Skip to main content
SpringerLink
Log in

A modified method to improve failure analysis

  • Original Article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

Abstract

Failure mode and effects analysis (FMEA) is an effective method that is widely used to manage failures and prevent risks, and, thanks to its simplicity and its versatility, the most important and renowned quality norms request it use. However, in literature, several works have criticized this tool and claims that it had short-comes. The FMEA team members are considered with the same importance and failures values are calculated meaning their judgement and without any differentiation. Moreover, failures modes are supposed to be independent and the effect of their relationship is ignored in the risk analysis. The accuracy of the FMEA analysis is also reduced due to the fact that risk factors are supposed to have the same importance. In this article, we propose to combine FMEA with other methods in order to overcame it limitedness. Firstly, a criteria selection will be proposed in order to select the most relevant factors for risk analysis. Their weights will be calculated using the best worst method (BWM). Secondly, a weight associated to every team member will be calculated and used to obtain failures values. Thirdly, the design structure method (DSM) will be used to identify the relationship between failures and to judge their importance, we propose to use the fuzzy technique for order of preference by similarity method (FTOPSIS). In order to test the applicability and the effectiveness of this method, a case study will be proposed in the end.

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
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Abdelgawad M, Fayek AR (2010) Risk management in the construction industry using combined fuzzy FMEA and fuzzy AHP. J Constr Eng Manag 136(9):1028–1036

    Google Scholar 

  • AIAG (2008) AIAG FMEA-4: potential failure mode and effect analysis (FMEA), 4th edn. The Automotive Division of the American Society for Quality (ASQC) and the Automotive Industry Action Group (AIAG), Southfield

  • Bowles JB (2003) An assessment of RPN prioritization in a failure modes effects and criticality analysis. Reliability and Maintainability Symposium 380–386

  • Braglia M (2000) MAFMA: multi-attribute failure mode analysis. Int J Qual Reliab Manag 17(9):1017–1033

    Google Scholar 

  • Braglia M, Bevilacqua M (2000) Fuzzy modeling and analytic hierarchy processing as a means to quantify risk levels associated with failure modes in production systems. Technol Law Insur 5(3–4):125–134

    Google Scholar 

  • Braglia M, Frosolini M, Montanari R (2003) Fuzzy TOPSIS approach for failure mode, effects and criticality analysis. Qual Reliab Eng Int 19(5):425–443

    Google Scholar 

  • Browning T (2001) Applying the design structure matrix to system decomposition and integration problems: a review and new directions

  • Buckley JJ (1985) Fuzzy hierarchical analysis. Fuzzy Sets Syst 17:233–247

    MathSciNet  MATH  Google Scholar 

  • Can GF (2018) An intutionistic approach based on failure mode and effect analysis for prioritizing corrective and preventive strategies. Hum Factors Ergon Manuf 28(3):130–147

    Google Scholar 

  • Carmignani G (2009) An integrated structural framework to cost-based FMECA: the priority-cost FMECA. Reliab Eng Syst Saf 94(4):861–871

    Google Scholar 

  • Carpitella S, Certa A, Izquierdo J, La Fata CM (2018) A combined multi-criteria approach to support FMECA analyses: a real-world case. Reliab Eng Syst Saf 169:394–402

    Google Scholar 

  • Chang KH (2015) A novel general risk assessment method using the soft TOPSIS approach. J Ind Prod Eng 32(6):408–421

    Google Scholar 

  • Chang DS, Sun KLP (2009) Applying DEA to enhance assessment capability of FMEA. Int J Qual Reliab Manag 26(6):629–643

    Google Scholar 

  • Chen CT (2000) Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114(1):1–9

    MATH  Google Scholar 

  • Danilovic M, Browning TR (2007) Managing complex product development projects with design structure matrices and domain mapping matrices. Int J Project Manag 25(3):300–314

    Google Scholar 

  • Di Bona G, Silvestri A, Forcina A, Petrillo A (2018) Total efficient risk priority number (TERPN): a new method for risk assessment. J Risk Res 21(11):1384–1408

