This study presents a novel approach combining Failure Mode and Effect Analysis (FMEA) and Multi-Attributive Border Approximation Area Comparison (MABAC) method based on a stochastic evaluation process to prioritize potential failure modes (FMs) in an assembly line. The aim of the proposed approach is to improve the performance of FMEA by eliminating its shortcomings addressed in the study. In this context, firstly the risk factor (RF) importance weights and the performance values of the FMs for the RFs are determined by generating random numbers having uniform distribution in a range of minimum and maximum value of a limited number of expert evaluations. In this wise, the number of experts are increased to improve effectiveness of the risk evaluation process. Diverse opinions of experts are also assessed more precisely. Secondly, the priorities of the FMs are identified by implementing MABAC method. MABAC is a practical and reliable tool which provides stability for solutions. Finally, a comparative analysis is implemented to confirm the effectiveness of Stochastic FMEA-MABAC approach.
Mots clés : FMEA, Stochastic, MABAC, Uniform Distribution, MCDM
@article{RO_2017__51_4_1077_0,
author = {Kili\c{c} Delice, Elif and Can, Gulin Feryal},
title = {A stochastic approach for failure mode and effect analysis},
journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
pages = {1077--1100},
publisher = {EDP-Sciences},
volume = {51},
number = {4},
year = {2017},
doi = {10.1051/ro/2017010},
language = {en},
url = {http://www.numdam.org/articles/10.1051/ro/2017010/}
}
TY - JOUR AU - Kiliç Delice, Elif AU - Can, Gulin Feryal TI - A stochastic approach for failure mode and effect analysis JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2017 SP - 1077 EP - 1100 VL - 51 IS - 4 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ro/2017010/ DO - 10.1051/ro/2017010 LA - en ID - RO_2017__51_4_1077_0 ER -
%0 Journal Article %A Kiliç Delice, Elif %A Can, Gulin Feryal %T A stochastic approach for failure mode and effect analysis %J RAIRO - Operations Research - Recherche Opérationnelle %D 2017 %P 1077-1100 %V 51 %N 4 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ro/2017010/ %R 10.1051/ro/2017010 %G en %F RO_2017__51_4_1077_0
Kiliç Delice, Elif; Can, Gulin Feryal. A stochastic approach for failure mode and effect analysis. RAIRO - Operations Research - Recherche Opérationnelle, Tome 51 (2017) no. 4, pp. 1077-1100. doi : 10.1051/ro/2017010. http://www.numdam.org/articles/10.1051/ro/2017010/
, , , and , Risk evaluation in failure mode and effects analysis of aircraft turbine rotor blades using dempster–shafer evidence theory under uncertainty. Eng. Failure Anal. 18 (2011) 2084–2092. | DOI
and , Application of FMEA to an automotive leaf spring manufacturing organization. TQM J. 24 (2012) 260–274. | DOI
, and , Healthcare failure mode and effects analysis under fuzziness. Hum. Ecol. Risk Assess. Internat. J. 19 (2013) 538–552. | DOI
, and , Risk evaluation approaches in failure mode and effects analysis: A literature review. Expert Syst. Appl. 40 (2013) 828–838. | DOI
W.G. Ireson, C.F. Coombs and R.Y. Moss, Handbook of Reliability Engineering and Management. McGraw Hill (1996).
