Bootstrap Confidence Interval for Robust Cpk Index

A Cpk index is the most widely used measure of process capability. A better understanding and interpretation of Cpk is by constructing its confidence interval. The construction of such intervals, are normally based on the assumption that the measurements process can be treated as samples from...

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Main Authors: Midi, Habshah, Foo, Lee Kien
Format: Article
Language:English
English
Published: Institute for Mathematical Research 2008
Online Access:http://psasir.upm.edu.my/id/eprint/12454/1/artikel_5_vol1_no2.pdf
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author Midi, Habshah
Foo, Lee Kien
author_facet Midi, Habshah
Foo, Lee Kien
author_sort Midi, Habshah
collection UPM
description A Cpk index is the most widely used measure of process capability. A better understanding and interpretation of Cpk is by constructing its confidence interval. The construction of such intervals, are normally based on the assumption that the measurements process can be treated as samples from a normal distribution. Nevertheless, many processes are not normal and have a heavy tail distribution, which probably due to the presence of outliers in the data. An alternative approach is to use a bootstrap confidence interval estimate of Cpk index which is based on robust method. The advantage of this estimate is that its usage does not depend on any distribution. A numerical example is presented to evaluate the performance of the bootstrap confidence interval of the robust Cpk index. The result indicates that the bootstrap confidence interval estimate based on the robust Cpk is better than the classical Cpk index.
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spelling upm.eprints-124542013-05-27T07:52:21Z http://psasir.upm.edu.my/id/eprint/12454/ Bootstrap Confidence Interval for Robust Cpk Index Midi, Habshah Foo, Lee Kien A Cpk index is the most widely used measure of process capability. A better understanding and interpretation of Cpk is by constructing its confidence interval. The construction of such intervals, are normally based on the assumption that the measurements process can be treated as samples from a normal distribution. Nevertheless, many processes are not normal and have a heavy tail distribution, which probably due to the presence of outliers in the data. An alternative approach is to use a bootstrap confidence interval estimate of Cpk index which is based on robust method. The advantage of this estimate is that its usage does not depend on any distribution. A numerical example is presented to evaluate the performance of the bootstrap confidence interval of the robust Cpk index. The result indicates that the bootstrap confidence interval estimate based on the robust Cpk is better than the classical Cpk index. Institute for Mathematical Research 2008-06 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/12454/1/artikel_5_vol1_no2.pdf Midi, Habshah and Foo, Lee Kien (2008) Bootstrap Confidence Interval for Robust Cpk Index. Math Digest : Research Bulletin Institute for Mathematical Research, 1 (2). pp. 26-31. ISSN 1985-2436 English
spellingShingle Midi, Habshah
Foo, Lee Kien
Bootstrap Confidence Interval for Robust Cpk Index
title Bootstrap Confidence Interval for Robust Cpk Index
title_full Bootstrap Confidence Interval for Robust Cpk Index
title_fullStr Bootstrap Confidence Interval for Robust Cpk Index
title_full_unstemmed Bootstrap Confidence Interval for Robust Cpk Index
title_short Bootstrap Confidence Interval for Robust Cpk Index
title_sort bootstrap confidence interval for robust cpk index
url http://psasir.upm.edu.my/id/eprint/12454/1/artikel_5_vol1_no2.pdf
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