Advertisement

Switching- and hedging- point policy for preventive maintenance with degrading machines: application to a two-machine line

  • Maria Chiara MagnaniniEmail author
  • Tullio Tolio
Article
  • 23 Downloads

Abstract

Maintenance and production are frequently managed as separate activities although they do interact. Disruptive events such as machine failures may find the company unready to repair the machine immediately leading to time waste. Preventive Maintenance may be carried out and maintenance time reduced to the effective task duration, in order to prevent time waste. Companies and researchers have been focusing on policies able to mitigate the impact of Preventive Maintenance on system availability, by exploiting the knowledge about degradation profiles in machines and the joint information from the machine state and the buffer level. In this work, the mathematical proof of the optimal threshold-based control policy for Preventive Maintenance with inventory cost, maintenance cost, backlog cost is provided. The control policy is defined in terms of buffer thresholds and dependency of the thresholds on the degradation condition. The optimal control policy is proved to include a combination of switching points and hedging points, where the first ones activate the Preventive Maintenance for a given condition and the latter ones control the production rate in order to minimize the surplus. An extensive experimental campaign analyzes the impact of system parameters such as the Maintenance duration on the cost function. The results show that there exists cases in which the optimal policy is dominated by the effect of the hedging points or the switching points, alternatively. Therefore, the proposed method is used to provide suggestions to the management for operative decisions, in order to choose the policy fitting best the system.

Keywords

Manufacturing systems Preventive maintenance Stochastic flow model Optimal control policy 

