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Оптимизация на поддръжката×Регресия на Вайбул за оцеляване (Weibull Parametric Survival Regression)×
ОбластНадеждностАнализ на преживяемостта
СемействоProcess / pipelineSurvival analysis
Година на възникване20021951
СъздателHongzhou WangWaloddi Weibull
Типdecision optimization frameworkFully parametric survival regression model
Основополагащ източникWang, H. (2002). A survey of maintenance policies of deteriorating systems. European Journal of Operational Research, 139(3), 469–489. DOI ↗Kalbfleisch, J. D. & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. DOI ↗
Други названияOptimal Maintenance Policy, Preventive Maintenance Scheduling, Predictive Maintenance Optimization, Bakım Optimizasyonuweibull aft model, weibull survival model, parametric survival regression, Weibull Regresyonu — Parametrik Hayatta Kalma
Свързани34
РезюмеMaintenance Optimization is a quantitative framework for determining the timing, type, and frequency of maintenance actions—preventive, predictive, or corrective—that minimize total cost or expected downtime over a system's operational life. Systematic formulations were consolidated by Hongzhou Wang (2002), whose survey unified age-replacement, block-replacement, and imperfect-repair policies under a common cost-rate structure applicable to deteriorating systems across engineering and operations management.Weibull regression is a fully parametric survival model, formalised by Kalbfleisch and Prentice, that assumes survival times follow a Weibull distribution. A shape parameter controls whether the hazard increases, decreases, or remains constant over time, while covariates shift the scale of the distribution to express how predictors affect survival.
ScholarGateНабор от данни
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  2. 1 Източници
  3. PUBLISHED
  1. v1
  2. 1 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Maintenance Optimization · Weibull Regression. Извлечено на 2026-06-18 от https://scholargate.app/bg/compare