Restricted accessResearch articleFirst published online 2021-06-21
Extended failure mode and effect analysis approach based on hesitant fuzzy linguistic Z-numbers for risk prioritisation of nuclear power equipment failures
The successful diagnosis of nuclear power equipment failures plays a vital role in guaranteeing the safe operation of nuclear power systems. Failure mode and effect analysis (FMEA) is one of the most commonly used methods for identifying potential failures. However, several shortcomings associated with the conventional FMEA method limit its further application. This paper develops an extended FMEA approach based on hesitant fuzzy linguistic Z-numbers (HFLZNs). Firstly, the concept of HFLZNs is proposed to describe the evaluation information, which inherits the prominent features of the hesitant fuzzy linguistic term set and linguistic Z-numbers (LZNs). Secondly, an HFLZN assessment method is developed to determine the weights of risk factors, and the weights of experts are measured based on hesitation degree. Subsequently, considering the psychological characteristics of decision makers, Tomada de Decisão Iterativa Multicritério and LZNs are integrated to obtain the risk ranking of failure modes. Finally, the practicability of the extended FMEA method is proven by an illustrative example concerning the risk evaluation of a nuclear main pump bearing, and its robustness is verified by indepth analysis.
PengH., WangX., WangT., LiuY. and WangJ., A Multi-Criteria Decision Support Framework for Inland Nuclear Power Plant Site Selection under Z-Information: A Case Study in Hunan Province of China, Mathematics8 (2020), 252.
2.
TianZ., WangJ. and ZhangH., An integrated approach for failure mode and effects analysis based on fuzzy best-worst, relative entropy, and VIKOR methods, Appl Soft Comput72 (2018), 636–646.
3.
Gallardo-SaavedraS., Hernández-CallejoL. and Duque-PérezO., Quantitative failure rates and modes analysis in photovoltaic plants, Energy183 (2019), 825–836.
4.
LiuH., FMEA Using Uncertainty Theories and MCDM Methods, Singapore: Springer; 2016.
5.
GuoJ., LinZ., ZuL. and ChenJ., Failure modes and effects analysis for CO2 transmission pipelines using a hesitant fuzzy VIKOR method, Soft Comput23 (2019), 10321–10338.
6.
LiuH., LiuL. and LiuN., Risk evaluation approaches in failure mode and effects analysis: A literature review, Expert Syst Appl40 (2013), 828–838.
7.
LiuH., ChenX., DuanC. and WangY., Failure mode and effect analysis using multi-criteria decision making methods: A systematic literature review, Comput Ind Eng135 (2019), 881–897.
8.
ChemwenoP., PintelonL., Van HorenbeekA. and MuchiriP., Development of a risk assessment selection methodology for asset maintenance decision making: An analytic network process (ANP) approach, Int J Prod Econ170 (2015), 663–676.
9.
LoH. and LiouJ.J.H., A novel multiple-criteria decision-making-based FMEA model for risk assessment, Appl Soft Comput73 (2018), 684–696.
10.
BianT., ZhengH., YinL. and DengY., Failure mode and effects analysis based on D numbers and TOPSIS, Qual Reliab Eng Int34 (2018), 501–515.
11.
ChenZ., YangY., WangX., ChinK. and TsuiK., Fostering linguistic decision-making under uncertainty: A proportional interval type-2 hesitant fuzzy TOPSIS approach based on Hamacher aggregation operators and andness optimization models, Inform Sciences500 (2019), 229–258.
12.
WuZ., WuZ., MingX.G., MingX.G., SongW., SongW., et al., Nuclear Product Design Knowledge System Based on FMEA Method in New Product Development, Arab J Sci Eng39 (2014), 2191–2203.
13.
GaoS. and DengY., An evidential evaluation of nuclear safeguards, Int J Distrib Sens N15 (2019), 812342223.
14.
NieR., TianZ., WangX., WangJ. and WangT., Risk evaluation by FMEA of supercritical water gasification system using multi-granular linguistic distribution assessment, Knowl-Based Syst162 (2018), 185–201.
15.
TianC. and PengJ., An integrated picture fuzzy ANP-TODIM multi-criteria decision-making approach for tourism attraction recommendation, Technol Econ Dev Eco26(3) (2020), 573–598.
16.
JahangoshaiR.M., YousefiS., ValipourM. and DehdarM.M., Risk analysis of sequential processes in food industry integrating multi-stage fuzzy cognitive map and process failure mode and effects analysis, Comput Ind Eng123 (2018), 325–337.
