Condition-based maintenance for multi-component systems using importance measure and predictive information

References

• Abdel-Hameed, M. (1975). A gamma wear proces. IEEE Transactions on Reliability, 24(2), 152–153.
   Web of Science ®Google Scholar
• Abdel-Hameed, M. (2010). Degradation processes: An overview. In : M.S. Nikulin, N. Limnios, N. Balakrishnan, W. Kahle, & C. Huber-Carol (Eds.), Advances in Degradation Modeling, ser. Springer series in Statistics for Industry and Technology (pp. 17–25). Boston, MA: Birkhauser.
   Google Scholar
• Ahmad, R., & Kamaruddin, S. (2012). An overview of time-based and condition-based maintenance in industrial application. Computers & Industrial Engineering, 63(1), 135–149.
   Web of Science ®Google Scholar
• Andrews, J.D., & Beeson, S. (2003). Birnbaum’s measure of component importance for noncoherent systems. IEEE Transactions on Reliability, 52(2), 213–219.
   Web of Science ®Google Scholar
• Barbera, F., Schneider, H., & Watson, E. (1999). A condition based maintenance model for a two-unit series system. European Journal of Operational Research, 116(2), 281–290.
   Web of Science ®Google Scholar
• Barros, A., Bérenguer, C., & Grall, A. (2003). Optimization of replacement times using imperfect monitoring information. IEEE Transactions on Reliability, 52(4), 523–533.
   Web of Science ®Google Scholar
• Bérenguer, C., Grall, A., & Castanier, B. (2000). Simulation and evaluation of condition-based maintenance policies for multi-component continuous-state deteriorating systems. In M.P. Cottam, D.W. Harvey, R.P. Pape, & J. Tait (Eds.), Book Review—Foresight and Precaution: Proceedings of ESREL 2000, SARS and SRA-Europe Annual Conference (pp. 275–282). Rotterdam: Balkema.
   Google Scholar
• Bian, L., & Gebraeel, N. (2014). Stochastic modeling and real-time prognostics for multi-component systems with degradation rate interactions. IIE Transactions, 46(5), 470–482.
   Web of Science ®Google Scholar
• Birnbaum, L. (1969). On the importance of different elements in a multielement system. Multivariate analysis. Academic Press, 2, 581–592.
   Google Scholar
• Borgonovo, E. (2007). Differential, criticality and Birnbaum importance measures: An application to basic event, groups and SSCs in event trees and binary decision diagrams. IEEE Transactions on Reliability, 92(10), 1458–1467.
   Google Scholar
• Borgonovo, E. (2010). The reliability importance of components and prime implicants in coherent and non-coherent systems including total-order interactions. European Journal of Operational Research, 204(3), 485–495.
   Web of Science ®Google Scholar
• Borgonovo, E., Marseguerra, M., & Zio, E. (2000). A Monte Carlo methodological approach to plant availability modeling with maintenance, aging and obsolescence. Reliability Engineering & System Safety, 67(1), 61–73.
   Web of Science ®Google Scholar
• Bouvard, K., Artus, S., Bérenguer, C., & Cocquempot, V. (2011). Condition-based dynamic maintenance operations planning & grouping. Application to commercial heavy vehicles. Reliability Engineering & System Safety, 96(6), 601–610.
   Web of Science ®Google Scholar
• Castanier, B., Grall, A., & Bérenguer, C. (2005). A condition-based maintenance policy with non-periodic inspections for a two-unit series system. Reliability Engineering & System Safety, 87(1), 109–120.
   Web of Science ®Google Scholar
• Chen, C.-T., Chen, Y.-W., & Yuan, J. (2003). On a dynamic preventive maintenance policy for a system under inspection. Reliability Engineering & System Safety, 80(1), 41–47.
   Web of Science ®Google Scholar
• Cheng, J. (2010). Condition based maintenance optimization for multi-component systems based on neural network health prediction ( published M.A. Sc. dissertation). Concordia University, Dept. of Engineering and Computer Science, Montreal, Quebec, Canada.
   Google Scholar
• Cho, D., & Parlar, M. (1991). A survey of maintenance models for multi-unit systems. European Journal of Operational Research, 51(1), 1–23.
   Web of Science ®Google Scholar
• Coit, D.W., & Jin, T. (2000). Gamma distribution parameter estimation for field reliability data with missing failure times. IIE Transactions, 32(12), 1161–1166.
   Web of Science ®Google Scholar
• Cui, L., Xie, M., & Loh, H.-T. (2004). Inspection schemes for general systems. IIE Transactions, 36(9), 817–825.
   Web of Science ®Google Scholar
• Dasgupta, A., & Pecht, M. (1991). Material failure mechanisms and damage models. IEEE Transactions on Reliability, 40(5), 531–536.
   Web of Science ®Google Scholar
• Dekker, R., Wildeman, R., & Van Egmond, R. (1996). Joint replacement in an operational planning phase. European Journal of Operational Research, 91(1), 74–88.
