پیش بینی و تحلیل حالات خرابی و شکست با استفاده از اعداد راف و روش طرحریزی رابطه خاکستری

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشیار، گروه مهندسی صنایع، دانشکده مهندسی شهید نیکبخت، دانشگاه سیستان و بلوچستان، زاهدان، ایران

2 دانشجوی کارشناسی ارشد، دانشکده مهندسی شهید نیکبخت، دانشگاه سیستان و بلوچستان، زاهدان، ایران

چکیده

یکی از ابزارهای پرکاربرد برای شناسایی و اولویت بندی ریسک های موجود در محیط های صنعتی، تولیدی و خدماتی تکنیک تجزیه و تحلیل حالت های شکست و آثار آن FMEA است. FMEA سنتی کاستی های بسیاری دارد. از این رو پژوهش های بسیاری در راستای افزایش عملکرد FMEA انجام شده است. در این پژوهش برای مقابله با کمبود های FMEA سنتی، روش جدیدی برای بیان اطلاعات مبهم و ذهنی از اعداد راف و یک روش توسعه یافته تحلیل رابطه خاکستری ( GRA) با عنوان روش طرحریزی رابطه خاکستری (GRP) برای اولویت بندی حالت های بالقوه شکست استفاده شده است. در روش پیشنهادی ارزیابی فاکتورهای ریسک توسط اعضای تیم FMEA به وسیله اعداد راف مدلسازی شده است و سپس روش GRP اولویت های حالات شکست را تعیین می کند. برای نشان دادن کارکرد روش پیشنهادی، یک مثال برای رتبه بندی حالت های شکست، بررسی و مقایسه مدل پیشنهادی استفاده شده است. رویکرد جدید با در نظر گرفتن وزن فاکتورهای ریسک و استفاده از یک روش اولویت بندی با استفاده از روشGRP ، بر کاستی های روش FMEA سنتی مثل ضرب فاکتورهای ریسک و مقادیر ناپیوسته حاصل از آن و بی توجهی به وزن فاکتورهای ریسک غلبه کرده است. روش پیشنهادی با پوشش دادن ابهام و عدم قطعیت در قضاوت های متخصصان به اولویت بندی ریسک موثرتر و دقیق تری دست می یابد. نتایج نشان می دهد که یک رتبه بندی معقول تر و دقیق تری توسط ترکیب اعداد راف و روش GRP برای FMEA در مقایسه باFMEA سنتی حاصل شده است.

کلیدواژه‌ها


عنوان مقاله [English]

Failure Mode and Effects Analysis Using Rough Set Theory and Grey Relational Projection Method

نویسندگان [English]

  • Alireza Shahraki 1
  • Zohreh Tahmasbi Abdar 2
1 Shahid Nikbakht Engineering, University of Sistan and Baluchestan, Zahedan, Iran.
2 Masters student, Faculty of Shahid Nikbakht Engineering, University of Sistan And Baluchestan, Zahedan, Iran
چکیده [English]

Failure modes and effects analysis technique (FMEA) is One of the high usage tool to identify and prioritization of risks in the industrial, production and service environments. traditional FMEA has many shortcomings, Therefore many researches have been done to enhance the performance of FMEA. Also, in this study, a new approach has been proposed to deal with shortcomings of traditional FMEA. In this new approach Rough numbers have been used for representation of vague and subjective information and an improved method of gray relational analysis (GRA) as the Gray relational projection method (GRP) to prioritize potential failure modes. In the proposed method, evaluation of risk factors by members of the FMEA team has been modeled by Rough numbers and then The GRP method determines the priority of failure modes. To illustrate the performance of the proposed method, an example is used for the ranking of failure modes and evaluating and comparing the proposed model. The new approche have been overcame the shortcomings of traditional FMEA like multiplication of risk factors and the resulted discontinuous amounts and inattention to the weight of risk factors, by considering the weight of risk factors and using a method of prioritization by using GRP method. The proposed approach is achieved more affective and more accurate prioritization by covering ambiguity and uncertainty in experts’ judgements. The results indicates that in comparison with the traditional FMEA, a more reasonable and more accurate ranking have been resulted for FMEA method by combination of Rough numbers and GRP method.

