  In this study, variable acceptance sampling plans under Type I hybrid
censoring is designed for a lot of independent and identical units with
exponential lifetimes using Bayesian estimate of the parameter $\vartheta$.
This approach is new from the conventional methods in acceptance sampling plan
which relay on maximum likelihood estimate and minimising of Bayes risk.
Bayesian estimate is obtained using squared error loss and Linex loss
functions. Optimisation problem is solved for minimising the testing cost under
each methods and optimal values of the plan parameters $n, t_1$ and $t_2$ are
calculated. The proposed plans are illustrated using various examples and a
real life case study is also conducted. Expected testing cost of the sampling
plan obtained using squared error loss function is much lower than the cost of
existing plans using maximum likelihood estimate.
