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

Abstract

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

Date of Award	2015 Aug 10
Original language	English
Supervisor	Shuen-Lin Jeng (Supervisor)