M. Jaenada, L. Pardo, N. Balakrishnan
Many nowadays products have a long life before failure. Reliability analyses for such highly reliable devices therefore present a practical challenge as obtaining sufficient failure information to adequately assess lifetime behavior will require extended experimental duration. As an alternative, accelerated life testing (ALT) is commonly used to shorten the time to failure of units under test, with the results subsequently extrapolated to normal operating conditions. This work develops robust inferential methods based on the density power divergence for analyzing step-stress ALT data. Point estimates and approximate confidence intervals for model parameters, along with robust estimates of some important lifetime characteristics are also studied. To demonstrate the practical utility of robust estimators in step-stress ALTs, real data are analyzed and a Monte Carlo simulation is conducted. Our results highlight the robustness of the MDPDE in the presence of data contamination.
Palabras clave: Accelerated Life-Tests, Reliability, Robustness
Programado
Premio Ramiro Melendreras
10 de junio de 2025 19:00
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