Planning Repeated Measures Accelerated Degradation Tests under Non-linear Mixed Effect Models

• Main Authors: Geng-JieYeh, 葉耿傑
• Other Authors: Shuen-Lin Jeng
• Format: Others
• Language: en_US
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/93109429808951812335

碩士 === 國立成功大學 === 統計學系 === 103 === Repeated measures accelerated degradation tests (RMADTs) can provide more information about the product reliability when one would expect few or even no failures during a study. In this paper, we deal with the optimal test planning problem under the non-linear Arrhenius acceleration model. Further, unit-to-unit variability is described by the random effects, which is also non-linear in time. Due to the assumption of non-linear mixed effect model (NLMEM), the analytical calculation of the likelihood and some related functions such as Fisher information matrix are difficult. Therefore, we perform the Monte Carlo integration to calculate the asymptotic variance of estimators as the optimality criterion. Grid search procedures are conducted to find the optimum test plan under some constraints. Quasi-random low-discrepancy sequences and some R packages for efficient computation are used to relief the computational burden. The method is illustrated with an application of an integrated circuit device example.