, , , and , Application of fuzzy logic to matrix FMECA. In AIP Conf. Proc. AIP 557 (2001) 1987–1994 . | DOI
and , A fuzzy multi criteria risk assessment based on decision matrix technique: A case study for aluminum industry. J. Loss Prev. Process Industries 40 (2016) 89–100. | DOI
, , and , Fuzzy belief structure based VIKOR method: an application for ranking delay causes of Tehran metro system by FMEA criteria. Transport 31 (2016) 108–118. | DOI
, , and , Failure mode and effects analysis by data envelopment analysis. Decis. Support Syst. 48 (2009) 246–256. | DOI
, , , , and , Failure mode and effects analysis using fuzzy evidential reasoning approach and grey theory. Expert Syst. Appl. 38 (2011) 4403–4415. | DOI
and , Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis. Reliab. Eng. Syst. Safety 50 (1995) 203–213. | DOI
and , A revised failure mode and effects analysis model. Inter. J. Quality Reliab. Manag. 13 (1996) 43–47. | DOI
and , Modified failure mode and effects analysis using approximate reasoning. Reliab. Eng. Syst. Safety 79 (2003) 69–85. | DOI
, , and , Failure mode and effects analysis using D numbers and grey relational projection method. Expert Syst. Appl. 41 (2014) 4670–4679. | DOI
, , and , A novel approach for FMEA: Combination of interval 2-tuple linguistic variables and gray relational analysis. Quality Reliab. Eng. Inter. 31 (2015) 761–772. | DOI
, , and , A rough TOPSIS approach for failure mode and effects analysis in uncertain environments. Quality Reliab. Eng. Inter. 30 (2014) 473–486. | DOI
, , and , Risk evaluation in failure mode and effects analysis using fuzzy weighted geometric mean. Expert Syst. Appl. 36 (2009) 1195–1207. | DOI
, , and , Multi criteria FMECA for coal-fired thermal power plants using copras-g. Inter. J. Quality Reliab. Manag. 31 (2014) 601–614. | DOI
, and , Fuzzy criticality assessment model for failure modes and effects analysis. Int. J. Quality Reliab. Manag. 20 (2003) 503–524. | DOI
, , and , An integrated multicriteria decision making methodology using compromise solution methods for prioritising risk of marine machinery systems. Ocean Eng. 105 (2015) 92–103. | DOI
, and , Systematic failure mode effect analysis (FMEA) using fuzzy linguistic modelling. Inter. J. Quality Reliab. Manag. 22 (2005) 986–1004. | DOI
, and , Kargo firması seçiminde stokastik copras yaklaşımı. In Ulusal Yoneylem Araştırması ve Endustri Mhendisliği Kongresi, Izmir. Temmuz 36 (2016) 13–15.
and , The selection of transport and handling resources in logistics centers using multi-attributive border approximation area comparison (MABAC). Expert Syst. Appl. 42 (2015) 3016–3028. | DOI
H.-Ch. Liu, FMEA using uncertainty theories and MCDM methods. In FMEA Using Uncertainty Theories and MCDM Methods. Springer (2016) 13–27.
, and , Failure mode and effects analysis using fuzzy method and grey theory. Kybernetes 28 (1999) 1072–1080. | DOI
, and , Failure mode and effects analysis using grey theory. Integr. Manuf. Syst. 12 (2001) 211–216. | DOI
and , An alternative evaluation of fmea: fuzzy art algorithm. Quality Reliab. Eng. Inter. 25 (2009) 647–661. | DOI
and , Risk management in the construction industry using combined fuzzy FMEA and fuzzy AHP. J. Constr. Eng. Manag. 136 (2010) 1028–1036. | DOI
and , Evaluating the risk of failure using the fuzzy OWA and DEMATEL method. J. Intel. Manuf. 22 (2011) 113–129. | DOI
Y. Park Y. Geum and Y. Cho, A systematic approach for diagnosing service failure: Service-specific FMEA and Grey Relational Analysis Approach (2011). | Zbl
and , ANP/RPN: A multi criteria evaluation of the risk priority number. Quality Reliab. Eng. Inter. 28 (2012) 85–104. | DOI
, , and , Risk evaluation in failure mode and effects analysis with extended VIKOR method under fuzzy environment. Expert Syst. Appl. 39 (2012) 12926–12934. | DOI
A. Hadi−Vencheh and M Aghajani, Failure mode and effects analysis: A fuzzy group MCDM approach. J. Soft Comput. Appl. (2013) (2013) 1–14.
, , and , Failure mode and effect analysis using fuzzy analytic hierarchy process. Inter. J. Prod. Quality Manag. 14 (2014) 296–313.
