Determining sampling plans in acceptance sampling to reduce producer and consumer risks
by Siddharth Mahajan
International Journal of Industrial and Systems Engineering (IJISE), Vol. 15, No. 4, 2013

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.

Online publication date: Fri, 27-Dec-2013

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Industrial and Systems Engineering (IJISE):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com