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FMEA Using Cluster Analysis and Prospect Theory and Its Application to Blood Transfusion

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Abstract

The classical FMEA focuses on the risk analysis problems in which a small number of experts participate. Nowadays, with the increasing complexity of products and processes, an FMEA may require the participation of a large number of experts from distributed departments or organizations.

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References

  • Abdellaoui M, Bleichrodt H, Paraschiv C (2007) Loss aversion under prospect theory: a parameter-free measurement. Manage Sci 53(10):1659–1674

    Google Scholar 

  • Adhikary DD, Bose GK, Bose D, Mitra S (2014) Multi criteria FMECA for coal-fired thermal power plants using COPRAS-G. Int J Qual Reliab Manage 31(5):601–614

    Google Scholar 

  • Altuzarra A, Moreno-Jiménez JM, Salvador M (2010) Consensus building in AHP-group decision-making: a Bayesian approach. Oper Res 58(6):1755–1773

    MathSciNet  MATH  Google Scholar 

  • Baghery M, Yousefi S, Rezaee MJ (2018) Risk measurement and prioritization of auto parts manufacturing processes based on process failure analysis, interval data envelopment analysis and grey relational analysis. J Intell Manuf 29(8):1803–1825

    Google Scholar 

  • Bodily SE (1979) Note—a delegation process for combining individual utility functions. Manage Sci 25(10):1035–1041

    MathSciNet  MATH  Google Scholar 

  • Boje DM, Murnighan JK (1982) Group confidence pressures in iterative decisions. Manage Sci 28(10):1187–1196

    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 

  • Cai CG, Xu XH, Wang P, Chen XH (2017) A multi-stage conflict style large group emergency decision-making method. Soft Comput 21(19):5765–5778

    MATH  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 

  • Certa A, Hopps F, Inghilleri R, La Fata CM (2017) A Dempster-Shafer theory-based approach to the failure mode, effects and criticality analysis (FMECA) under epistemic uncertainty: application to the propulsion system of a fishing vessel. Reliab Eng Syst Saf 159:69–79

    Google Scholar 

  • Chang CL, Wei CC, Lee YH (1999) Failure mode and effects analysis using fuzzy method and grey theory. Kybernetes 28(9):1072–1080

    Google Scholar 

  • Chemweno P, Pintelon L, De Meyer A-M, Muchiri PN, Van Horenbeek A, Wakiru J (2017) A dynamic risk assessment methodology for maintenance decision support. Qual Reliab Eng Int 33(3):551–564

    Google Scholar 

  • Chin KS, Wang YM, Poon GKK, Yang JB (2009) Failure mode and effects analysis by data envelopment analysis. Decis Support Syst 48(1):246–256

    Google Scholar 

  • Faiella G, Parand A, Franklin BD, Chana P, Cesarelli M, Stanton NA, Sevdalis N (2018) Expanding healthcare failure mode and effect analysis: a composite proactive risk analysis approach. Reliab Eng Syst Saf 169:117–126

    Google Scholar 

  • Gitinavard H, Mousavi SM, Vahdani B (2017) Soft computing-based new interval-valued hesitant fuzzy multi-criteria group assessment method with last aggregation to industrial decision problems. Soft Comput 21(12):3247–3265

    MATH  Google Scholar 

  • Guerrero HH, Bradley JR (2013) Failure modes and effects analysis: an evaluation of group versus individual performance. Prod Oper Manag 22(6):1524–1539

    Google Scholar 

  • Hochbaum DS, Levin A (2006) Methodologies and algorithms for group-rankings decision. Manage Sci 52(9):1394–1408

    Google Scholar 

  • Huang J, Li Z, Liu HC (2017) New approach for failure mode and effect analysis using linguistic distribution assessments and TODIM method. Reliab Eng Syst Saf 167:302–309

    Google Scholar 

  • Jee TL, Tay KM, Lim CP (2015) A new two-stage fuzzy inference system-based approach to prioritize failures in failure mode and effect analysis. IEEE Trans Reliab 64(3):869–877

