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Optimal CBPM policy considering maintenance effects and environmental condition

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Abstract

The requirement for advanced manufacturing systems and the need to ensure system efficiency and economy have led to an increased emphasis on maintenance policies. However, conventional preventive maintenance (PM) neglects maintenance effects and environmental condition. Hence, a condition-based predictive maintenance (CBPM) policy for intelligent monitored system subjected to degradation is now presented. The aim is to simultaneously optimize two objectives: maximize equipment availability for efficiency and minimize maintenance cost for economy. The multiple attribute value theory is used to determine the optimal PM intervals in different maintenance cycles. Furthermore, a hybrid hazard rate recursion evolution incorporating two improvement factors and the environmental factor is developed. Both maintenance effects and environmental condition are integrated into maintenance scheduling. Finally, through a case study, the analysis shows that the application of CBPM policy results in a noticeable increase in the availability–benefits and the cost–benefits. It indicates that CBPM policy can lead to significant gains by considering maintenance effects and environmental condition.

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References

  1. Tam ASB, Chan WM, Price JWH (2007) Maintenance scheduling to support the operation of manufacturing and production assets. Int J Adv Manuf Technol 34:399–405

    Article  Google Scholar 

  2. Swanson L (1999) The impact of new production technologies on the maintenance function: an empirical study. Int J Prod Res 37:849–869

    Article  MathSciNet  MATH  Google Scholar 

  3. Jenab K, Zolfaghari S (2008) A virtual collaborative maintenance architecture for manufacturing enterprises. J Intell Manuf 19:763–771

    Article  Google Scholar 

  4. Barlow RE, Hunter LC (1960) Optimum preventive maintenance policies. Oper Res 8:90–100

    Article  MathSciNet  MATH  Google Scholar 

  5. Savsar M (2006) Effects of maintenance policies on the productivity of flexible manufacturing cells. Omega Int J Manage Sci 34:274–282

    Article  Google Scholar 

  6. Lai MT, Chen YC (2006) Optimal periodic replacement policy for a two-unit system with failure rate interaction. Int J Adv Manuf Technol 29:367–371

    Article  MathSciNet  Google Scholar 

  7. Sheu SH, Griffith WS (2002) Extended block replacement policy with shock models and used items. Eur J Oper Res 140:50–60

    Article  MathSciNet  MATH  Google Scholar 

  8. Savsar M (2008) Modelling of multi-stage production lines with maintenance operations. Int J Comput Integ M 21:396–406

    Article  Google Scholar 

  9. Badia FG, Berrade MD, Campos CA (2002) Optimal inspection and preventive maintenance of units with revealed and unrevealed failures. Reliab Eng Syst Saf 78:157–163

    Article  Google Scholar 

  10. Halim T, Tang LC (2009) Confidence interval for optimal preventive maintenance interval and its applications in maintenance planning. Int J Adv Manuf Technol 40:203–213

    Article  Google Scholar 

  11. Naderi B, Zandieh M, Ghomi SMTF (2009) Scheduling sequence-dependent setup time job shops with preventive maintenance. Int J Adv Manuf Technol 43:170–181

    Article  Google Scholar 

  12. Feng CXJ, Yu ZG, Kusiak A (2006) Selection and validation of predictive regression and neural network models based on designed experiments. IIE Trans 38:13–23

    Article  Google Scholar 

  13. Shum YS, Gong DC (2007) The application of genetic algorithm in the development of preventive maintenance analytic model. Int J Adv Manuf Technol 32:169–183

    Article  Google Scholar 

  14. Sheu DD, Kuo JY (2006) A model for preventive maintenance operations and forecasting. J Intell Manuf 17:441–451

    Article  Google Scholar 

  15. Pham H, Wang H (1996) Imperfect maintenance. Eur J Oper Res 94:425–438

    MATH  Google Scholar 

  16. Doyen L, Gaudoin O (2004) Classes of imperfect repair models based on reduction of failure intensity or virtual age. Reliab Eng Syst Saf 84:45–56

    Article  Google Scholar 

  17. Zhou X, Xi L, Lee J (2007) Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation. Reliab Eng Syst Saf 92:530–534

    Article  Google Scholar 

  18. Martorell S, Sanchez A, Serradell V (1999) Age-dependent reliability model considering effects of maintenance and working conditions. Reliab Eng Syst Saf 64:19–31

    Article  Google Scholar 

  19. Lee J, Ni J, Djurdjanovic D, Qiu H, Liao H (2006) Intelligent prognostics tools and e-maintenance. Comput Ind 57:476–489

    Article  Google Scholar 

  20. Yu J, Xi L (2009) A hybrid learning-based model for on-line monitoring and diagnosis of out-of-control signals in multivariate manufacturing processes. Int J Prod Res 47:4077–4108

