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Activity Number: 126 - New Development in Reliability Models and Innovative Applications
Type: Contributed
Date/Time: Monday, July 30, 2018 : 8:30 AM to 10:20 AM
Sponsor: Section on Physical and Engineering Sciences
Abstract #330212
Title: Statistical Inference on Remaining Useful Life in a Two-Phase Degradation Model Under Gamma Process
Author(s): Hon Keung Tony Ng* and Man Ho Ling and Kwok Leung Tsui
Companies: Southern Methodist University and The Education University of Hong Kong and City University of Hong Kong
Keywords: Degradation models; Gamma process; Change point; Bayesian ; Stochastic expectation-maximization
Abstract:

Remaining useful life prediction has been one of the important research topics in reliability engineering. For modern products, due to physical and chemical changes that take place with usage and with age, a significant degradation rate change usually exists. Degradation models that do not incorporate a change point may not accurately yield the remaining useful life prediction for products with two-phase degradation. For this reason, we consider the degradation analysis for products with two-phase degradation under the gamma process. Incorporating a probability distribution of the time of rate change into the degradation model, the remaining useful life prediction for a single product can be obtained, even though the rate change has not occurred during the inspection. A Bayesian approach and a frequentist approach are proposed for estimation and statistical inference of the remaining useful life of products with two-phase degradation. A simulation study is carried out to evaluate the performance of the developed methodologies and a real dataset on light emitting diodes is presented to illustrate the application of the proposed model.


Authors who are presenting talks have a * after their name.

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