A two-stage prognosis model in condition based maintenance

DOI10.1016/j.ejor.2006.08.047zbMath1278.90124OpenAlexW2127602933MaRDI QIDQ884042

Wenbin Wang

Publication date: 13 June 2007

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2006.08.047

zbMATH Keywords

maintenanceresidual lifeprognosiscondition monitoringtwo-stage failure

Mathematics Subject Classification ID

Reliability, availability, maintenance, inspection in operations research (90B25)

Related Items (11)

Estimating remaining useful life for degrading systems with large fluctuations ⋮ Editorial: Recent development on nonlinear methods in function spaces and applications in nonlinear fractional differential equations ⋮ Degradation data analysis and remaining useful life estimation: a review on Wiener-process-based methods ⋮ The availability model and parameters estimation method for the delay time model with imperfect maintenance at inspection ⋮ A simulation-based multivariate Bayesian control chart for real time condition-based maintenance of complex systems ⋮ Parameter estimation of a multistate model for an aging piece of equipment under condition-based maintenance ⋮ Online health management for complex nonlinear systems based on hidden semi-Markov model using sequential Monte Carlo methods ⋮ A Bayesian model and numerical algorithm for CBM availability maximization ⋮ An approximate algorithm for prognostic modelling using condition monitoring information ⋮ A model for real-time failure prognosis based on hidden Markov model and belief rule base ⋮ A Model for Residual Life Prediction Based on Brownian Motion in Framework of Similarity

Cites Work

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• Stochastic processes and filtering theory
• A model to predict the residual life of rolling element bearings given monitored condition information to date
• Developments in delay time analysis for modelling plant maintenance
• Towards a general condition based maintenance model for a stochastic dynamic system
• A model to predict the residual life of aircraft engines based upon oil analysis data
• Developing and Testing the Delay-Time Model
• Modelling the probability assessment of system state prognosis using available condition monitoring information

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