کلیدواژه‌ها [English]

  • risk evaluation
  • Failure Mode and Effects Analysis
  • Rough Set Theory
  • Grey Relational Projection Method

[1]    Bernstein, P.L., Against the gods: The remarkable story of risk. 1996: Wiley New York.

[2]    Aven, T., Risk assessment and risk management: Review of recent advances on their foundation. European Journal of Operational Research, 2016. 253 (1): p. 1-13.

[3]    Reilly, J. and R. Thompson, International survey, 1400 projects. 2001, internal report.

[4]    Woodhouse, S., B. Burney, and K. Coste, To err is human: improving patient safety through failure mode and effect analysis. Clinical leadership & management review: the journal of CLMA, 2003. 18(1): p. 32-36.

[5]    Bowles, J.B. and C.E. Peláez, Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis. Reliability Engineering & System Safety, 1995. 50(2): p. 203-213.

[6]    Chang, K.-H. and C.-H. Cheng, Evaluating the risk of failure using the fuzzy OWA and DEMATEL method. Journal of Intelligent Manufacturing, 2011. 22 (2): p. 113-129.

[7]    Liu, H.-C., L. Liu, and N. Liu, Risk evaluation approaches in failure mode and effects analysis: A literature review. Expert systems with applications,2013. 40(2): p. 828-838.

[8]    Braglia, M., M. Frosolini, and R. Montanari, Fuzzy TOPSIS approach for failure mode, effects and criticality analysis. Quality and Reliability Engineering International, 2003. 19(5): p. 425-443.

[9]    Braglia, M., MAFMA: multi-attribute failure mode analysis. International Journal of Quality & Reliability Management, 2000. 17(9): p. 1017-1033.

[10]  Liu, H.-C., et al., Risk evaluation in failure mode and effects analysis with extended VIKOR method under fuzzy environment. Expert Systems with Applications, 2012. 39(17): p. 12926-12934.

[11]  Chin, K.-S., et al., Failure mode and effects analysis by data envelopment analysis. Decision Support Systems, 2009. 48(1): p. 246-256.

[12]  Seyed-Hosseini, S., N. Safaei, and M. Asgharpour, Reprioritization of failures in a system failure mode and effects analysis by decision making trial and evaluation laboratory technique. Reliability Engineering & System Safety, 2006. 91(8): p. 872-881.

[13]  Yang, J., et al., Risk evaluation in failure mode and effects analysis of aircraft turbine rotor blades using Dempster–Shafer evidence theory under uncertainty. Engineering Failure Analysis, 2011. 18(8): p. 2084-2092.

[14]  Zhang, Z. and X. Chu, Risk prioritization in failure mode and effects analysis under uncertainty. Expert Systems with Applications, 2011. 38(1): p. 206-214.

[15]  Chang, C.-L., P.-H. Liu, and C.-C. Wei, Failure mode and effects analysis using grey theory. Integrated Manufacturing Systems, 2001. 12(3): p. 211-216.

[16]  Liu, H.-C., et al., Failure mode and effects analysis using D numbers and grey relational projection method. Expert Systems with Applications, 2014. 41 (10): p. 4670-4679.

[17]  F.A.Mir fakhrodini and S.H.M.Poorhamidi, score potential situation ranking using fuzzy cluster analysis,2013.10(27): p. 68-93.

[18]  Rezaie, K. and M. Shaghaghi, Failure Mode and Effects Analysis Using Generalized Mixture Operators. Journal of Optimization in Industrial Engineering, 2012. 5(11): p. 1-10.

