering two complement fuzzy sets. Afterwords, a new p-value-based approach is considered for testing the mentioned fuzzy hypotheses which is constructed on the basis of two capability indices C-p and C-pm. This new approach has several advantages over the common p-value methods for testing fuzzy hypotheses. The main one is depending the result of this new approach on both null and alternative fuzzy hypotheses, while the common p-value-based methods are according to only the null fuzzy hypothesis. To clarify the potential of the proposed approach in the process of capability analyses, two applied examples are given based on two real-world data set.
引用
收藏
页码:1649 / 1658
页数:10
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