CONSTRUCTION OF MULTIPLE DEPENDENT STATE SAMPLING PLAN FOR VARIABLES ON SYMMETRIC DISTRIBUTIONS
Keywords:
multiple dependent state sampling plan, symmetric distribution, operating characteristic curve, acceptable quality level, limiting quality levelDOI:
https://doi.org/10.17654/0972086322009Abstract
Acceptance sampling is a statistical technique which contains the procedure, to reach a decision on either to accept or to reject the lots based on the quality of the sampled units inspected. The variable sampling inspection plan, one of the acceptance sampling techniques, is applicable when the quality characteristic of sampled items is measured on a continuous scale and functional form of the probability distribution is known. When the lots are submitted substantially in the order of their production from a process having a constant proportion of non-conforming, one of the conditional sampling plans, called multiple dependent state sampling inspection plan, is implemented. In this article, a multiple dependent state sampling plan is proposed for sentencing lots of products with quality characteristic following symmetric distributions. The proposed plan is designed by considering two points on the OC curve, namely, (AQL, 1 – $\alpha$) and (LQL, $\beta$), by formulating it as a non-linear optimization problem. A comparative study is carried out for three symmetric distributions, namely, Laplace, logistic and normal distributions.
Received: April 21, 2022
Accepted: June 14, 2022
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