17.
GuimarãesA.C.F., LapaC.M.F. and MoreiraM.D.L., Fuzzy methodology applied to Probabilistic Safety Assessment for digital system in nuclear power plants, Nucl Eng Des241 (2011), 3967–3976.
18.
AdarE., İnceM., KaratopB. and BilgiliM.S., The risk analysis by failure mode and effect analysis (FMEA) and fuzzy-FMEA of supercritical water gasification system used in the sewage sludge treatment, Journal of Environmental Chemical Engineering5 (2017), 1261–1268.
19.
YazdiM., DaneshvarS. and SetarehH., An extension to Fuzzy Developed Failure Mode and Effects Analysis (FDFMEA) application for aircraft landing system, Safety Sci98 (2017), 113–123.
20.
BraaksmaJ., MeestersA., KlingenbergW. and HicksC., A Quantitative Method for Failure Mode and Effects Analysis, Int J Prod Res50 (2011), 6904–6917.
21.
WangL., LiuH. and QuanM., Evaluating the risk of failure modes with a hybrid MCDM model under interval-valued intuitionistic fuzzy environments, Comput Ind Eng102 (2016), 175–185.
22.
MohsenO. and FereshtehN., An extended VIKOR method based on entropy measure for the failure modes risk assessment–A case study of the geothermal power plant (GPP), Safety Sci92 (2017), 160–172.
23.
ShinJ., LeeS. and YoonB., Identification and Prioritisation of Risk Factors in R&D Projects Based on an R&D Process Model, Sustainability-Basel10 (2018), 972.
24.
GhoushchiSJ, YousefiS. and KhazaeiliM., An extended FMEA approach based on the Z-MOORA and fuzzy BWM for prioritization of failures, Appl Soft Comput81 (2019), 105505.
25.
RodriguezR.M., MartinezL. and HerreraF., Hesitant Fuzzy Linguistic Term Sets for Decision Making, IEEE T Fuzzy Syst20 (2012), 109–119.
26.
LiaoH., XuZ. and ZengX., Novel correlation coefficients between hesitant fuzzy sets and their application in decision making, Knowl-Based Syst82 (2015), 115–127.
27.
ChenZ., ChinK., LiY. and YangY., Proportional hesitant fuzzy linguistic term set for multiple criteria group decision making, Inform Sciences357 (2016), 61–87.
28.
ShenK., LiL. and WangJ., Circular economy model for recycling waste resources under government participation: a case study in industrial waste water circulation in China, Technol Econ Dev Eco26 (2020), 21–47.
29.
WangJ., CaoY. and ZhangH., Multi-Criteria Decision-Making Method Based on Distance Measure and Choquet Integral for Linguistic Z-Numbers, Cogn Comput9 (2017), 827–842.
30.
TianZ., NieR., WangJ., LuoH. and LiL., A prospect theory-based QUALIFLEX for uncertain linguistic Z-number multi-criteria decision-making with unknown weight information, J Intell Fuzzy Syst38 (2020), 1775–1787.
31.
SongC., WangJ. and LiJ., New Framework for Quality Function Deployment Using Linguistic Z-Numbers, Mathematics8 (2020), 224.
32.
WangX., WangY., WangJ., ChengP. and LiL., A TODIM-PROMETHEE II Based Multi-Criteria Group Decision Making Method for Risk Evaluation of Water Resource Carrying Capacity under Probabilistic Linguistic Z-Number Circumstances, Mathematics8 (2020), 1190.
33.
GomesL.F.A.M., RangelL.A.D. and MaranhãoF.J.C., Multicriteria analysis of natural gas destination in Brazil: An application of the TODIM method, Mathematical and Computer Modelling50 (2009), 92–100.
34.
ZhouJ., WuY., WuC., HeF., ZhangB. and LiuF., A geographical information system based multi-criteria decision-making approach for location analysis and evaluation of urban photovoltaic charging station: A case study in Beijing, Energ Convers Manage205 (2020), 112340.
35.
NieR., TianZ., ChinK. and WangJ., Implementing healthcare service quality enhancement using a cloud-support QFD model integrated with TODIM method and linguistic distribution assessments, Journal of the Operational Research Society, 2020. https://doi.org/10.1080/01605682.2020.1824554.
36.
