International Journal of Statistics and Applied Mathematics
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2021, Vol. 6, Issue 1, Part A

A novel algorithm with a blend of single and sequential sampling (SSS) to reduce producer and consumer menace


Author(s): Devaarul S and Santhi T

Abstract: In this article, the two sampling techniques namely single and sequential sampling are blended together so as to reduce the producer and consumer menace. When the inspection or testing costs per product are high or products are destructive during testing then screening of the rejected lots may leads to high risk and hence a heavy loss may occur for the producer. If the lot is not accepted basis on the first phase of inspection then the faith of consumer on the sampling protocol may be reduced. Therefore to eradicate these shortcomings, Single and Sequential Sampling (SSS) algorithms are blended to obtain a new sampling protocol. The producer is given another chance of acceptance but at the same time item by item is recommended if the lot is not accepted during first phase of inspection. Hence producers as well as consumers are loaded with smaller menace (risks). A new algorithm to sentence the lot is given and the related measures are derived. The OC function shows slower decrease in the probability of acceptance for known quality levels and it is found that the producer risk is lower when compared to other sampling plans. Tables are constructed to select the parameters of the sampling plans.

Pages: 39-44 | Views: 560 | Downloads: 16

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How to cite this article:
Devaarul S, Santhi T. A novel algorithm with a blend of single and sequential sampling (SSS) to reduce producer and consumer menace. Int J Stat Appl Math 2021;6(1):39-44.
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