Implementation of compound optimal design strategy in reliability acceptance sampling plans

In this article, a reliability acceptance sampling plan (RASP) has been used to determine the acceptability of a lot of products based on their lifetime. We determined the optimal sample size in RASP by using a compound optimal design strategy. To compute the compound optimal design, we have considered two objective functions in the presence of progressive censoring. The extreme value distribution has been used to illustrate the concept. We compute the Fisher information matrix and the asymptotic variance-covariance matrix of the maximum likelihood estimates using a progressively censored sample. This matrix is utilized to determine the compound optimal design by developing a graphical solution approach that facilitates the computation and interpretation of the compound optimal design. A sensitivity analysis has been studied to examine the effects of misspecifying the lifetime model parameters. To demonstrate its practical use, we illustrate the proposed methodology with a real-life example.