Determining sampling plans in acceptance sampling to reduce producer and consumer risks
Siddharth Mahajan
International Journal of Industrial and Systems Engineering, 2013, vol. 15, issue 4, 462-474
Abstract:
In this paper, we find the best sampling plan in acceptance sampling, to reduce producer and consumer risks. A sampling plan consists of two parameters, the sample size and the maximum allowed number of defectives. For a given sample size, there is a trade-off between the producer risk and the consumer risk. Which risk would be higher would depend on the other parameter which decides the sampling plan, the maximum allowed number of defectives. We show that as the sample size is increased, both producer and consumer risks can be reduced together. But increasing the sample size, means additional inspection cost for each and every sample. So, risk reduction would happen at a cost. Typically, the binomial distribution is used to determine the producer and consumer risks for a sampling plan. In the model, we use the normal approximation to the binomial. With the model, the sampling plan can be found very quickly, using Excel.
Keywords: acceptance sampling; consumer risks; producer risks; quality; risk reduction; sampling plans. (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=57480 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:15:y:2013:i:4:p:462-474
Access Statistics for this article
More articles in International Journal of Industrial and Systems Engineering from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().