Department Industrial Engineering and Manufacturing Autonomous University of Ciudad Juarez Av. Plutarco Elías Calles 1210, Fovissste Chamizal 32310 Ciudad Juárez, Chihuahua, México
Publication date: 2019-12-31
Eksploatacja i Niezawodność – Maintenance and Reliability 2019;21(4):654-661
Many products wear out over time even before they fail or stop working, therefore, through accelerated degradation tests one is
able to make inferences about statistical parameters or the distributions of a product useful life. Since many devices experience
different types of variation due to unobservable factors during the manufacturing processes or under certain operating conditions;
these situations lead to the need in developing accelerated degradation models with several variables of acceleration and random
effects. The proposed model in this paper, is a model based on the gamma process with random effects to have a better analysis
of degradation. This model is applied to the analysis of the temperature increase of metal stampings that are affected by multiple
explanatory variables. In addition, a statistical inference method based on a Bayesian approach is used to estimate the unknown
parameters to then perform a reliability analysis after obtaining the first-passage time distributions.
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