   Web of Science ®Google Scholar
• Dieulle, L., Bérenguer, C., Grall, A., & Roussignol, M. (2001). Continuous time predictive maintenance scheduling for a deteriorating system. IEEE Proceedings of the Annual Reliability and Maintainability Symposium (pp. 150–155). Philadelphia, PA: IEEE.
   Google Scholar
• Do Van, P., Barros, A., & Bérenguer, C. (2008). Reliability importance analysis of markovian systems at steady state using perturbation analysis. Reliability Engineering & System Safety, 93(11), 1605–1615.
   Web of Science ®Google Scholar
• Do Van, P., Barros, A., & Bérenguer, C. (2010). From differential to difference importance measures for Markov reliability models. European Journal of Operational Research, 204(3), 513–521.
   Web of Science ®Google Scholar
• Do Van, P., Barros, A., Bérenguer, C., Bouvard, K., & Brissaud, F. (2013). Dynamic grouping maintenance strategy with time limited opportunities. Reliability Engineering and System Safety, 120, 51–59.
   Web of Science ®Google Scholar
• Do Van, P., & Bérenguer, C. (2012). Condition-based maintenance with imperfect preventive repairs for a deteriorating production system. Reliability and Quality Engineering International, 28(6), 624–633.
   Web of Science ®Google Scholar
• Egeland, T. (1991). Two trends in reliability. Structural Safety, 9(4), 261–268.
   Web of Science ®Google Scholar
• Ge, E.S., Li, Q.M., & Huang, A.L. (2012). Optimization of condition-based maintenance policy for deteriorating system based on Monte-Carlo simulation. Advanced Materials Research, 544, 44–48.
   Google Scholar
• Grall, A., Dieulle, L., Bérenguer, C., & Roussignol, M. (2002). Continuous-time predictive-maintenance scheduling for a deteriorating system. IEEE Transactions on Reliability, 51(2), 141–150.
   Web of Science ®Google Scholar
• Gupta, A., & Lawsirirat, C. (2006). Strategically optimum maintenance of monitoring-enabled multi-component systems using continuous-time jump deterioration models. Journal of Quality in Maintenance Engineering, 12(3), 306–329.
   Google Scholar
• Haurie, A., & L’Ecuyer, P. (1982). A stochastic control approach to group preventive replacements in multi-component systems. IEEE Transactions on Automatic Control, 27, 387–93.
   Web of Science ®Google Scholar
• Hong, J.S., & Lie, C.H. (1993). Joint reliability-importance of two edges in an undirected network. IEEE Transactions on Reliability, 42(1), 17–23.
   Web of Science ®Google Scholar
• Huynh, K.T., Barros, A., and Bérenguer, C. (2013). A reliability-based opportunistic predictive maintenance model for k-out-of-n deteriorating systems. Chemical Engineering Transactions, 33, 493–498.
   Google Scholar
• Huynh, K.T., Barros A., Bérenguer, C., & Castro, I.T. (2011). A periodic inspection and replacement policy for systems subject to competing failure modes due to degradation and traumatic events. Reliability Engineering & System Safety, 96(4), 497–508.
   Web of Science ®Google Scholar
• Huynh, K.T., Castro I.T., Barros A., & Bérenguer, C. (2014). On the use of mean residual life as a condition index for condition-based maintenance decision-making. IEEE Transactions on Systems, 44(7), 877–893.
   Web of Science ®Google Scholar
• Jardine, A., Lin, D., & Banjevic, D. (2006). A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical systems and Signal Processing, 20(7), 1483–1510.
   Web of Science ®Google Scholar
• Jeong, I.J., Leon, V.J., & Villalobos, J.R. (2007). Integrated decision-support system for diagnosis, maintenance planning, and scheduling of manufacturing systems. International Journal of Production Research, 45(2), 267–285.
   Web of Science ®Google Scholar
• Jia, Q.-S. (2010). A structural property of optimal policies for multi-component maintenance problems. IEEE Transactions on Automation Science and Engineering, 7(3), 677–680.
   Web of Science ®Google Scholar
• Kabir, A.B.M.Z., & Farrash, S.H.A. (1996). Simulation of an integrated age replacement and spare provisioning policy using SLAM. Reliability Engineering & System Safety, 52(2), 129–138.
   Web of Science ®Google Scholar
• Kulshrestha, D. (1968). Operational behaviour of a multicomponent system having stand-by redundancy with opportunistic reparis. Unternehmensforschung, 12(1), 159–172.
   Google Scholar
• Le Son, K., Fouladirad, M., Barros, A., Levrat, E., & Iung, B. (2013). Remaining useful life estimation based on stochastic deterioration models: A comparative study. Reliability Engineering & System Safety, 112, 165–175.
   Web of Science ®Google Scholar
• Letot, C., & Dehombreux, P. (2012). Dynamic reliability degradation based models and maintenance optimization. In Proceedings of the 9th National Congress on Theoretical and Applied Mechanics (NCTAM2012). Brussels, 09–10 May 2012.