[19]  A. Roghanian, A. Azar, H. Ghaedrahmati, In the field of safety management and fuzzy data envelopment analysis .Second FDEA to analyze the potential error mode and its effects ,Rasht,Iran,1389.

[20]  M. Safari ,M. Bineshian, Using the integrated model of decision technique,the method of analyzing potential failure scenarios.First international multidimensional accounting, audit, management and economics ,Isfahan,Iran,1394.

[21]  Liu, H.-C., et al., Failure mode and effects analysis using fuzzy evidential reasoning approach and grey theory. Expert Systems with Applications,2011. 38(4): p. 4403-4415.

[22]  Zhang, X., F. Jin, and P. Liu, A grey relational projection method for multi-attribute decision making based on intuitionistic trapezoidal fuzzy number. Applied Mathematical Modelling, 2013. 37(5): p. 3467-3477.

[23]  Zheng, G., et al., Application of improved grey relational projection method to evaluate sustainable building envelope performance. Applied Energy,2010. 87(2): p. 710-720.

[24] Karimi,T and M.Sadeghi moghadam,Rough collection and gray collection.1393, tehran: institute of book mehraban publication of entesharat.

[25]  Stamatis, D.H., Failure mode and effect analysis: FMEA from theory to execution. 2003: ASQ Quality Press.

[26]  Pillay, A. and J. Wang, Modified failure mode and effects analysis using approximate reasoning. Reliability Engineering & System Safety,2003.79(1): p. 69-85.

[27]  Chin, K.-S., et al., Failure mode and effects analysis using a group-based evidential reasoning approach. Computers & Operations Research,2009.36(6): p. 1768-1779.

[28]  Kutlu, A.C. and M. Ekmekçioğlu, Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP. Expert Systems with Applications,2012. 39(1): p. 61-67.

[29]  Liu, H.-C., L. Liu, and P. Li, Failure mode and effects analysis using intuitionistic fuzzy hybrid weighted Euclidean distance operator. International Journal of Systems Science, 2014. 45(10): p. 2012-2030.

[30]  Sharma, R.K., D. Kumar, and P. Kumar, Systematic failure mode effect analysis (FMEA) using fuzzy linguistic modelling. International Journal of Quality & Reliability Management, 2005. 22(9): p. 986-1004.

[31]  Meng Tay, K. and C. Peng Lim, Fuzzy FMEA with a guided rules reduction system for prioritization of failures. International Journal of Quality & Reliability Management, 2006. 23(8): p. 1047-1066.

[32]  Pawlak, Z., Rough sets. International Journal of Computer & Information Sciences, 1982. 11(5): p. 341-356.

[33]  Pawlak, Z., Rough sets: Theoretical aspects of reasoning about data. Vol. 9.  Springer Science & Business Media.

[34]  Huang, S.-Y., Intelligent decision support: handbook of applications and advances of the rough sets theory. Vol. 11. 1992: Springer Science & Business Media.

[35]  Greco, S., B. Matarazzo, and R. Slowinski, Rough sets theory for multicriteria decision analysis. European journal of operational research, 2001. 129(1): p. 1-47.

[36]  Zhai, L.-Y., L.-P. Khoo, and Z.-W. Zhong, A rough set enhanced fuzzy approach to quality function deployment. The International Journal of Advanced Manufacturing Technology, 2008. 37(5-6): p. 613-624.

[37]  Song, W., X. Ming, and Z. Xu, Risk evaluation of customer integration in new product development under uncertainty. Computers & Industrial Engineering, 2013. 65(3): p. 402-412.

[38]  Tzeng, G.-H. and S. Tasur, The multiple criteria evaluation of grey relation model. The Journal of Grey System, 1994. 6(2): p. 87-108.

[39]  Song, W., et al., A rough TOPSIS approach for failure mode and effects analysis in uncertain environments. Quality and Reliability Engineering International, 2014. 30(4): p. 473-486.