Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

Multi-phase sequential preventive maintenance scheduling for deteriorating repairable systems

  • Published:
Journal of Intelligent Manufacturing Aims and scope Submit manuscript

Abstract

In this paper, we present a novel multi-phase sequential preventive maintenance (PM) model with multiple maintenance objectives for repairable mechanical systems under deterioration. Although sequential PM scheduling has appeared in literature, conventionally the length of time between maintenance events in the later of replacement process changes very frequently, which has led to poor operability in practice, and has consequently brought a great challenge for maintenance managers. To solve this problem, the concept of multiple phases sequential PM, in which the replacement cycle is divided into several phases, each with equal PM intervals, is proposed to make the policy more suitable in practical applications. A new relationship between cost and maintenance quality, which considers the age reduction factor as a function of maintenance cost and system age, is established to describe the effect of maintenance. The maintenance modeling and optimizing problems are formulated using a multi-attribute value model (MAVM) and a computation algorithm is presented to find the optimum solution. A case study of examining equipment is presented to illustrate the performance of the proposed policy. A comparison with other methods is given to illustrate the effectiveness of our approach. Finally, a sensitivity analysis is performed on the optimality of the maintenance schedule based on related parameters.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Behzadian, M., Otaghsara, S. K., Yazdani, M., & Ignatius, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with Applications, 39(17), 13051–13069.

    Article  Google Scholar 

  • Block, H. W., Borges, W. S., & Savits, T. H. (1985). Age-dependent minimal repair. Journal of Applied Probability, 20(4), 370–385.

    Article  Google Scholar 

  • Brown, M., & Proschan, F. (1983). Imperfect repair. Journal of Applied Probability, 20(4), 851–859.

    Article  Google Scholar 

  • Canfield, R. V. (1986). Cost optimization of periodic preventive maintenance. IEEE Transactions on Reliability, 35(1), 78–81.

    Article  Google Scholar 

  • Cassady, C. R., Murdock, W. P., & Pohl, E. A. (2001). Selective maintenance for support equipment involving multiple maintenance actions. European Journal of Operational Research, 129(2), 252–258.

    Article  Google Scholar 

  • Christer, A. (1999). Developments in delay time analysis for modelling plant maintenance. The Journal of the Operational Research Society, 50(11), 1120–1137. doi:10.2307/3010083.

    Article  Google Scholar 

  • Christer, A. H., Wang, W., Baker, R. D., & Sharp, J. (1995). Modelling maintenance practice of production plant using the delay-time concept. IMA Journal of Management Mathematics, 6(1), 67–83.

    Article  Google Scholar 

  • Dao, C. D., Zuo, M. J., & Pandey, M. (2014). Selective maintenance for multi-state seriesparallel systems under economic dependence. Reliability Engineering & System Safety, 121, 240–249.

    Article  Google Scholar 

  • Dekker, R. (1996). Applications of maintenance optimization models: A review and analysis. Reliability Engineering & System Safety, 51(3), 229–240.

    Article  Google Scholar 

  • Deng, C., Wu, J., & Shao, X. (2016). Research on eco-balance with LCA and LCC for mechanical product design. The International Journal of Advanced Manufacturing Technology, 87(5–8), 1217–1228.

    Article  Google Scholar 

  • Doostparast, M., Kolahan, F., & Doostparast, M. (2014). A reliability-based approach to optimize preventive maintenance scheduling for coherent systems. Reliability Engineering & System Safety, 126, 98–106.

    Article  Google Scholar 

  • Duan, C., Deng, C., & Wang, B. (2017). Optimal multi-level condition-based maintenance policy for multi-unit systems under economic dependence. The International Journal of Advanced Manufacturing Technology, 91(9), 4299–4312. doi:10.1007/s00170-017-0100-0.

    Article  Google Scholar 

  • Finkelstein, M. (2008). Failure rate modelling for reliability and risk. London: Springer Science & Business Media.

    Google Scholar 

  • Gao, Q., Kammer, A. S., Zalluhoglu, U., & Olgac, N. (2015). Critical effects of the polarity change in delayed states within an LTI dynamics with multiple delays. IEEE Transactions on Automatic Control, 60(11), 3018–3022.

    Article  Google Scholar 

  • Gao, Q., & Olgac, N. (2016). Determination of the bounds of imaginary spectra of LTI systems with multiple time delays. Automatica, 72, 235–241.

    Article  Google Scholar 

  • Gao, Q., & Olgac, N. (2017). Stability analysis for LTI systems with multiple time delays using the bounds of its imaginary spectra. Systems & Control Letters, 102, 112–118.

    Article  Google Scholar 

  • Guneri, A. F., Cengiz, M., & Seker, S. (2009). A fuzzy ANP approach to shipyard location selection. Expert Systems with Applications, 36(4), 7992–7999.

    Article  Google Scholar 

  • Huang, Y. S., Chang, W. C., Li, W. H., & Lin, Z. L. (2013). Aggregation of utility-based individual preferences for group decision-making. European Journal of Operational Research, 229(2), 462–469.

    Article  Google Scholar 

  • Jardine, A. K., 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.

    Article  Google Scholar 

  • Jiang, R., & Ji, P. (2002). Age replacement policy: A multi-attribute value model. Reliability Engineering & System Safety, 76(3), 311–318.

    Article  Google Scholar 

  • Khatab, A., & Aghezzaf, E. H. (2016). Selective maintenance optimization when quality of imperfect maintenance actions are stochastic. Reliability Engineering & System Safety, 150, 182–189.