    Google Scholar 

  • Kahneman D, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econometrica 47(2):263–291

    MathSciNet  MATH  Google Scholar 

  • Keeney RL (1975) Group decision-making using cardinal social welfare functions. Manage Sci 22(4):430–437

    MathSciNet  MATH  Google Scholar 

  • Kim KO, Zuo MJ (2018) General model for the risk priority number in failure mode and effects analysis. Reliab Eng Syst Saf 169:321–329

    Google Scholar 

  • Liao H, Xu Z, Zeng XJ, Merigó JM (2015) Qualitative decision-making with correlation coefficients of hesitant fuzzy linguistic term sets. Knowl-Based Syst 76:127–138

    Google Scholar 

  • Liu HC (2016) FMEA using uncertainty theories and MCDM methods. Springer, Singapore

    Google Scholar 

  • Liu H, Rodríguez RM (2014) A fuzzy envelope for hesitant fuzzy linguistic term set and its application to multicriteria decision-making. Inf Sci 258:220–238

    MathSciNet  MATH  Google Scholar 

  • Liu HC, Liu L, Lin QL (2013a) Fuzzy failure mode and effects analysis using fuzzy evidential reasoning and belief rule-based methodology. IEEE Trans Reliab 62(1):23–36

    MathSciNet  Google Scholar 

  • Liu HC, Liu L, Liu N (2013b) Risk evaluation approaches in failure mode and effects analysis: a literature review. Expert Syst Appl 40(2):828–838

    Google Scholar 

  • Liu HC, Fan XJ, Li P, Chen YZ (2014) Evaluating the risk of failure modes with extended MULTIMOORA method under fuzzy environment. Eng Appl Artif Intell 34:168–177

    Google Scholar 

  • Liu BS, Shen YH, Zhang W, Chen XH, Wang XQ (2015) An interval-valued intuitionistic fuzzy principal component analysis model-based method for complex multi-attribute large-group decision-making. Eur J Oper Res 245(1):209–225

    MathSciNet  MATH  Google Scholar 

  • Liu HC, You JX, Chen S, Chen YZ (2016a) An integrated failure mode and effect analysis approach for accurate risk assessment under uncertainty. IIE Trans 48(11):1027–1042

    Google Scholar 

  • Liu HC, You JX, Li P, Su Q (2016b) Failure mode and effect analysis under uncertainty: an integrated multiple criteria decision-making approach. IEEE Trans Reliab 65(3):1380–1392

    Google Scholar 

  • Liu HC, Wang LE, You XY, Wu SM (2018a) Failure mode and effect analysis with extended grey relational analysis method in cloud setting. Total Qual Manag Bus Excel. https://doi.org/10.1080/14783363.2017.1337506

  • Liu HC, You JX, Shan MM, Su Q (2018b) Systematic failure mode and effect analysis using a hybrid multiple criteria decision-making approach. Total Qual Manag & Bus Excel. https://doi.org/10.1080/14783363.2017.1317585

  • Liu HC, You XY, Tsung F, Ji P (2018c) An improved approach for failure mode and effect analysis involving large group of experts: An application to the healthcare field. Qual Eng. https://doi.org/10.1080/08982112.2018.1448089

  • Liu HC, You JX, Duan CY (2019) An integrated approach for failure mode and effect analysis under interval-valued intuitionistic fuzzy environment. Int J Prod Econ 207:163–172

    Google Scholar 

  • Lu Y, Teng F, Zhou J, Wen A, Bi Y (2013) Failure mode and effect analysis in blood transfusion: a proactive tool to reduce risks. Transfusion 53(12):3080–3087

    Google Scholar 

  • Panchal D, Singh AK, Chatterjee P, Zavadskas EK, Keshavarz-Ghorabaee M (2019) A new fuzzy methodology-based structured framework for RAM and risk analysis. Appl Soft Comput 74:242–254