, , and , Evaluating the risk of failure modes with extended MULTIMOORA method under fuzzy environment. Eng. Appl. Artificial Intel. 34 (2014) 168–177. | DOI
, and , Failure mode and effects analysis using intuitionistic fuzzy hybrid weighted euclidean distance operator. Inter. J. Syst. Sci. 45 (2014) 2012–2030. | DOI | MR | Zbl
, and , Evaluating the risk of healthcare failure modes using interval 2-tuple hybrid weighted distance measure. Comput. Ind. Eng. 78 (2014) 249–258. | DOI
and , Fuzzy based failure modes and effect analysis for yacht system design. Ocean Eng. 79 (2014) 131–141. | DOI
and , Qualitative and quantitative approaches to analyse reliability of a mechatronic system: a case. J. Indus. Eng. Inter. 11 (2015) 253–268. | DOI
and , Identification and risk assessment of soldering failure sources using a hybrid failure mode and effect analysis model and a fuzzy inference system. J. Intell. Fuzzy Syst. 28 (2015) 2771–2784. | DOI
and , Integrated framework for behaviour analysis in a process plant. J. Loss Prevention Process Industries 40 (2016) 147–161. | DOI
and , Fuzzy and grey theories in failure mode and effect analysis for tanker equipment failure prediction. Safety Sci. 83 (2016) 74–79. | DOI
, , and , Failure mode and effects analysis using intuitionistic fuzzy hybrid TOPSIS approach. Soft Comput. 19 (2015) 1085–1098. | DOI
, J.-Xin You, X.-F. Ding and Q. Su, Improving risk evaluation in fmea with a hybrid multiple criteria decision making method. Inter. J. Quality Reliab. Manag. 32 (2015) 763–782. | DOI
, , , , , Ferrari, S. Marinelli and R. Savazza, Waste treatment: an environmental, economic and social analysis with a new group fuzzy PROMETHEE approach. Clean Techn. Environ. Policy 18 (2016) 1317–1332. | DOI
, and , Identifying and evaluating enterprise architecture risks using FMEA and fuzzy VIKOR. J. Intel. Manuf. 27 (2016) 475–486. | DOI
, and , A new fmea method by integrating fuzzy belief structure and TOPSIS to improve risk evaluation process. Inter. J. Adv. Manuf. Techn. 77 (2015) 357–368. | DOI
, , and , An integrated failure mode and effect analysis approach for accurate risk assessment under uncertainty. IIE Trans. 48 (2016) 1027–1042. | DOI
, , and , Failure mode and effect analysis under uncertainty: an integrated multiple criteria decision making approach. IEEE Trans. Reliab. 65 (2016) 1380–1392. | DOI
H. Zhao, J.-X. You and H.-Ch. Liu, Failure mode and effect analysis using multimoora method with continuous weighted entropy under interval-valued intuitionistic fuzzy environment. Soft Comput. (2016) 1–13.
, and , An improved FMECA for feed system of CNC machining center based on ICR and DEMATEL method. Int. J. Adv. Manuf. Techn. 83 (2016) 43–54. | DOI
, , Xiao-Dong Lai and H.-Ch. Liu, An interval-valued intuitionistic fuzzy MABAC approach for material selection with incomplete weight information. Appl. Soft Comput. 38 (2016) 703–713. | DOI
and , Pythagorean fuzzy choquet integral based MABAC method for multiple attribute group decision making. Int. J. Intell. Syst. 31 (2016) 989–1020. | DOI
Su-min Yu, J. Wang and J.-q. Wang, An interval type-2 fuzzy likelihood-based MABAC approach and its application in selecting hotels on a tourism website. Int. J. Fuzzy Syst. (2016) 1–15. | MR
J. Roy, A. Ranjan and A. Debnath, An extended MABAC for multi-attribute decision making using trapezoidal interval type-2 fuzzy numbers. Preprint (2016). | arXiv
J. Roy, K. Chatterjee, A. Bandhopadhyay and S. Kar, Evaluation and selection of medical tourism sites: A rough AHP based MABAC approach. Preprint (2016). | arXiv
, and , Use of the fuzzy AHP-MABAC hybrid model in ranking potential locations for preparing laying-up positions. Vojnotehnički Glasnik 64 (2016) 705–729. | DOI
and , Calibrated fuzzy AHP for current bank account selection. Expert Syst. Appl. 40 (2013) 3775–3783. | DOI
and , Reliability prediction and failure mode effects and criticality analysis (FMECA) of electronic devices using fuzzy logic. Int. J. Quality Reliab. Manag. 22 (2005) 183–200. | DOI
, and , Failure modes and effects analysis (fmea) for wind turbines. Inter. J. Electrical Power Energy Syst. 32 (2010) 817–824. | DOI
F.M. Company, Potential failure mode and effects analysis in design (Design FMECA) and for manufacturing and assembly process (Process FMECA) instruction manual (1988).
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