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Selection of single sampling plans by attributes under the conditions of zero-inflated Poisson distribution

Loganathan Appaia (Department of Statistics, Manonmaniam Sundaranar University, Tirunelveli, India)
Shalini Kandaswamy (Department of Statistics, Manonmaniam Sundaranar University, Tirunelveli, India)

International Journal of Quality & Reliability Management

ISSN: 0265-671X

Article publication date: 30 September 2014

222

Abstract

Purpose

The purpose of this paper is to determine single sampling plans (SSPs) by attributes when the number of nonconformities is distributed according to a zero-inflated Poisson (ZIP) distribution.

Design/methodology/approach

Manufacturing processes have now-a-days been aligned properly and are monitored well, so that the occurrence of nonconformities would be a rare phenomenon. The information related to number of nonconformities per product will have more number of zeros. Under such circumstances, the appropriate probability distribution of the number of nonconformities is a ZIP distribution. The operating characteristic function of the sampling plan is derived.

Findings

Parameters of the sampling plans are obtained for some sets of values of (p 1, α, p 2, β). Numerical examples are given to illustrate the selection of SSPs under ZIP distribution and to study its advantages over Poisson SSP.

Originality/value

Results obtained in this paper are original and has been done for the first time in this regard. Parameters of the sampling plans are essential to make decisions either to accept or reject the lots based on the inspection of the samples.

Keywords

Acknowledgements

The authors would like to thank the University Grants Commission, New Delhi for providing financial support to carry out this work and gratefully acknowledge the referees for their helpful comments.

Citation

Appaia, L. and Kandaswamy, S. (2014), "Selection of single sampling plans by attributes under the conditions of zero-inflated Poisson distribution", International Journal of Quality & Reliability Management, Vol. 31 No. 9, pp. 1002-1011. https://doi.org/10.1108/IJQRM-06-2012-0093

Publisher

:

Emerald Group Publishing Limited

Copyright © 2014, Emerald Group Publishing Limited

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