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

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Title: A Quality Decision-Making Approach Based on the Asymptotic Distribution of the Taguchi Index Estimator.
Authors: Chen, Kuen-Suan1,2,3 (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]
Copyright of International Journal of Reliability, Quality & Safety Engineering is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: A Quality Decision-Making Approach Based on the Asymptotic Distribution of the Taguchi Index Estimator.
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  Data: <searchLink fieldCode="AR" term="%22Chen%2C+Kuen-Suan%22">Chen, Kuen-Suan</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> kuensuan.chen@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Lin%2C+Gu-Hong%22">Lin, Gu-Hong</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> ghlin@nkust.edu.tw</i><br /><searchLink fieldCode="AR" term="%22Yu%2C+Chun-Min%22">Yu, Chun-Min</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> yu2013000@gmail.com</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Reliability%2C+Quality+%26+Safety+Engineering%22">International Journal of Reliability, Quality & Safety Engineering</searchLink>. Aug2025, Vol. 32 Issue 4, p1-16. 16p.
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  Data: <searchLink fieldCode="DE" term="%22Process+capability%22">Process capability</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+measure+theory%22">Fuzzy measure theory</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+decision+making%22">Statistical decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Asymptotic+distribution%22">Asymptotic distribution</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Reliability, Quality & Safety Engineering is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1142/S0218539325500160
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      – Code: eng
        Text: English
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        PageCount: 16
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    Subjects:
      – SubjectFull: Process capability
        Type: general
      – SubjectFull: Confidence intervals
        Type: general
      – SubjectFull: Fuzzy measure theory
        Type: general
      – SubjectFull: Statistical decision making
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      – SubjectFull: Asymptotic distribution
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      – TitleFull: A Quality Decision-Making Approach Based on the Asymptotic Distribution of the Taguchi Index Estimator.
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            NameFull: Lin, Gu-Hong
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            – D: 01
              M: 08
              Text: Aug2025
              Type: published
              Y: 2025
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            – TitleFull: International Journal of Reliability, Quality & Safety Engineering
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