   Google Scholar
• Levitin, G., & Lisnianski, A. (1999). Importance and sensitivity analysis of multi-state systems using the universal generating function method. Reliability Engineering & System Safety, 65(3), 271–282.
   Web of Science ®Google Scholar
• Lewis, S.A., & Edwards, T.G. (1997). Smart sensors and system health management tools for avionics and mechanical systems. In 16th Digital avionics systems conference (2, pp. 1–7). Irvine, CA, USA.
   Google Scholar
• Lu, H., Kolarik, W.J., & Lu, S.S. (2001). Real-time performance reliability prediction. IEEE Transactions on Reliability, 50(4), 353–357.
   Web of Science ®Google Scholar
• Marseguerra, M., Zio, E., & Podofillini, L. (2002). Condition-based maintenance optimization by means of genetic algorithms and Monte Carlo simulation. Reliability Engineering & System Safety, 77(2), 151–165.
   Web of Science ®Google Scholar
• Moinzadeh, K., & Schmidt, C.P. (1991). An (s-1, s) inventory system with emergency orders. Operations Research, 39(2), 308–321.
   Web of Science ®Google Scholar
• Moustafa, M.S., Maksoud, E.Y., & Sadek, S. (2004). Optimal major and minimal maintenance policies for deteriorating systems. Reliability Engineering & System Safety, 83(3), 363–368.
   Web of Science ®Google Scholar
• Nguyen, K.-A., Do Van, P., & Grall, A. (2013). A predictive maintenance strategy for multi-component systems using importance measure. In Annual Conference of the European Safety and Reliability Conference, ESREL (pp. 967–975). Amsterdam, Netherlands, 2013, 29 September–02 October. London: Taylor & Francis Group.
   Google Scholar
• Nicolai, R.P., & Dekker, R. (2008). Optimal maintenance of multi-component systems: A review. Complex System Maintenance Handbook (pp. 263–286). London: Springer.
   Google Scholar
• Ponchet, A., Fouladirad, M., & Grall, A. (2011). Maintenance policy on a finite time span for a gradually deteriorating system with imperfect improvements. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 225(2), 105–116.
   Web of Science ®Google Scholar
• Rausand, M., & Høyland, A. (2004). System reliability theory: Models, statistical methods and applications (2nd ed. ). New Jersey: John Wiley & Sons.
   Google Scholar
• Ross, S.M. (1996). Stochastic processes. New York, NY: John Wiley & Sons.
   Google Scholar
• Sarker, R., & Haque, A. (2000). Optimization of maintenance and spare provisioning policy using simulation. Applied Mathematical Modelling, 24(10), 751–760.
   Web of Science ®Google Scholar
• Tian, Z., & Liao, H. (2011). Condition based maintenance optimization for multi-component systems using proportional hazards model. Reliability Engineering & System Safety, 96(5), 581–589.
   Web of Science ®Google Scholar
• van der Borst, M., & Schoonakker, H. (2001). An overview of PSA importance measures. Reliability Engineering & System Safety, 72(3), 241–245.
   Web of Science ®Google Scholar
• Van Horenbeek, A., & Pintelon, L. (2013). A dynamic predictive maintenance policy for complex multi-component systems. Reliability Engineering & System Safety, 120, 39–50.
   Web of Science ®Google Scholar
• Van Noortwijk, J.M. (2009). A survey of the application of gamma processes in maintenance. Reliability Engineering & System Safety, 94(1), 2–21.
   Web of Science ®Google Scholar
• Vasseur, D., & Llory, M. (1999). International survey on psa figures of merit. Reliability Engineering & System Safety, 66(3), 261–274.
   Web of Science ®Google Scholar
• Vu, H.-C., Do, P., Barros, A., & Bérenguer, C. (2014). Maintenance planning and dynamic grouping for multi-component systems with positive and negative economic dependencies. IMA Journal of Management Mathematics, doi:10.1093/imaman/dpu007.
   Google Scholar
• Wang, L., Chu, J., & Mao, W. (2008). A condition-based order-replacement policy for a single-unit system. Applied Mathematical Modelling, 32(11), 2274–2289.
   Web of Science ®Google Scholar
• Wang, L., Chu, J., & Mao, W. (2009). A condition-based replacement and spare provisioning policy for deteriorating systems with uncertain deterioration to failure. European Journal of Operational Research, 194(1), 184–205.
   Web of Science ®Google Scholar
• Yang, Y., & Klutke, G.-A. (2000). Improved inspection schemes for deteriorating equipment. Probability in the Engineering and Informational Sciences, 14(4), 445–460.
   Web of Science ®Google Scholar
• Yang, Y., & Klutke, G.-A. (2001). A distribution-free lower bound for availability of quantile-based inspection schemes. IEEE Transactions on Reliability, 50(4), 419–421.
   Web of Science ®Google Scholar
• Yuan, X. (2007). Stochastic modeling of deterioration in nuclear power plant component ( Unpublished Ph.D. dissertation). University of Waterloo, Dept. of Civil Engineering, Ontario, Canada.
   Google Scholar