    Google Scholar 

  • Franceschini F, Galetto M (2001) A new approach for evaluation of risk priorities of failure modes in FMEA. Int J Prod Res 39(13):2991–3002

    Google Scholar 

  • Ghoushchi SJ, Yousefi S, Khazaeili M (2018) An extended FMEA approach based on the Z-MOORA and fuzzy BWM for prioritization of failures. Appl Soft Comput 81:105505. https://doi.org/10.1016/j.asoc.2019.105505

    Article  Google Scholar 

  • Helvacioglu S, Ozen E (2014) Fuzzy based failure modes and effect analysis for yacht system design. Ocean Eng 79:131–141

    Google Scholar 

  • Hu AH, Hsu CW, Kuo TC, Wu WC (2009) Risk evaluation of green components to hazardous substance using FMEA and FAHP. Expert Syst Appl 36:7142–7147

    Google Scholar 

  • Hu Y-P, You X-Y, Wang L, Liu H-C (2018) An integrated approach for failure mode and effect analysis based on uncertain linguistic GRA–TOPSIS method. Soft Comput. https://doi.org/10.1007/s00500-018-3480-7

    Article  Google Scholar 

  • Hwang C-L, Yoon K (1981) Methods for multiple attribute decision making. In: Lecture notes in economics and mathematical systems, pp 58–191. https://doi.org/10.1007/978-3-642-48318-9_3

  • Ilangkumaran M, Shanmugam P, Sakthivel G, Visagavel K (2014) Failure mode and effect analysis using fuzzy analytic hierarchy process. Int J Product Qual Manag 14(3):296–313

    Google Scholar 

  • Kahraman C, Cebeci U, Ulukan Z (2003) Multi-criteria supplier selection using fuzzy AHP. Logist Inf Manag 16(6):382–394

    Google Scholar 

  • Koning J, Jaspers R, Doornink J, Ouwehand B, Klinkhamer F, Snijders B, Sadakov S (June 2009) Maintenance implications of critical components in ITER CXRS upper port plug design. Fusion Eng Des 84(7–11):1091–1094

    Google Scholar 

  • Koomsap P, Charoenchokdilok T (2018) Improving risk assessment for customer oriented FMEA. Total Qual Manag Bus Excell 29(13–14):1563–1579

    Google Scholar 

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

    Google Scholar 

  • Laarhoven PMJ, Pedrycz W (1983) A fuzzy extension of Saaty’s priority theory. Fuzzy Sets Syst 11:229–241

    MathSciNet  MATH  Google Scholar 

  • Liu HC, Liu L, Liu N, Mao LX (2012) Risk evaluation in failure mode and effects analysis with extended VIKOR method under fuzzy environment. Expert Syst Appl 39(17):12926–12934

    Google Scholar 

  • Liu H-C, Liu L, Liu N (2013) Risk evaluation approaches in failure mode and effects analysis: a literature review. Expert Syst Appl 40:828–838. https://doi.org/10.1016/j.eswa.2012.08.010

    Article  Google Scholar 

  • Liu HC, Li Z, Song W, Su Q (2017) Failure mode and effect analysis using cloud model theory and PROMETHEE method. IEEE Trans Reliab 66(4):1058–1072

    Google Scholar 

  • Liu HC, Hu YP, Wang JJ, Sun MH (2019) Failure mode and effects analysis using 2-dimensional uncertain linguistic variables and alternative queuing method. IEEE Trans Reliab 68(2):554–565

    Google Scholar 

  • Li C, Dong Y, Herrera F (2019) A consensus model for large-scale linguistic group decision making with a feedback recommendation based on clustered personalized individual semantics and opposing consensus groups. IEEE Trans Fuzzy Syst 27(2):221–233

    Google Scholar 

  • Lo HW, Liou JJH (2018) A novel multiple-criteria decision-making-based FMEA model for risk assessment. Appl Soft Comput 73:684–696

    Google Scholar 

  • Uma Maheswari and Koshy Varghese. (2007) Modeling Design Iteration Using DSM and Simulation. In 24th International Symposium on Automation and Robotics in Construction