LuZ., GaoY. and ZhaoW., A TODIM-based approach for environmental impact assessment of pumped hydro energy storage plant, J Clean Prod 2019, 119265.
37.
KrohlingR.A. and de SouzaT.T.M., Combining prospect theory and fuzzy numbers to multi-criteria decision making, Expert Syst Appl39 (2012), 11487–11493.
38.
YuS., WangJ. and WangJ., An extended TODIM approach with intuitionistic linguistic numbers, Int T Oper Res25 (2018), 781–805.
39.
WangL., WangY. and MartínezL., Fuzzy TODIM method based on alpha-level sets, Expert Syst Appl140 (2020), 112899.
40.
ZhuJ., ShuaiB., WangR. and ChinK., Risk Assessment for Failure Mode and Effects Analysis Using the Bonferroni Mean and TODIM Method, Mathematics7 (2019), 536.
41.
QiaoD., ShenK., WangJ. and WangT., Multi-criteria PROMETHEE method based on possibility degree with Z-numbers under uncertain linguistic environment, J Amb Intel Hum Comp11 (2020), 2187–2201.
42.
DuanC., LiuH., ZhangL. and ShiH., An Extended Alternative Queuing Method with Linguistic Z-numbers and Its Application for Green Supplier Selection and Order Allocation, Int J Fuzzy Syst21 (2019), 2510–2523.
43.
PengH. and WangJ., Hesitant Uncertain Linguistic Z-Numbers and Their Application in Multi-criteria Group Decision-Making Problems, Int J Fuzzy Syst19 (2017), 1300–1316.
44.
KahnemanD. and TverskyA., Prospect Theory: An Analysis of Decision Under Risk, Econometrica47 (1979), 263–291.
45.
Zadeh LA. A Note on Z-numbers, Inform Sciences 181 (2011), 2923–2932.
46.
FanC., YihS., TsengW. and ChenW., Empirical analysis of software-induced failure events in the nuclear industry, Safety Sci57 (2013), 118–128.
47.
HeJ., BaoT., WuJ., ShaoG., DuD., LeX., et al., Reliability assessment and data processing techniques of the squib valve in pressurized water NPPs, Nucl Eng Des332 (2018), 59–69.
48.
XiaoF. and WangJ., Multistage decision support framework for sites selection of solar power plants with probabilistic linguistic information, J Clean Prod230 (2019), 1396–1409.
49.
QiaoD., WangX., WangJ. and ChenK., Cross Entropy for Discrete Z-numbers and Its Application in Multi-Criteria Decision-Making, Int J Fuzzy Syst21 (2019), 1786–1800.
50.
LiuY., PengH., WangT., WangX. and WangJ., Supplier Selection in the Nuclear Power Industry with an Integrated ANP-TODIM Method under Z-Number Circumstances, Symmetry12 (2020), 1357.
51.
XiongS., ChenZ. and ChinK., A Novel MAGDM Approach With Proportional Hesitant Fuzzy Sets, Int J Comput Int Sys11 (2018), 256.
52.
ZhangH., DongY., CarrascosaPalomares-I. and ZhouH., Failure Mode and Effect Analysis in a Linguistic Context: A Consensus-Based Multiattribute Group Decision-Making Approach, IEEE T Reliab68 (2019), 566–582.
53.
JiangW., XieC., WeiB. and TangY., Failure Mode and Effects Analysis based on Z-numbers, Intelligent Automation & Soft Computing 2017, 1–8.
54.
ZhaoY., TongJ., ZhangL. and WuG., Diagnosis of operational failures and on-demand failures in nuclear power plants: An approach based on dynamic Bayesian networks, Ann Nucl Energy138 (2020), 107181.
55.
QinJ., XiY. and PedryczW., Failure mode and effects analysis (FMEA) for risk assessment based on interval type-2 fuzzy evidential reasoning method, Appl Soft Comput89 (2020), 106134.
56.
ZhangH., DongY., XiaoJ., ChiclanaF. and Herrera-ViedmaE., Personalized individual semantics-based approach for linguistic failure modes and effects analysis with incomplete preference information, IISE Trans52 (2020), 1275–1296.
57.
WangX.K.,
ZhangH.Y.,
WangJ.Q.,
LiJ.B.,
LiL.. Extended TODIM-PROMETHEE II method with hesitant probabilistic information for solving potential risk evaluation problems of water resource carrying capacity, Expert Systems (2021), e12681.
