A note on the generalized indices of process capability

Process capability indices are widely used to assess whether the outputs of an in-control process meet the specifications. The commonly used indices are , , and . In most applications, the quality characteristics are assumed to follow normal distribution. But, in practice, many quality characteristi...

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Main Authors: S. Gauri, S. Pal
Format: Article
Language:English
Published: Ayandegan Institute of Higher Education, 2020-09-01
Series:International Journal of Research in Industrial Engineering
Subjects:
Online Access:http://www.riejournal.com/article_119805_0acf48cbbf99aa5cfca2df0617a0b369.pdf
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spelling doaj-87b15612317044189c7a978b43933bb12021-09-06T05:51:51ZengAyandegan Institute of Higher Education,International Journal of Research in Industrial Engineering2783-13372717-29372020-09-019328630310.22105/riej.2020.237520.1137119805A note on the generalized indices of process capabilityS. Gauri0S. Pal1Statistical Quality Control and Operations Research Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata-700108, India.Statistical Quality Control and Operations Research Unit, Indian Statistical Institute, 110, Nelson Manickam Road, Chennai- 600029, India.Process capability indices are widely used to assess whether the outputs of an in-control process meet the specifications. The commonly used indices are , , and . In most applications, the quality characteristics are assumed to follow normal distribution. But, in practice, many quality characteristics, e.g. count data, proportion defective etc. follow Poisson or binomial distributions, and these characteristics usually have one-sided specification limit. In these cases, computations of  or  using the standard formula is inappropriate. In order to alleviate the problem, some generalized indices (e.g.  index,  index,   index and  index) are proposed in literature. The variant of these indices for one-sided specification are  and ,  and ¸  and ,  and  respectively. All these indices can be computed in any process regardless of whether the quality characteristics are discrete or continuous.  However, the same value for different generalized indices and  or  signifies different capabilities for a process and this poses difficulties in interpreting the estimates of the generalized indices. In this study, the relative goodness of the generalized indices is quantifying capability of a process is assessed. It is found that only   or  gives proper assessment about the capability of a process. All other generalized indices give a false impression about the capability of a process and thus usages of those indices should be avoided. The results of analysis of multiple case study data taken from Poisson and binomial processes validate the above findings.http://www.riejournal.com/article_119805_0acf48cbbf99aa5cfca2df0617a0b369.pdfgeneralized pcigoodness of generalized pcinormal processpoisson processbinomial process
collection DOAJ
language English
format Article
sources DOAJ
author S. Gauri
S. Pal
spellingShingle S. Gauri
S. Pal
A note on the generalized indices of process capability
International Journal of Research in Industrial Engineering
generalized pci
goodness of generalized pci
normal process
poisson process
binomial process
author_facet S. Gauri
S. Pal
author_sort S. Gauri
title A note on the generalized indices of process capability
title_short A note on the generalized indices of process capability
title_full A note on the generalized indices of process capability
title_fullStr A note on the generalized indices of process capability
title_full_unstemmed A note on the generalized indices of process capability
title_sort note on the generalized indices of process capability
publisher Ayandegan Institute of Higher Education,
series International Journal of Research in Industrial Engineering
issn 2783-1337
2717-2937
publishDate 2020-09-01
description Process capability indices are widely used to assess whether the outputs of an in-control process meet the specifications. The commonly used indices are , , and . In most applications, the quality characteristics are assumed to follow normal distribution. But, in practice, many quality characteristics, e.g. count data, proportion defective etc. follow Poisson or binomial distributions, and these characteristics usually have one-sided specification limit. In these cases, computations of  or  using the standard formula is inappropriate. In order to alleviate the problem, some generalized indices (e.g.  index,  index,   index and  index) are proposed in literature. The variant of these indices for one-sided specification are  and ,  and ¸  and ,  and  respectively. All these indices can be computed in any process regardless of whether the quality characteristics are discrete or continuous.  However, the same value for different generalized indices and  or  signifies different capabilities for a process and this poses difficulties in interpreting the estimates of the generalized indices. In this study, the relative goodness of the generalized indices is quantifying capability of a process is assessed. It is found that only   or  gives proper assessment about the capability of a process. All other generalized indices give a false impression about the capability of a process and thus usages of those indices should be avoided. The results of analysis of multiple case study data taken from Poisson and binomial processes validate the above findings.
topic generalized pci
goodness of generalized pci
normal process
poisson process
binomial process
url http://www.riejournal.com/article_119805_0acf48cbbf99aa5cfca2df0617a0b369.pdf
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