A value-based maintenance optimization method for failure prevention based on reliability modeling of a hybrid assembly system

  • Yinhua Liu
  • Shiming Zhang
  • Xialiang Ye


The effective maintenance policy for the fixtures of the assembly system will guarantee good process capability and product quality to a great extent. Traditional maintenance schedules for the assembly system, such as a constant reliability index as the maintenance trigger, are always based on the fixed maintenance threshold in engineering practice. It always results in down time of the process, unqualified products or the excessive maintenance costs. The aim of this paper is to present a method to optimize the maintenance schedules for a serial-parallel hybrid assembly system. Based on the production chain definition of the hybrid system, a reliability evaluation method by integrating the process performance of the hybrid assembly system and product qualities is proposed. On the basis of the reliability method, a value-based preventive maintenance optimization policy for the fixture components is presented to prevent system failures. Compared with the traditional reliability threshold method for maintenance, the proposed maintenance method generates more value on the premise that the system status and product quality are guaranteed. A case study is used to illustrate the proposed method and validate the effectiveness and advantages.


Preventive maintenance Assembly system Fixture component Product quality Reliability 


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This project is supported by the National Natural Science Foundation of China (Grant No. 51405299) and Natural Science Foundation of Shanghai (Grant No. 14ZR1428700).


  1. 1.
    Sayed MS, Lohse N (2014) Ontology-driven generation of Bayesian diagnostic models for assembly systems. Int J Adv Manuf Tech 74(5–8):1033–1052. CrossRefGoogle Scholar
  2. 2.
    Du S, Xi L, Yu J, Sun J (2010) Online intelligent monitoring and diagnosis of aircraft horizontal stabilizer assemble processes. Int J Adv Manuf Tech 50(1–4):377–389. CrossRefGoogle Scholar
  3. 3.
    Zhao Y (2003) On preventive maintenance policy of a critical reliability level for system subject to degradation. Reliab Eng Syst Saf 79(3):301–308. CrossRefGoogle Scholar
  4. 4.
    Bris R, Chelet E, Yalaoui F (2003) New method to minimize the preventive maintenance cost of series–parallel systems. Reliab Eng Syst Saf 82(3):247–255. CrossRefGoogle Scholar
  5. 5.
    Liu Y, Ye X, Ji F, Zheng S, Jin S (2016) Dynamic maintenance plan optimization of fixture components for a multistation autobody assembly process. Int J Adv Manuf Tech 85(9–12):2703–2714. CrossRefGoogle Scholar
  6. 6.
    Wang JM, Huang M, Yi J, Liu XJ (2015) The study of process reliability of aircraft engine. Proc Eng 99:835–839CrossRefGoogle Scholar
  7. 7.
    Wesley JH, Alexander U (2008) Current computational trends in equipment prognostics. Int J Comput Int Sys 1(1):94–102. CrossRefGoogle Scholar
  8. 8.
    Tripathy PK, Majhi PR (2003) An EOQ model with process reliability considerations. J Oper Res Soc 54(5):549–554. CrossRefzbMATHGoogle Scholar
  9. 9.
    Dardalhon MF, Pressecq (1999) Evaluation of process reliability with micromechanical test structures. Sensor Actuat A-Phys 74(3):126–133Google Scholar
  10. 10.
    Jin J, Chen Y (2001) Quality and reliability information integration for design evaluation of fixture system reliability. Qua Reliab Eng Int 17(5):355–372. CrossRefGoogle Scholar
  11. 11.
    Bell SA, Percy DF (2012) Modeling uncertainty in preventive maintenance scheduling. Qua Reliab Eng Int 28(6):604–615Google Scholar
  12. 12.
    Lin G (2005) Process reliability assessment with a Bayesian approach. Int J Adv Manuf Tech 25(3–4):392–395. CrossRefGoogle Scholar
  13. 13.
    Pearn WL, Lin G (2002) Estimated incapability index: reliability and decision making with sample information. Qua Reliab Eng Int 18(2):141–147. CrossRefGoogle Scholar
  14. 14.
    Zhang F, Lu J, Yan Y, Tang S, Meng C (2011) Dimensional quality oriented reliability modeling for complex manufacturing processes. Int J Comput Int 4(6):1262–1268. CrossRefGoogle Scholar
  15. 15.
