The Birnbaum-Saunders distribution has been recognized as a versatile failure time model. However, it is not widely used in process control as some of its important characteristics have not been obtained. In this paper, we utilize the bootstrap method to construct a prediction interval for future observations from a Birnbaum-Saunders distribution. Monte Carlo simulations are carried out to evaluate the performance of the proposed procedure. The results reveal that the bootstrap intervals are satisfied with desired coverage probabilities and average lengths as sample size n is at least 30. (C) 1997 Elsevier Science Ltd.
