Prognostics and Remaining Useful Life
Prognostics and Health Management (PHM) is a methodology for predicting the remaining useful life (RUL) of equipment by monitoring its condition and extrapolating degradation trends. Unlike reactive maintenance (wait for failure) or preventive maintenance (fixed schedules), prognostics enable predictive maintenance: act only when failure is imminent. Formalized in the 2000s by researchers including George Vachtsevanos, RUL prediction integrates sensor data, degradation models, and uncertainty quantification to inform maintenance planning and reduce downtime.
Källpost
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- Vachtsevanos, G., Lewis, F. L., Roemer, M., Hess, A., & Wu, B. (2006). Intelligent Fault Diagnosis and Prognosis for Engineering Systems. Wiley. · DOI 10.1002/9780470117842
- Saxena, A., Celaya, J., Balaji, B., Goebel, K., Saha, B., Saha, S., & Schwabacher, M. (2010). Metrics for evaluating the accuracy of prognostic techniques. International Journal of Prognostics and Health Management, 1(1), 1-20. · URL
- Goebel, K., Saha, B., & Saxena, A. (2008). A comparison of three data-driven techniques for prognostics. IEEE Aerospace Conference, 1-11. · URL
- Si, X. S., Wang, W., Hu, C. H., & Chen, M. Y. (2012). Remaining useful life estimation based on stochastic degradation models. Reliability Engineering & System Safety, 99, 146-154. · URL
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