Skip to main content
SpringerLink
Log in

An Improved Grey Failure Mode and Effect Analysis for a Steel-Door Industry

  • Research Article-Systems Engineering
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

Failure mode and effect analysis (FMEA) is a method used to detect causes of failures that may occur in a product or process, and FMEA is more important to prevent a failure before existing by computerized controllers in many industries. The control mechanism must have the ability to calculate and interpret the risk priority number (RPN) value for a fault mode. RPN consists of the ratio values of severity, occurrence, and detectability in FMEA for failure prioritization in order to provide a proper mechanism under this uncertain environment. So, this study is to develop a new grey failure mode and effect analysis (GFMEA) approach by combining grey relational analysis (GRA) with the mass gravity theory (MGT). A new RPN calculation technique based on the mass gravity law has been developed by calculating the relationship between the weights of each process for the production process. The problems resolved within the company without reflection to customers and were detected in the next operations for a steel-door manufacturing process. Hence, the new RPN values are more reliable for decision-makers in the process of production and operations management and obtained with efficient solutions for use to computerized FMEA process.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Fattahi, R.; Khalilzadeh, M.: Risk evaluation using a novel hybrid method based on FMEA, extended MULTIMOORA, and AHP methods under fuzzy environment. Saf. Sci. 102, 290–300 (2018)

    Article  Google Scholar 

  2. Dutta, C.B.; Biswas, U.: Failure diagnosis in real time stochastic discrete event systems. Eng. Sci. Technol. Int. J. 18(4), 616–633 (2015)

    Google Scholar 

  3. Bicen, Y.: Propositional logic concept for fault diagnosis in complex systems. Eng. Sci. Technol. Int. J. 23(5), 1068–1073 (2020)

    Google Scholar 

  4. MIL-STD-1629A: Procedures for performing a failure mode effects and criticality analysis, US Department of Defense, Washington, D.C., USA, (1980).

  5. IEC-60812: Analysis techniques for system reliability-procedures for failure mode and effect analysis. In: International Electrotechnical Commission, Geneva, Switzerland, (1985).

  6. QS-9000: ISO 9001:2015 standards. In: International Organization of Standards (ISO), Geneva, Switzerland (2017).

  7. Pillay, A.; Wang, J.: Modified failure mode and effects analysis using approximate reasoning. Reliability Eng. Syst. Safety 79(1), 69–85 (2003)

    Article  Google Scholar 

  8. Geum, Y.; Cho, Y.; Park, Y.: A systematic approach for diagnosing service failure: service-specific FMEA and grey relational analysis approach. Math. Comput. Model. 54(11–12), 3126–3142 (2011)

    Article  Google Scholar 

  9. Xiao, N.; Hong-Zhong, H.; Li, Y.; He, L.; Jin, T.: Multiple failure modes analysis and weighted risk priority number evaluation in FMEA. Eng. Fail. Anal. 18(4), 1162–1170 (2011)

    Article  Google Scholar 

  10. Kutlu, C.; Ekmekçioğlu, M.: Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP. Expert Syst. Appl. 39(1), 61–67 (2012)

    Article  Google Scholar 

  11. Ben-Daya, M.; Raouf, A.: A revised failure mode and effects analysis model. Int. J. Quality Reliab. Manag. 13(1), 43–47 (1996)

    Article  Google Scholar 

  12. Liu, H.-C.; Liu, L.; Liu, N.: Risk evaluation approaches in failure mode and effects analysis: a literature review. Expert Syst. Appl. 40(2), 828–838 (2013)

    Article  Google Scholar 

  13. Bowles, J.B.; Peláez, C.E.: Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis. Reliab. Eng. Syst. Saf. 50(2), 203–213 (1995)

    Article  Google Scholar 

  14. Chang, C.-L.; Liu, P.-H.; Wei, C.-C.: Failure mode and effects analysis using grey theory. Integr. Manuf. Syst. 12(3), 211–216 (2001)

    Article  Google Scholar 

  15. Goyal, S.; Grover, S.: Applying fuzzy grey relational analysis for ranking the advanced manufacturing systems. Grey Syst. Theory Appl. 2(2), 284–298 (2012)

    Article  Google Scholar 

  16. Sofyalioglu, C.: Grey evaluation model of process failure mode effect analysis. Ege Academic Rev. 11(1), 151–164 (2011)

    Google Scholar 

  17. Case, F.; Nor, A.; Teoh, P.C.: A diagnostic service tool using FMEA. Int. J. Comput. Integr. Manuf. 23(7), 640–654 (2010)

    Article  Google Scholar 

  18. Mentes, A.; Ozen, E.: A hybrid risk analysis method for a yacht fuel system safety. Safety Sci. 79, 94–104 (2015)

    Article  Google Scholar 

  19. Chang, K.-H.; Cheng, C.-H.: Evaluating the risk of failure using the fuzzy OWA and DEMATEL method. J. Intell. Manuf. 22(2), 113–129 (2011)

    Article  Google Scholar 

  20. Song, W.; Ming, X.; Wu, Z.; Zhu, B.: Failure modes and effects analysis using integrated weight-based fuzzy TOPSIS. Int. J. Comput. Integr. Manuf. 26(12), 1172–1186 (2013)