    Chen Y, Jin J, Shi J (2004) Integration of dimensional quality and locator reliability in design and evaluation of multi-station body-in-white assembly processes. IIE Trans 36(9):827–839. CrossRefGoogle Scholar
  16. 16.
    Chen Y, Jin J (2005) Quality–reliability chain modeling for system–reliability analysis of complex manufacturing processes. IEEE Trans Reliab 54(3):475–488. CrossRefGoogle Scholar
  17. 17.
    Liu Y, Lin P, Li Y, Huang H (2015) Bayesian reliability and performance assessment for multi-state systems. Reliab, IEEE Trans Reliab 64(1):394–409. CrossRefGoogle Scholar
  18. 18.
    Lin Y, Chang P (2013) Reliability-based performance indicator for a manufacturing network with multiple production lines in parallel. J Manuf Syst 32(1):147–153. CrossRefGoogle Scholar
  19. 19.
    Lin L, You M, Ni J (2009) Reliability-based dynamic maintenance threshold for failure prevention of continuously monitored degrading systems. J Manuf Sci Eng Trans ASME 131(3):031010(1-9)Google Scholar
  20. 20.
    Chang C (2014) Optimum preventive maintenance policies for systems subject to random working times, replacement, and minimal repair. Comput Ind Eng 67(1):185–194. CrossRefGoogle Scholar
  21. 21.
    Xia T, Xi L, Zhou X, Lee J (2012) Dynamic maintenance decision-making for series-parallel manufacturing system based on MAM-MTW methodology. Eur J Oper Res 221(1):231–240. CrossRefzbMATHGoogle Scholar
  22. 22.
    Ni J, Gu X, Jin X (2015) Preventive maintenance opportunities for large production systems. Eur J CIRP ANN-Manuf Techn 64(1):447–450. CrossRefGoogle Scholar
  23. 23.
    Tsai Y, Wang K, Tsai L (2004) A study of availability-centered preventive maintenance for multi-component systems. Reliab Eng Syst Safe 84(3):261–270. CrossRefGoogle Scholar
  24. 24.
    Xia T, Xi L, Zhou X, Pan E (2010) Optimization of multi-objective preventive maintenance for series-parallel deteriorating systems. Comput Integr Manuf 16(4):783–788Google Scholar
  25. 25.
    Bouvard K, Artus S, Bérenguer C, Cocquempot V (2011) Condition-based dynamic maintenance operations planning & grouping. Application to commercial heavy vehicles. Reliab Eng Syst Saf 96(6):601–610. CrossRefGoogle Scholar
  26. 26.
    Chiachio J, Chiachio M, Sankararaman S, Saxena A, Kai G (2015) Condition-based prediction of time-dependent reliability in composites. Reliab Eng Syst Saf 142:134–147. CrossRefGoogle Scholar
  27. 27.
    Wang G, Zhang Y (2013) Optimal repair-replacement policies for a system with two types of failures. Eur J Oper Res 226(3):500–506. MathSciNetCrossRefzbMATHGoogle Scholar
  28. 28.
    Liu B, Xu Z, Xie M, Kuo W (2014) A value-based preventive maintenance policy for multi-component system with continuously degrading components. Reliab Eng Syst Saf 132:83–89. CrossRefGoogle Scholar
  29. 29.
    Xia T, Huang K, Xi L, Zhou X, Lee J (2015) Preventive maintenance modeling for multi-component systems with considering stochastic failures and disassembly sequence. Reliab Eng Syst Safe 142:231–237CrossRefGoogle Scholar
  30. 30.
    Fitouhi MC, Nourelfath M (2014) Integrating noncyclical preventive maintenance scheduling and production planning for multi-state systems. Reliab Eng Syst Safe 121(1):175–186. CrossRefGoogle Scholar
  31. 31.
    Lin Y, Chang P, Chen JC (2013) Performance evaluation for a footwear manufacturing system with multiple production lines and different station failure rates. Int J Prod Res 51(5):1603–1617. CrossRefGoogle Scholar
  32. 32.
    Xia T, Jin X, Xi L, Zhang Y, Ni J (2015) Operating load based real-time rolling grey forecasting for machine health prognosis in dynamic maintenance schedule. J Intell Manuf 26(2):269–280. CrossRefGoogle Scholar
  33. 33.
    Sun J, Xi L, Du S, Ju B (2008) Reliability modeling and analysis of serial-parallel hybrid multi-operational manufacturing system considering dimensional quality, tool degradation and system configuration. Int J Prod Econ 114(1):149–164. CrossRefGoogle Scholar

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© Springer-Verlag London Ltd., part of Springer Nature 2017

Authors and Affiliations

  1. 1.School of Mechanical EngineeringUniversity of Shanghai for Science and TechnologyShanghaiChina

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