PARAMETRIC ESTIMATION OF THE PROCESS CAPABILITY INDEX S''pk AND ITS APPLICATION TO ELECTRONIC INDUSTRIES.
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| Title: | PARAMETRIC ESTIMATION OF THE PROCESS CAPABILITY INDEX S'' |
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| Authors: | SAHA, MAHENDRA1 drmahendrasaha1981@gmail.com, PAREEK, PRATIBHA2 pratibhaprk8437@gmail.com, DEVI, ANJU3 anjuchoudharykuk@gmail.com, YADAV, ABHIMANYU S.4 asybhu10@gmail.com |
| Source: | Reliability: Theory & Applications. Dec2025, Vol. 20 Issue 4, p931-947. 17p. |
| Subjects: | Process capability, Electronic industries, Monte Carlo method, Bayes' estimation, Confidence intervals, Estimation theory, Gaussian distribution, Data analysis |
| Abstract: | The proposed index is the process capability index used in the electronics industries to measure the capability of the process. This article focuses on process capability index, specifically applicable to normal random variables. The article has three main objectives: Firstly, we explore various classical estimation methods for the proposed index from frequentist approaches for normal distributions and compare their performance based on mean squared errors. Second, we calculate the classical confidence interval for the proposed index, which includes the asymptotic confidence interval. Third, we examine both Bayes point and interval estimation under symmetric and asymmetric loss functions for the proposed index. A Monte Carlo and Markov Chain Monte Carlo simulation study is conducted to compare the performance of the classical and the Bayes estimates of the proposed index for some set of parameters. Finally, to demonstrate the applicability of this index, two real data sets from the electronics industry are re-analyzed. [ABSTRACT FROM AUTHOR] |
| Copyright of Reliability: Theory & Applications is the property of International Group on Reliability 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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| Items | – Name: Title Label: Title Group: Ti Data: PARAMETRIC ESTIMATION OF THE PROCESS CAPABILITY INDEX S''<subscript>pk</subscript> AND ITS APPLICATION TO ELECTRONIC INDUSTRIES. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22SAHA%2C+MAHENDRA%22">SAHA, MAHENDRA</searchLink><relatesTo>1</relatesTo><i> drmahendrasaha1981@gmail.com</i><br /><searchLink fieldCode="AR" term="%22PAREEK%2C+PRATIBHA%22">PAREEK, PRATIBHA</searchLink><relatesTo>2</relatesTo><i> pratibhaprk8437@gmail.com</i><br /><searchLink fieldCode="AR" term="%22DEVI%2C+ANJU%22">DEVI, ANJU</searchLink><relatesTo>3</relatesTo><i> anjuchoudharykuk@gmail.com</i><br /><searchLink fieldCode="AR" term="%22YADAV%2C+ABHIMANYU+S%2E%22">YADAV, ABHIMANYU S.</searchLink><relatesTo>4</relatesTo><i> asybhu10@gmail.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Reliability%3A+Theory+%26+Applications%22">Reliability: Theory & Applications</searchLink>. Dec2025, Vol. 20 Issue 4, p931-947. 17p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Process+capability%22">Process capability</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+industries%22">Electronic industries</searchLink><br /><searchLink fieldCode="DE" term="%22Monte+Carlo+method%22">Monte Carlo method</searchLink><br /><searchLink fieldCode="DE" term="%22Bayes'+estimation%22">Bayes' estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Confidence+intervals%22">Confidence intervals</searchLink><br /><searchLink fieldCode="DE" term="%22Estimation+theory%22">Estimation theory</searchLink><br /><searchLink fieldCode="DE" term="%22Gaussian+distribution%22">Gaussian distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The proposed index is the process capability index used in the electronics industries to measure the capability of the process. This article focuses on process capability index, specifically applicable to normal random variables. The article has three main objectives: Firstly, we explore various classical estimation methods for the proposed index from frequentist approaches for normal distributions and compare their performance based on mean squared errors. Second, we calculate the classical confidence interval for the proposed index, which includes the asymptotic confidence interval. Third, we examine both Bayes point and interval estimation under symmetric and asymmetric loss functions for the proposed index. A Monte Carlo and Markov Chain Monte Carlo simulation study is conducted to compare the performance of the classical and the Bayes estimates of the proposed index for some set of parameters. Finally, to demonstrate the applicability of this index, two real data sets from the electronics industry are re-analyzed. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Reliability: Theory & Applications is the property of International Group on Reliability 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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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.24412/1932-2321-2025-489-931-947 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 931 Subjects: – SubjectFull: Process capability Type: general – SubjectFull: Electronic industries Type: general – SubjectFull: Monte Carlo method Type: general – SubjectFull: Bayes' estimation Type: general – SubjectFull: Confidence intervals Type: general – SubjectFull: Estimation theory Type: general – SubjectFull: Gaussian distribution Type: general – SubjectFull: Data analysis Type: general Titles: – TitleFull: PARAMETRIC ESTIMATION OF THE PROCESS CAPABILITY INDEX S''pk AND ITS APPLICATION TO ELECTRONIC INDUSTRIES. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: SAHA, MAHENDRA – PersonEntity: Name: NameFull: PAREEK, PRATIBHA – PersonEntity: Name: NameFull: DEVI, ANJU – PersonEntity: Name: NameFull: YADAV, ABHIMANYU S. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 19322321 Numbering: – Type: volume Value: 20 – Type: issue Value: 4 Titles: – TitleFull: Reliability: Theory & Applications Type: main |
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