    Article  MATH  Google Scholar 

  21. Jardine AKS, Makis V, Banjevic D, Braticevic D, Ennis M (1998) A decision optimization model for condition-based maintenance. J Qual Maint Eng 4:115–121

    Article  Google Scholar 

  22. Jardine AKS, Joseph T, Banjevic D (1999) Optimizing condition-based maintenance decisions for equipment subject to vibration monitoring. J Qual Maint Eng 5:192–202

    Article  Google Scholar 

  23. Safari E, Sadjadi SJ, Shahanaghi K (2010) Scheduling flowshops with condition-based maintenance constraint to minimize expected makespan. Int J Adv Manuf Technol 46:757–767

    Article  Google Scholar 

  24. Ruiz R, García-Díaz JC, Maroto C (2007) Considering scheduling and preventive maintenance in the flowshop sequencing problem. Comput Oper Res 34:3314–3330

    Article  MATH  Google Scholar 

  25. Naderi B, Zandieh M, Fatemi Ghomi SMT (2009) A study on integrating sequence dependent setup time flexible flow lines and preventive maintenance scheduling. J Intell Manuf 20:683–694

    Article  Google Scholar 

  26. Lee TH (2009) Optimal production run length and maintenance schedule for a deteriorating production system. Int J Adv Manuf Technol 43:959–963

    Article  Google Scholar 

  27. Jayabalan V, Chaudhuri D (1992) Cost optimization of maintenance scheduling for a system with assured reliability. IEEE Trans Reliab 41:21–25

    Article  MATH  Google Scholar 

  28. Pan E, Liao W, Xi L (2010) Single-machine-based production scheduling model integrated preventive maintenance planning. Int J Adv Manuf Technol 50:365–375

    Article  Google Scholar 

  29. Nakagawa T (1988) Sequential imperfect preventive maintenance policies. IEEE Trans Reliab 37:295–298

    Article  MathSciNet  MATH  Google Scholar 

  30. Bartholomew-Biggs M, Zuo MJ, Li X (2009) Modelling and optimizing sequential imperfect preventive maintenance. Reliab Eng Syst Saf 94:53–62

    Article  Google Scholar 

  31. Marseguerra M, Zio E (2000) Optimizing maintenance and repair policies via a combination of genetic algorithms and Monte Carlo simulation. Reliab Eng Syst Saf 68:69–83

    Article  Google Scholar 

  32. Tsai YT, Wang KS, Tsai LC (2004) A study of availability-centered preventive maintenance for multi-component systems. Reliab Eng Syst Saf 84:261–270

    Article  Google Scholar 

  33. Savsar M (2005) Performance analysis of an FMS operating under different failure rates and maintenance policies. Int J Flex Manuf Sys 16:229–249

    Article  MATH  Google Scholar 

  34. Vatn J, Hokstad P, Bodsberg L (1996) An overall model for maintenance optimization. Reliab Eng Syst Saf 51:241–257

    Article  Google Scholar 

  35. Jiang R, Ji P (2002) Age replacement policy: a multi-attribute value model. Reliab Eng Syst Saf 76:311–318

    Article  Google Scholar 

  36. Jung KM, Han SS, Park DH (2008) Optimization of cost and downtime for replacement model following the expiration of warranty. Reliab Eng Syst Saf 93:995–1003

    Article  Google Scholar 

  37. Berrichi A, Amodeo L, Yalaoui F, Châtelet E, Mezghiche M (2009) Bi-objective optimization algorithms for joint production and maintenance scheduling: application to the parallel machine problem. J Intell Manuf 20:389–400

    Article  Google Scholar 

  38. Malik MAK (1979) Reliable preventive maintenance policy. AIIE Trans 11:221–228

    Google Scholar 

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Authors and Affiliations

  1. State Key Laboratory of Mechanical System and Vibration, Industrial Engineering Department, School of Mechanical Engineering, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Shanghai, 200240, China

    Tangbin Xia, Lifeng Xi & Xiaojun Zhou

  2. University of Cincinnati, Cincinnati, 45221–0072, OH, USA

    Jay Lee

Authors
  1. Tangbin Xia
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  2. Lifeng Xi
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  3. Jay Lee
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  4. Xiaojun Zhou
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Correspondence to Tangbin Xia.

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Xia, T., Xi, L., Lee, J. et al. Optimal CBPM policy considering maintenance effects and environmental condition. Int J Adv Manuf Technol 56, 1181–1193 (2011). https://doi.org/10.1007/s00170-011-3235-4

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  • DOI: https://doi.org/10.1007/s00170-011-3235-4

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