    Article  Google Scholar 

  • Kijima, M., Morimura, H., & Suzuki, Y. (1988). Periodical replacement problem without assuming minimal repair. European Journal of Operational Research, 37(2), 194–203.

    Article  Google Scholar 

  • Liao, W., Pan, E., & Xi, L. (2010). Preventive maintenance scheduling for repairable system with deterioration. Journal of Intelligent Manufacturing, 21(6), 875–884.

    Article  Google Scholar 

  • Lie, C. H., & Chun, Y. H. (1986). An algorithm for preventive maintenance policy. IEEE Transactions on Reliability, 35(1), 71–75.

    Article  Google Scholar 

  • Lin, D., Zuo, M. J., & Yam, R. C. (2001). Sequential imperfect preventive maintenance models with two categories of failure modes. Naval Research Logistics, 48(2), 172–183.

    Article  Google Scholar 

  • Liu, Y., & Huang, H. Z. (2010). Optimal selective maintenance strategy for multi-state systems under imperfect maintenance. IEEE Transactions on Reliability, 59(2), 356–367.

    Article  Google Scholar 

  • Malik, M. A. K. (1979). Reliable preventive maintenance scheduling. AIIE Transactions, 11(3), 221–228.

    Article  Google Scholar 

  • Marler, R. T., & Arora, J. S. (2004). Survey of multi-objective optimization methods for engineering. Structural and Multidisciplinary Optimization, 26(6), 369–395.

    Article  Google Scholar 

  • Monghasemi, S., Nikoo, M. R., Fasaee, M. A. K., & Adamowski, J. (2015). A novel multi criteria decision making model for optimizing time cost quality trade-off problems in construction projects. Expert Systems with Applications, 42(6), 3089–3104.

    Article  Google Scholar 

  • Nakagawa, T. (1986). Periodic and sequential preventive maintenance policies. Journal of Applied Probability, 23(02), 536–542.

    Article  Google Scholar 

  • Nakagawa, T. (1988). Sequential imperfect preventive maintenance policies. IEEE Transactions on Reliability, 37(3), 295–298.

    Article  Google Scholar 

  • Ormerod, R. J., & Ulrich, W. (2013). Operational research and ethics: A literature review. European Journal of Operational Research, 228(2), 291–307.

    Article  Google Scholar 

  • Pham, H., & Wang, H. (1996). Imperfect maintenance. European Journal of Operational Research, 94(3), 425–438.

    Article  Google Scholar 

  • Qu, Y., & Wu, S. (2011). Phasic sequential preventive maintenance policy based on imperfect maintenance for deteriorating systems. Journal of Mechanical Engineering, 10, 028.

    Google Scholar 

  • Scarf, P. A. (1997). On the application of mathematical models in maintenance. European Journal of Operational Research, 99(3), 493–506. doi:10.1016/S0377-2217(96)00316-5.

    Article  Google Scholar 

  • Tang, D., Makis, V., Jafari, L., & Yu, J. (2015a). Optimal maintenance policy and residual life estimation for a slowly degrading system subject to condition monitoring. Reliability Engineering & System Safety, 134, 198–207.

  • Tang, D., Yu, J., Chen, X., & Makis, V. (2015b). An optimal condition-based maintenance policy for a degrading system subject to the competing risks of soft and hard failure. Computers & Industrial Engineering, 83, 100–110.

  • Vaurio, J. K. (1997). On time-dependent availability and maintenance optimization of standby units under various maintenance policies. Reliability Engineering & System Safety, 56(1), 79–89.

    Article  Google Scholar 

  • Veber, B., Nagode, M., & Fajdiga, M. (2008). Generalized renewal process for repairable systems based on finite Weibull mixture. Reliability Engineering & System Safety, 93(10), 1461–1472.

    Article  Google Scholar 

  • Wang, H. (2002). A survey of maintenance policies of deteriorating systems. European Journal of Operational Research, 139(3), 11.

    Article  Google Scholar 

  • Wu, S., & Clements-Croome, D. (2005). Preventive maintenance models with random maintenance quality. Reliability Engineering & System Safety, 90(1), 99–105.

    Article  Google Scholar 

  • Yager, R. R. (2004). OWA aggregation over a continuous interval argument with applications to decision making. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 34(5), 1952–1963.

    Article  Google Scholar 

  • Yu, J. (2017). Adaptive hidden Markov model-based online learning framework for bearing faulty detection and performance degradation monitoring. Mechanical Systems and Signal Processing, 83, 149–162.

    Article  Google Scholar 

  • Zhou, X., Xi, L., & Lee, J. (2007). Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation. Reliability Engineering & System Safety, 92(4), 530–534.

    Article  Google Scholar 

Download references

Acknowledgements

The authors are grateful to the Technical Editor and all reviewers for their valuable and constructive comments. The research was supported by China Scholarship Council (CSC); the National Natural Science Foundation of China (NSFC) under Grant Nos. 51375181, 51475189, 51121002; International S&T Coperation Program of China (ISTCP) under Grant No. 2016YFE0121700.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chaoqun Duan.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Duan, C., Deng, C. & Wang, B. Multi-phase sequential preventive maintenance scheduling for deteriorating repairable systems. J Intell Manuf 30, 1779–1793 (2019). https://doi.org/10.1007/s10845-017-1353-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10845-017-1353-z

Keywords