Notes

References

  1. Aghezzaf EH, Najid NM (2008) Integrated production planning and preventive maintenance in deteriorating production systems. Inf Sci 178(17):3382–3392MathSciNetzbMATHCrossRefGoogle Scholar
  2. Aghezzaf EH, Jamali MA, Ait-Kadi D (2007) An integrated production and preventive maintenance planning model. Eur J Oper Res 181(2):679–685zbMATHCrossRefGoogle Scholar
  3. Ambani S, Meerkov SM, Zhang L (2010) Feasibility and optimization of preventive maintenance in exponential machines and serial lines. IIE Trans 42(10):766–777CrossRefGoogle Scholar
  4. Barlow R, Hunter L (1960) Optimum preventive maintenance policies. Oper Res 8(1):90–100MathSciNetzbMATHCrossRefGoogle Scholar
  5. Buzacott JA (1967) Automatic transfer lines with buffer stocks. Int J Prod Res 5(3):183–200CrossRefGoogle Scholar
  6. Buzacott JA, Shanthikumar JG (1993) Stochastic models of manufacturing systems, vol 4. Prentice Hall Englewood Cliffs, NJzbMATHGoogle Scholar
  7. Chen D, Trivedi KS (2005) Optimization for condition-based maintenance with semi-markov decision process. Reliab Eng Syst Saf 90(1):25–29CrossRefGoogle Scholar
  8. Colledani M, Tolio T (2012) Integrated quality, production logistics and maintenance analysis of multi-stage asynchronous manufacturing systems with degrading machines. CIRP Ann Manuf Technol 61(1):455–458CrossRefGoogle Scholar
  9. Colledani M, Tolio T, Fischer A, Iung B, Lanza G, Schmitt R, Váncza J (2014) Design and management of manufacturing systems for production quality. CIRP Ann Manuf Technol 63(2):773–796CrossRefGoogle Scholar
  10. Conway R, Maxwell W, McClain JO, Thomas LJ (1988) The role of work-in-process inventory in serial production lines. Oper Res 36(2):229–241CrossRefGoogle Scholar
  11. Dallery Y, Gershwin SB (1992) Manufacturing flow line systems: a review of models and analytical results. Queueing Syst 12(1–2):3–94zbMATHCrossRefGoogle Scholar
  12. de Jonge B, Teunter R, Tinga T (2017) The influence of practical factors on the benefits of condition-based maintenance over time-based maintenance. Reliab Eng Syst Saf 158:21–30CrossRefGoogle Scholar
  13. Dekker R (1996) Applications of maintenance optimization models: a review and analysis. Reliab Eng Syst Saf 51(3):229–240CrossRefGoogle Scholar
  14. Fitouhi MC, Nourelfath M, Gershwin SB (2017) Performance evaluation of a two-machine line with a finite buffer and condition-based maintenance. Reliab Eng Syst Saf 166:61–72CrossRefGoogle Scholar
  15. Gershwin SB (1994) Manufacturing systems engineering. Prentice Hall, Upper Saddle RiverGoogle Scholar
  16. Groenevelt H, Pintelon L, Seidmann A (1992) Production lot sizing with machine breakdowns. Manag Sci 38(1):104–123zbMATHCrossRefGoogle Scholar
  17. Iravani SM, Duenyas I (2002) Integrated maintenance and production control of a deteriorating production system. Lie Trans 34(5):423–435Google Scholar
  18. Karamatsoukis C, Kyriakidis E (2010) Optimal maintenance of two stochastically deteriorating machines with an intermediate buffer. Eur J Oper Res 207(1):297–308MathSciNetzbMATHCrossRefGoogle Scholar
  19. Kyriakidis E, Dimitrakos TD (2006) Optimal preventive maintenance of a production system with an intermediate buffer. Eur J Oper Res 168(1):86–99MathSciNetzbMATHCrossRefGoogle Scholar
  20. Li J, Meerkov SM (2008) Production systems engineering. Springer, BerlinzbMATHGoogle Scholar
  21. Liberopoulos G, Papadopoulos C, Tan B, Smith J, Gershwin S (2006) Stochastic modeling of manufacturing systems. Springer, GermanyzbMATHCrossRefGoogle Scholar
  22. Meller RD, Kim DS (1996) The impact of preventive maintenance on system cost and buffer size. Eur J Oper Res 95(3):577–591zbMATHCrossRefGoogle Scholar
  23. Nahmias S, Olsen TL (2015) Production and operations analysis. Waveland Press, Long GroveGoogle Scholar
  24. Najid NM, Alaoui-Selsouli M, Mohafid A (2011) An integrated production and maintenance planning model with time windows and shortage cost. Int J Prod Res 49(8):2265–2283zbMATHCrossRefGoogle Scholar
  25. Papadopoulos H, Heavey C (1996) Queueing theory in manufacturing systems analysis and design: a classification of models for production and transfer lines. Eur J Oper Res 92(1):1–27zbMATHCrossRefGoogle Scholar
  26. Pierskalla WP, Voelker JA (1976) A survey of maintenance models: the control and surveillance of deteriorating systems. Naval Res Logist 23(3):353–388MathSciNetzbMATHCrossRefGoogle Scholar
  27. Raouf A (1994) Improving capital productivity through maintenance. Int J Oper Prod Manag 14(7):44–52CrossRefGoogle Scholar
  28. Scarf PA (1997) On the application of mathematical models in maintenance. Eur J Oper Res 99(3):493–506zbMATHCrossRefGoogle Scholar
  29. Song DP (2009) Production and preventive maintenance control in a stochastic manufacturing system. Int J Prod Econ 119(1):101–111CrossRefGoogle Scholar
  30. Swanson L (2001) Linking maintenance strategies to performance. Int J Prod Econ 70(3):237–244CrossRefGoogle Scholar
  31. Tolio TA, Ratti A (2018) Performance evaluation of two-machine lines with generalized thresholds. Int J Prod Res 56(1–2):926–949CrossRefGoogle Scholar
  32. Valdez-Flores C, Feldman RM (1989) A survey of preventive maintenance models for stochastically deteriorating single-unit systems. Naval Res Logist 36(4):419–446MathSciNetzbMATHCrossRefGoogle Scholar
  33. Van der Duyn Schouten F, Vanneste S (1995) Maintenance optimization of a production system with buffer capacity. Eur J Oper Res 82(2):323–338zbMATHCrossRefGoogle Scholar
  34. Van Horenbeek A, Pintelon L (2014) Development of a maintenance performance measurement framework—using the analytic network process (anp) for maintenance performance indicator selection. Omega 42(1):33–46CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Politecnico di MilanoMilanoItaly

Personalised recommendations