    Article  Google Scholar 

  21. Liu, H.-C.; You, J.-X.; Lin, Q.-L.; Li, H.: Risk assessment in system FMEA combining fuzzy weighted average with fuzzy decision-making trial and evaluation laboratory. Int. J. Comput. Integr. Manuf. 28(7), 701–714 (2015)

    Article  Google Scholar 

  22. Zhou, Q.; Thai, V.V.: Fuzzy and grey theories in failure mode and effect analysis for tanker equipment failure prediction. Saf. Sci. 83, 74–79 (2016)

    Article  Google Scholar 

  23. Battirola Filho, J.; Piechnicki, F.; Loures, E.; Santos, E.: Process-aware FMEA framework for failure analysis in maintenance. J. Manuf. Technol. Manag. 28(6), 822–848 (2017)

    Article  Google Scholar 

  24. Can, G.F.: An intutionistic approach based on failure mode and effect analysis for prioritizing corrective and preventive strategies. Human Factors Ergonom. Manuf. Service Ind. 28(3), 130–147 (2018)

    Article  Google Scholar 

  25. Zhao, X.S.; Chen, T.H.; Zhang, K.; Wang, M.-J.J.: Applying an improved failure mode effect analysis method to evaluate the safety of a three-in-one machine tool. Human Fact. Ergonom. Manuf. Service Ind. 30(1), 71–82 (2020)

    Article  Google Scholar 

  26. Teoh, P.C.; Case, K.: An evaluation of failure modes and effects analysis generation method for conceptual design. Int. J. Comput. Integr. Manuf. 18(4), 279–293 (2005)

    Article  Google Scholar 

  27. Puente, J.; Pino, R.; Priore, P.; De La Fuente, D.: A decision support system for applying failure mode and effects analysis. Int. J. Quality Reliab. Manag. 19(2), 137–150 (2002)

    Article  Google Scholar 

  28. Stamatis, D.H.: Failure mode and effect analysis: FMEA from theory to execution, Milwauke. ASQ Quality Press, USA (2003)

    Google Scholar 

  29. Aldridge, J.; Taylor, J.; Dale, B.: The application of failure mode and effects analysis at an automotive components manufacturer. Int. J. Quality Reliab. Manag. 8(3), 44–56 (1991)

    Article  Google Scholar 

  30. Deng, J.: Introduction to grey system theory. J. Grey Syst. 1(1), 1–24 (1989)

    MathSciNet  MATH  Google Scholar 

  31. Aydemir, E.; Bedir, F.; Ozdemir, G.: Degree of greyness approach for an EPQ model with imperfect items in copper wire industry. J. Grey Syst. 27(2), 13–27 (2015)

    Google Scholar 

  32. Liu, S.; Yang, Y.; Xie, N.; Forrest, J.: New progress of Grey system theory in the new millennium. Grey Systems: Theory and Application 6(1), 2–31 (2016)

    Article  Google Scholar 

  33. Wu, H.-H.: A comparative study of using grey relational analysis in multiple attribute decision making problems. Qual. Eng. 15(2), 209–217 (2002)

    Article  Google Scholar 

  34. Kuo, Y.; Yang, T.; Huang, G.-W.: The use of grey relational analysis in solving multiple attribute decision-making problems. Comput. Ind. Eng. 55(1), 80–93 (2008)

    Article  Google Scholar 

  35. Cao, X.; Deng, H.; Lan, W.: Use of the grey relational analysis method to determine the important environmental factors that affect the atmospheric corrosion of Q235 carbon steel. Anti-Corrosion Methods Mater. 62(1), 7–12 (2015)

    Article  Google Scholar 

  36. Dong, W.; Liu, S.; Fang, Z.: On modeling mechanisms and applicable ranges of grey incidence analysis models. Grey Syst. Theory Appl. 8(4), 448–461 (2018)

    Article  Google Scholar 

  37. Xie, N.; Liu, S.: A novel grey relational model based on grey number sequences. Grey Syst. Theory Appl. 1(2), 117–128 (2011)

    Article  Google Scholar 

  38. Spears, W.; Gordon, D.: Using artificial physics to control agents, In: IEEE International Conference on Information, Intelligence, and Systems, Bethesda, MD (1999).

  39. Xie, L.; Zeng, J.; Cui, Z.: General framework of artificial physics optimization algorithm, In: World Congress On Nature & Biologically Inspired Computing (Nabic), Coimbatore, (2009a).

  40. Xie, L.; Zeng, J.; Cui, Z.: On mass effects to artificial physics optimisation algorithm for global optimisation problems. Int. J. Innovative Comput. Appl. 2, 69–76 (2009)

    Article  Google Scholar 

  41. Xie, L.; Zeng, J.: The performance analysis of artificial physics optimization algorithm driven by different virtual forces. ICIC Express Letters 4, 239–244 (2010)

    Google Scholar 

  42. Gorbenko, A.; Popov, V.: Task resource scheduling problem. Int. J. Autom. Comput. 9(4), 429–441 (2012)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Engineering Faculty, Suleyman Demirel University, Isparta, Turkey

    Mehmet Yaşbayır & Erdal Aydemir

Authors
  1. Mehmet Yaşbayır
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Erdal Aydemir
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Erdal Aydemir.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yaşbayır, M., Aydemir, E. An Improved Grey Failure Mode and Effect Analysis for a Steel-Door Industry. Arab J Sci Eng 47, 3789–3803 (2022). https://doi.org/10.1007/s13369-021-06169-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-021-06169-3

Keywords

Search

Navigation