Optimum constant-stress life test plans for Pareto distribution under type-I censoring

Abstract

The paper considers the case of constant-stress partially accelerated life testing (CSPALT) when two stress levels are involved under type-I censoring. The lifetimes of test items are assumed to follow a two-parameter Pareto lifetime distribution. Maximum-likelihood method is used to estimate the parameters of CSPALT model. Confidence intervals for the model parameters are constructed. Optimum CSPALT plans that determine the best choice of the proportion of test units allocated to each stress are developed. Such optimum test plans minimize the generalized asymptotic variance of the maximum-likelihood estimators of the model parameters. For illustration, Monte Carlo simulation studies are presented.

Keywords:

• reliability
• Pareto distribution
• partial acceleration
• constant-stress
• maximum-likelihood estimation
• Fisher information matrix
• optimum test plans
• type-I censoring
• Monte Carlo simulation

Acknowledgements

This project was supported by King Saud University, Deanship of Scientific Research, College of Science Research Center. The authors also thank the editor and the referees for their helpful comments and corrections which led to improvements of an earlier version of this article.