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Модели на деградация×Статистически анализ на надеждността×
ОбластНадеждностНадеждност
СемействоRegression modelRegression model
Година на възникване19981998
СъздателMeeker, Escobar & LuWilliam Meeker & Luis Escobar
ТипStochastic degradation path modelParametric lifetime modeling
Основополагащ източникMeeker, W. Q., Escobar, L. A., & Lu, C. J. (1998). Accelerated degradation tests: modeling and analysis. Technometrics, 40(2), 89–99. DOI ↗Meeker, W. Q., & Escobar, L. A. (1998). Statistical Methods for Reliability Data. Wiley. ISBN: 978-0-471-14328-4
Други названияAccelerated Degradation Testing, Degradation Path Models, Performance Degradation Analysis, Bozunma ModelleriLife Data Analysis, Survival Analysis (Engineering), Time-to-Failure Analysis, Güvenilirlik Analizi
Свързани33
РезюмеDegradation models estimate product lifetime by tracking measurable performance characteristics—such as crack length, light output, or insulation resistance—over time rather than waiting for outright failure. Introduced in rigorous form by Meeker, Escobar, and Lu (1998), these models fit a stochastic degradation path to repeated measurements and define failure as the first time the characteristic crosses a predetermined threshold, enabling reliable lifetime inference from accelerated test data with very few or no observed failures.Statistical reliability analysis models the time-to-failure of components, systems, or products using parametric lifetime distributions fitted to observed or censored failure data. Formalized comprehensively by William Q. Meeker and Luis A. Escobar in their 1998 Wiley monograph, the framework integrates maximum likelihood estimation, censoring mechanisms, and distributional diagnostics to produce probability-of-failure curves, hazard rates, and quantile estimates that support design, warranty, and maintenance decisions.
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  2. 1 Източници
  3. PUBLISHED
  1. v1
  2. 1 Източници
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ScholarGateСравнение на методи: Degradation Models · Reliability Analysis. Извлечено на 2026-06-17 от https://scholargate.app/bg/compare