Salīdzināt metodes

	Degradācijas modeļi	Optimizācija apkopei
Nozare	Drošums	Drošums
Saime	Regression model	Process / pipeline
Izcelsmes gads	1998	2002
Autors	Meeker, Escobar & Lu	Hongzhou Wang
Tips	Stochastic degradation path model	decision optimization framework
Pirmavots	Meeker, W. Q., Escobar, L. A., & Lu, C. J. (1998). Accelerated degradation tests: modeling and analysis. Technometrics, 40(2), 89–99.	Wang, H. (2002). A survey of maintenance policies of deteriorating systems. European Journal of Operational Research, 139(3), 469–489.
Citi nosaukumi	Accelerated Degradation Testing, Degradation Path Models, Performance Degradation Analysis, Bozunma Modelleri	Optimal Maintenance Policy, Preventive Maintenance Scheduling, Predictive Maintenance Optimization, Bakım Optimizasyonu
Saistītās	3	3
Kopsavilkums	Degradation 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.	Maintenance 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.