An improved FMECA for feed system of CNC machining center based on ICR and DEMATEL method

  • Xiaofeng Wang
  • Yingzhi Zhang
  • Guixiang Shen


The Failure Mode, Effects and Criticality Analysis (FMECA) has been widely applied in the reliability research of machining centers in recent years. However, conventional FMECA does not take opinions of different team members or the relationship between the modes and causes of failure into account when considering the assignment of criticality. Thus, an improved FMECA (IFMECA) is proposed to overcome the disadvantages. The IFMECA method applied group decision-making theory to effectively combine every team member’s evaluation. Subsequently, weights of the factors were determined based on the combination of entropy and expert evaluation. Failures were then prioritized by decision-making trial and evaluation laboratory (DEMATEL) method. In this paper, improved criticalities (ICR) were calculated and failures of feed systems were prioritized by IFMECA based on the failure data of the feed system. According to the rank of failure modes obtained through IFMECA, it is observed that vibration or oscillation, motion parts output failure, and inaccurate re-home have more negative impacts on the feed system. Furthermore, this paper asserts that IFMECA method could also be applied to analyze other complex mechanical systems.


FMECA Group decision-making DEMATEL Feed system 


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  1. 1.
    Ben-Daya M, Raouf A (1996) A revised failure mode and effects analysis model. Int J Qual Reliab Manag 13(1):43–47CrossRefGoogle Scholar
  2. 2.
    Gilchrist W (1993) Modelling failure modes and effect analysis. Int J Qual Reliab Manag 10(5):16–23CrossRefGoogle Scholar
  3. 3.
    US Department of Defence (1984) Procedures for performing a failure mode effects and criticality analysis. Department of Defence (USA) MIL-STD-1629Google Scholar
  4. 4.
    Ford Motor Company (1988) Potential failure mode and effects analysis in design (Design FMEA) and for manufacturing and assembly processes (Process FMEA) instruction manual. Ford Motor Company, DearbornGoogle Scholar
  5. 5.
    European Cooperation for Space Standardization (2001) Failure modes, effects and criticality analysis. European Cooperation for Space Standardization ECSS-Q-30-02AGoogle Scholar
  6. 6.
    Wang J, Ruxton T, Labrie CR (1995) Design for safety of engineering systems with multiple failure state variables. Reliab Eng Syst Saf 50:271–284CrossRefGoogle Scholar
  7. 7.
    Sankar NR, Prabhu BS (2001) Modified approach for prioritization of failures in a system failure mode and effects analysis. Int J Qual Reliab Manag 18(3):324–335CrossRefGoogle Scholar
  8. 8.
    Bowles JB, Peláez CE (1995) Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis. Reliab Eng Syst Saf 50:203–213CrossRefGoogle Scholar
  9. 9.
    Anand P, Jin W (2003) Modified failure mode and effects analysis using approximate reasoning. Reliab Eng Syst Saf 79(1):69–85CrossRefGoogle Scholar
  10. 10.
    Zeshan K, Tim PK (2007) Using fuzzy self-organising maps for safety critical systems. Reliab Eng Syst Saf 92:1563–1583CrossRefGoogle Scholar
  11. 11.
    Seyed-Hosseini SM, Safaei N (2006) Reprioritization of failures in a system failure mode and effects analysis by decision making trial and evaluation laboratory technique. Reliab Eng Syst Saf 91:872–881CrossRefGoogle Scholar
  12. 12.
    Haibo Z, Yazhou J (2004) Failure Mode, Effects and Criticality Analysis (FMECA) of CNC system. China Mech Eng 15:491–493Google Scholar
  13. 13.
    Wang YQ, Jia YZ, Jiang WW (2001) Early failure analysis of machining centers: a case study. Reliab Eng Syst Saf 72:91–97CrossRefGoogle Scholar
  14. 14.
    Chryssolouris G (1987) MADEMA: an approach to intelligent manufacturing systems. CIM Rev 3(3):11–17Google Scholar
  15. 15.
    Braglia M, Frosolini M, Montanari R (2003) Fuzzy TOPSIS approach for failure mode, effects and criticality analysis. Qual Reliab Eng Int 19:425–443CrossRefGoogle Scholar
  16. 16.
    Borda JC (1781) Mémoire sur les Élections au Scrutin. Histoire de l’Académie Royale de Science ParisGoogle Scholar
  17. 17.
    Condorcet M (1785) Essai sur l’application de l’analyse à la probabilité des décisions rendues à la pluralité des voies. Imprimante Royale ParisGoogle Scholar
  18. 18.
    Arrow KJ (1951) Social choice and individual values. Wiley, New YorkzbMATHGoogle Scholar
  19. 19.
    Khaled J (2007) An ordinal sorting method for group decision-making. Eur J Oper Res 180:1272–1289CrossRefzbMATHGoogle Scholar
  20. 20.
    Tsiporkova E, Boeva V (2006) Multi-step ranking of alternatives in a multi-criteria and multi-expert decision making environment. Inf Sci 176(18):2673–2697CrossRefMathSciNetzbMATHGoogle Scholar
  21. 21.
    Bryan LB, Michael RB, Reeshad SD (2002) The effects of member expertise on group decision-making and performance. Organ Behav Hum Decis Process 88:719–736CrossRefGoogle Scholar
  22. 22.
    Chin KS, Wang YM, Poon GKK, Yang JB (2009) Failure mode and effects analysis using a group-based evidential reasoning approach. Comput Oper Res 36:1768–1779CrossRefzbMATHGoogle Scholar
  23. 23.
    Claude ES (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423CrossRefGoogle Scholar
  24. 24.
    Zhu AM, Yu LJ (2000) Application of entropy- fuzzy evaluation method to selection of talent. J Shenyang Univ Technol 22:69–70Google Scholar
  25. 25.
    Fontela E, Gabus A (1976) The DEMATEL observer, DEMATEL 1976 report. Battelle Geneva Research Center, GenevaGoogle Scholar
  26. 26.
    Jia YZ, Cheng XM, Jia ZX (1997) Failure mode analysis of machining centers. Proceedings of the Third ISSAT International Conference Reliability and quality in design, California, USA 74–76Google Scholar
  27. 27.
    Dhouib K, Gharbi A, Landolsi N (2010) Availability modelling and analysis of multi-product flexible transfer lines subject to random failures. Int J Adv Manuf Technol 78:139–152Google Scholar
  28. 28.
    Moradi E, Zandieh M (2010) Minimizing the makespan and the system unavailability in parallel machine scheduling problem: a similarity-based genetic algorithm. Int J Adv Manuf Technol 51:829–840CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  1. 1.College of Construction EngineeringJilin UniversityChangchunChina
  2. 2.College of Mechanical EngineeringJilin UniversityChangchunChina

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