Abstract
Proposes Bayesian life test sampling plan for non‐repairable products with exponential lifetime distribution, which are sold under a warranty policy. It is assumed that the parameter of the lifetime distribution is a random variable varying from lot to lot according to a known prior distribution. Describes constructions of a cost model with three cost components: test cost, accept cost, and reject cost. Presents an algorithm for finding optimal sampling plans which minimize the expected average cost per lot. Describes sensitivity analyses for the parameters for the prior distribution.
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