    Google Scholar 

  • Peeters JFW, Basten RJI, Tinga T (2018) Improving failure analysis efficiency by combining FTA and FMEA in a recursive manner. Reliab Eng Syst Saf 172:36–44

    Google Scholar 

  • Pillay A, Wang J (2003) Modified failure mode and effects analysis using approximate reasoning. Reliab Eng Syst Saf 79(1):69–85

    Google Scholar 

  • Ren P, Xu Z, Hao Z (2017) Hesitant fuzzy thermodynamic method for emergency decision-making based on prospect theory. IEEE Trans Cybern 47(9):2531–2543

    Google Scholar 

  • Rodríguez RM, Martínez L, Herrera F (2012) Hesitant fuzzy linguistic term sets for decision-making. IEEE Trans Fuzzy Syst 20(1):109–119

    Google Scholar 

  • Seyed-Hosseini SM, Safaei N, Asgharpour MJ (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(8):872–881

    Google Scholar 

  • Shannon CE, Weaver W (1947) A mathematical theory of communication. The University of Illinois Press, Urbana

    MATH  Google Scholar 

  • Song W, Ming X, Wu Z, Zhu B (2014) A rough TOPSIS approach for failure mode and effects analysis in uncertain environments. Qual Reliab Eng Int 30(4):473–486

    Google Scholar 

  • Stamatis DH (2003) Failure mode and effect analysis: FMEA from theory to execution, 2nd edn. ASQ Quality Press, New York

    Google Scholar 

  • Tversky A, Kahneman D (1992) Advances in prospect theory: cumulative representation of uncertainty. J Risk Uncertain 5(4):297–323

    MATH  Google Scholar 

  • von Ahsen A (2008) Cost-oriented failure mode and effects analysis. Int J Qual Reliab Manag 25(5):466–476

    Google Scholar 

  • Wang L, Wang YM, Martínez L (2017) A group decision method based on prospect theory for emergency situations. Inf Sci 418–419:119–135

    Google Scholar 

  • Wu Z, Xu J (2018) A consensus model for large-scale group decision-making with hesitant fuzzy information and changeable clusters. Information Fusion 41:217–231

    Google Scholar 

  • Xu XH, Zhong XY, Chen XH, Zhou YJ (2015) A dynamical consensus method based on exit-delegation mechanism for large group emergency decision-making. Knowl-Based Syst 86:237–249

    Google Scholar 

  • Yu PL (1973) A class of solutions for group decision problems. Manage Sci 19(8):936–946

    MathSciNet  MATH  Google Scholar 

  • Yue Z (2011) A method for group decision-making based on determining weights of decision makers using TOPSIS. Appl Math Model 35(4):1926–1936

    MathSciNet  MATH  Google Scholar 

  • Yue Z (2012) Application of the projection method to determine weights of decision makers for group decision-making. Scientia Iranica 19(3):872–878

    Google Scholar 

  • Zhou Y, Xia J, Zhong Y, Pang J (2016) An improved FMEA method based on the linguistic weighted geometric operator and fuzzy priority. Qual Eng 28(4):491–498

    Google Scholar 

  • Zhou S, Xu X, Zhou Y, Chen X (2017) A large group decision-making method based on fuzzy preference relation. Int J Inf Technol Decis-Mak 16(3):881–897

    Google Scholar 

  • Zhu J, Zhang S, Chen Y, Zhang L (2016) A hierarchical clustering approach based on three-dimensional gray relational analysis for clustering a large group of decision makers with double information. Group Decis Negot 25(2):325–354

    Google Scholar 

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Liu, HC. (2019). FMEA Using Cluster Analysis and Prospect Theory and Its Application to Blood Transfusion. In: Improved FMEA Methods for Proactive Healthcare Risk Analysis. Springer, Singapore. https://doi.org/10.1007/978-981-13-6366-5_4

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  • DOI: https://doi.org/10.1007/978-981-13-6366-5_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6365-8

  • Online ISBN: 978-981-13-6366-5

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