Measuring process capability for bivariate non-normal process using the bivariate burr distribution

Abbasi, B, Ahmad, S, Abdollahian, M and Zeephongsekul, P 2007, 'Measuring process capability for bivariate non-normal process using the bivariate burr distribution', WSEAS Transactions on Business and Economics, vol. 5, no. 4, pp. 71-77.


Document type: Journal Article
Collection: Journal Articles

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Title Measuring process capability for bivariate non-normal process using the bivariate burr distribution
Author(s) Abbasi, B
Ahmad, S
Abdollahian, M
Zeephongsekul, P
Year 2007
Journal name WSEAS Transactions on Business and Economics
Volume number 5
Issue number 4
Start page 71
End page 77
Total pages 7
Publisher World Scientific and Engineering Academy and Society
Abstract As is well known, process capability analysis for more than one quality variables is a complicated and sometimes contentious area with several quality measures vying for recognition. When these variables exhibit non-normal characteristics, the situation becomes even more complex. The aim of this paper is to measure Process Capability Indices (PCIs) for bivariate non-normal process using the bivariate Burr distribution. The univariate Burr distribution has been shown to improve the accuracy of estimates of PCIs for univariate non-normal distributions (see for example, [7] and [16]). Here, we will estimate the PCIs of bivariate non-normal distributions using the bivariate Burr distribution. The process of obtaining these PCIs will be accomplished in a series of steps involving estimating the unknown parameters of the process using maximum likelihood estimation coupled with simulated annealing. Finally, the Proportion of Non-Conformance (PNC) obtained using this method will be compared with those obtained from variables distributed under the bivariate Beta, Weibull, Gamma and Weibull-Gamma distributions.
Subject Operations Research
Manufacturing Safety and Quality
Business and Management not elsewhere classified
Keyword(s) Process Capability Index (PCI)
bivariate Burr distribution
simulated annealing algorithm
nonnormal distribution
multivariate processes.
Copyright notice © 2007 World Scientific and Engineering Academy and Society
ISSN 1109-9526
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