A Quality Decision-Making Approach Based on the Asymptotic Distribution of the Taguchi Index Estimator.

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Bibliographic Details
Title:	A Quality Decision-Making Approach Based on the Asymptotic Distribution of the Taguchi Index Estimator.
Authors:	Chen, Kuen-Suan^1,2,3 (AUTHOR) kuensuan.chen@gmail.com, Lin, Gu-Hong⁴ (AUTHOR) ghlin@nkust.edu.tw, Yu, Chun-Min¹ (AUTHOR) yu2013000@gmail.com
Source:	International Journal of Reliability, Quality & Safety Engineering. Aug2025, Vol. 32 Issue 4, p1-16. 16p.
Subjects:	Process capability, Confidence intervals, Fuzzy measure theory, Statistical decision making, Asymptotic distribution
Abstract:	Quality characteristics involving asymmetric tolerances occur in many production processes. C p m ′ ′ , a generalized Taguchi capability index, has been utilized to measure the manufacturing performance with asymmetric tolerances. Most investigations on this index assume a normal distribution when analyzing samples. In contrast, this study explored a natural estimator of C p m ′ ′ using subsamples. The limiting distribution and associated large-sample properties of the estimator were examined for the general population using the fourth central moment. This study thus derived an approximate (1 − α) 1 0 0 % confidence interval of C p m ′ ′ . However, collected data are often imprecise. To address this problem, this study derived a triangular fuzzy number for C p m ′ ′ ∗ by constructing a series of confidence intervals and employed it to develop fuzzy testing for determining whether the process is capable. A case study was given to illustrate how the proposed procedure was used for evaluating process capability. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	Quality characteristics involving asymmetric tolerances occur in many production processes. C p m ′ ′ , a generalized Taguchi capability index, has been utilized to measure the manufacturing performance with asymmetric tolerances. Most investigations on this index assume a normal distribution when analyzing samples. In contrast, this study explored a natural estimator of C p m ′ ′ using subsamples. The limiting distribution and associated large-sample properties of the estimator were examined for the general population using the fourth central moment. This study thus derived an approximate (1 − α) 1 0 0 % confidence interval of C p m ′ ′ . However, collected data are often imprecise. To address this problem, this study derived a triangular fuzzy number for C p m ′ ′ ∗ by constructing a series of confidence intervals and employed it to develop fuzzy testing for determining whether the process is capable. A case study was given to illustrate how the proposed procedure was used for evaluating process capability. [ABSTRACT FROM AUTHOR]
ISSN:	02185393
DOI:	10.1142/S0218539325500160