Lifetime models for remaining useful life estimation with randomly distributed failure thresholds



Published Jul 3, 2012
Bent Helge Nystad Giulio Gola John Einar Hulsund


In order to predict in advance and with the smallest possible uncertainty when a component needs to be fixed or replaced, lifetime models are developed based on the information of the component deterioration trend and its failure threshold to estimate the stochastic distribution of the hitting time (the first time the deterioration exceeds the failure threshold) and the remaining useful life. A primary issue is how to effectively handle the uncertainties related to the component deterioration trend and failure threshold. This problem is here investigated considering a non-stationary gamma process to model the component deterioration and a gamma-distributed failure threshold. Two lifetime models are proposed for comparison on an application concerning deterioration of choke valves used in offshore oil platforms.

How to Cite

Nystad, B. H., Gola, G., & Hulsund, J. E. (2012). Lifetime models for remaining useful life estimation with randomly distributed failure thresholds. PHM Society European Conference, 1(1).
Abstract 156 | PDF Downloads 175



gamma process, RUL, random distributed threshold

Abdel-Hameed, M. (1975). A gamma wear process. IEEE Transactions on Reliability, 24(2), 152-153.
Andrews, J., Kjørholt, H., & Jøranson, H. (2005). Production enhancement from sand management philosophy: a case study from Statfjord and Gullfaks (SPE 94511). SPE European Formation Damage
Conference, May 25-27, Sheveningen, The Netherlands.
Bringedal, B., Hovda, K., Ujang, P., With, H.M., & Kjørrefjord, G. (2010). Using online dynamic virtual flow metering and sand erosion monitoring for integrity management and production optimization. Deep Offshore Technology Conference, May 3-6, Huston,Texas.
Fantoni, P.F., & Nordlund, A. (2009). Wire system aging assessment and condition monitoring (WASCO). NKS-130. ISBN 87-7893-192-4
Frenk, J.B.G., & Nicolai, R.P. (2007). Approximating the randomized hitting time distribution of a non-stationary gamma process. Rotterdam: Econometric Institute and Erasmus Research Institute of Management.
Gola, G., & Nystad, B.H. (2011a). From measurement collection to remaining useful life estimation: defining a diagnostic-prognostic frame for optimal maintenance scheduling of choke valves undergoing erosion. Annual Conference of the Prognostics and Health Management Society, September 26-29, Montreal, Canada.
Gola, G., & Nystad, B.H. (2011b). Comparison of time- and state-space non-stationary gamma processes for estimating the remaining useful life of choke valves undergoing erosion. 24th International COMADEM Conference, May 30 - June 1, Stavanger, Norway.
Kirmanen, J., Niemelä, I., Pyötsiä, J., Simula, M., Hauhia, M., & Riihilahti, J. (2005). Flow control manual. Helsinki: Metso Automation.
Lu, J.C., & Meeker, W.Q. (1993). Using degradation measures to estimate a time-to-failure distribution. Technometrics, 35(2), 161-173.
Mc Pehrson, J.W. (2010). Reliability physics and engineering. London: Springer.
Nystad, B.H. (2008). Technical condition indexes and remaining useful life of aggregated systems. Doctoral dissertation. Norwegian University of Science and Technology (NTNU), Trondheim, Norway. ISBN: 978-82-471-1256-4
Rausand, M., & Høyland, A. (2004). System reliability theory. Models, statistical methods, and applications. New Jersey: Wiley & Sons.
van Noortwijk, J.M. (2009). A survey of the application of gamma processes in maintenance. Reliability Engineering and System Safety, 94(1), 2-21.
Welte, T.M., & Eggen, A.O. (2008). Estimation of sojourn time distribution parameters based on expert opinion and condition monitoring data. International Conference on Probability Methods Applied to Power Systems, May 25-29, Rincòn, Puerto Rico.
Technical Papers