  • Miri Lavasani MR, Wang J, Yang Z, Finlay J (2011) Application of fuzzy fault tree analysis on oil and gas offshore pipelines. Int J Mar Sci Eng 1:29–42

    Google Scholar 

  • Mzougui I, ElFelsoufi Z (2019) Improvement of failure mode, effects, and criticality analysis by using fault tree analysis and analytical hierarchy process. J Fail Anal Preven. https://doi.org/10.1007/s11668-019-00681-3

    Article  Google Scholar 

  • Mzougui I, ElFelsoufi Z (2019b) Proposition of a modified FMEA to improve reliability of product. Procedia CIRP 84:1003–1009. https://doi.org/10.1016/j.procir.2019.04.315

    Article  Google Scholar 

  • Panchal D, Jamwal U, Srivastava P, Kamboj K, Sharma R (2018) Fuzzy methodology application for failure analysis of transmission system. Int J Math Oper Res 12(2):220–237

    MATH  Google Scholar 

  • Rezaei J (2015) Best-worst multi-criteria decision-making method. Omega 53:49–57

    Google Scholar 

  • Rezaei J (2016) Best-worst multi-criteria decision-making method: some properties and a linear model. Omega 64:126–130

    Google Scholar 

  • Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New York

    MATH  Google Scholar 

  • Sachdeva A, Kumar D, Kumar P (2009) Multi-factor failure mode critically analysis using TOPSIS. J Ind Eng Int 5(8):1–9

    Google Scholar 

  • Seçme NY, Bayrakdarog˘lu A, Kahraman C (2009) Fuzzy performance evaluation in Turkish banking sector using analytic hierarchy process and TOPSIS. Experts Syst Appl 36:11699–11709

    Google Scholar 

  • Selim H, Yunusoglu MG, Balaman Y (2016) A dynamic maintenance planning framework based on fuzzy TOPSIS and FMEA: application in an international food company. Qual Reliab Eng Int 32(3):795–804

    Google Scholar 

  • Smith RP, Morrow JA (1999) Product development process modeling. Design Stud 20(3):237–261

    Google Scholar 

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

    Google Scholar 

  • Steward D (1981) The design structure matrix: a method for managing the design of complex systems. IEEE Trans Eng Manag 28(3):71–74

    Google Scholar 

  • Steward DV (1981) The design structure system: a method for managing the design of complex systems. IEEE Trans Eng Manag 28(3):71–74

    Google Scholar 

  • Tang RZ, Tang J, Ronghua X, He R (2009) Product design knowledge management based on design structure matrix. Adv Eng Inform 24(2):156–166

    Google Scholar 

  • Wakiru J, Muchiri PN, Pintelon L, Chemweno P (2019) A cost-based failure prioritization approach for selecting maintenance strategies for thermal power plants: a case study context of developing countries. Int J Syst Assur Eng Manag. https://doi.org/10.1007/s13198-019-00864-z

    Article  Google Scholar 

  • Michael H. Wang. (2011). A cost-based FMEA decision tool for product quality design and management. In 2011 proceedings of ieee international conference on intelligence and security informatics. https://doi.org/10.1109/ISI.2011.5984101

  • Yassine AA (2004) An introduction to modeling and analyzing complex product development processes using the design structure matrix (DSM) method. Urbana 51(9):1–7

    Google Scholar 

  • Zammori F, Gabbrielli R (2012) ANP/RPN: a multi criteria evaluation of the risk priority number. Qual Reliab Eng Int 28(1):85–104

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Sciences and Technologies, Abdelmalek Essaadi University, Tangier, Morocco

    Ilyas Mzougui & Zoubir El Felsoufi

Authors
  1. Ilyas Mzougui
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zoubir El Felsoufi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ilyas Mzougui.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mzougui, I., Felsoufi, Z.E. A modified method to improve failure analysis. Int J Syst Assur Eng Manag 12, 231–244 (2021). https://doi.org/10.1007/s13198-020-01043-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-020-01043-1

Keywords

Search

Navigation