Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
ATZ-Fachkongress

Chassis.tech plus 2024


4 Kongresse in einer Veranstaltung

Treffen Sie in München die Fachleute von Chassis, Lenkung, Bremsen sowie Reifen/Räder.
Erweiterte Suche
Anmelden
nach oben
The International Journal of Advanced Manufacturing Technology
Erschienen in: The International Journal of Advanced Manufacturing Technology 5-6/2021

03.01.2021 | ORIGINAL ARTICLE

Literature review and prospect of the development and application of FMEA in manufacturing industry

verfasst von: Zhongyi Wu, Weidong Liu, Wenbin Nie

Erschienen in: The International Journal of Advanced Manufacturing Technology | Ausgabe 5-6/2021

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In order to enable failure mode and effects analysis (FMEA) to play a better quality control role in complex manufacturing products or systems, the current research status of FMEA is reviewed from failure mode identification, risk assessment, and industrial standard application. Firstly, the research status of system failure identification is summarized from the following aspects: the breakthrough point of identification, the types of identification methods, and the normalized description of failure modes. Then, sort out the research status of risk assessment from five aspects: risk factor evaluation criteria, risk assessment opinion expression, expert opinion consensus, risk opinion assessment aggregation, and sensitivity analysis, and find out research hotspots and blind spots; finally, the changes of FMEA standards in various fields are summarized and compared, and the future development trend of FMEA in the context of intelligent manufacturing is discussed.
Vorheriger Artikel Simulation of sheet metal forming processes by presenting a bending-dependent inverse isogeometric methodology
Nächster Artikel Numerical simulation and experimental study on cold extrusion process for clutch outer gear hub with inner tooth shapes

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Lo HW, Liou JJ, Huang CN, Chuang YC (2019) A novel failure mode and effect analysis model for machine tool risk analysis. Reliab Eng Syst Saf 183:173–183CrossRef
2.
Su X, Deng Y, Mahadevan S (2012) An improved method for risk evaluation in failure modes and effects analysis of aircraft engine rotor blades. Eng Fail Anal 26:164–174CrossRef
3.
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):1803–1825CrossRef
4.
Sakthivel G, Ikua BW (2017) Failure mode and effect analysis using fuzzy analytic hierarchy process and GRA TOPSIS in manufacturing industry. Int J Prod Qual Manag 22(4):466–484
5.
Wang Z, Gao J, Wang R (2018) Failure mode and effects analysis using Dempster-Shafer theory and TOPSIS method: application to the gas insulated metal enclosed transmission line (GIL). Appl Soft Comput:633–647
6.
Ahn J, Noh Y, Park SH (2017) Fuzzy-based failure mode and effect analysis (FMEA) of a hybrid molten carbonate fuel cell (MCFC) and gas turbine system for marine propulsion. J Power Sources 364:226–233CrossRef
7.
Liu HC, You XY, Tsung F (2018) An improved approach for failure mode and effect analysis involving large group of experts: an application to the healthcare field. Qual Eng 30(4):762–775CrossRef
8.
9.
Mutlu NG, Altuntaş S Hazard and risk analysis for ring spinning yarn production process by integrated FTA-FMEA approach. J Text Apparel/Tekstil ve Konfeksiyon 29(3)
10.
Mutlu NG, Altuntas (2019) Risk analysis for occupational safety and health in the textile industry: integration of FMEA, FTA, and BIFPET methods. Int J Ind Ergon 72:222–240CrossRef
11.
12.
Liu HC, Liu L, Liu N (2013) Risk evaluation approaches in failure mode and effects analysis: a literature review. Expert Syst Appl 40(2):828–838CrossRef
13.
Waghmare SN, Raut DN, Mahajan SK, Mahajan SK, Bhamare SS (2014) Failure mode effect analysis and total productive maintenance: a review. Int J Innov Res Adv Eng 1(6):183–184
14.
Spreafico C, Russo D, Rizzi C (2017) A state-of-the-art review of FMEA/FMECA including patents. Comput Sci Rev 25:19–28CrossRef
15.
Liu H, Chen X, Duan C, Wang YM (2019) Failure mode and effect analysis using multi-criteria decision making methods: a systematic literature review. Comput Ind Eng 135:881–897CrossRef
16.
Liu HC (2019) FMEA for proactive healthcare risk analysis: a systematic literature review. In: Improved FMEA methods for proactive healthcare risk analysis. Springer, Singapore, pp 15–45CrossRef
17.
Stone RB, Tumer IY, Van Wie M (2005) The function-failure design method. J Mech Des 127(3):397–407CrossRef
18.
Wang C, Li Y, Li WQ (2013) System failure analysis and creative design based on functional role model. J Mach Des 30(12):1–5
19.
DeStefano CB, Jensen DC (2014) A qualitative failure analysis using function-based performance state-machines for fault identification and propagation during early design phases. In ASME 2014 International design engineering technical conferences and computers and information in engineering conference. American Society of Mechanical Engineers Digital Collection
20.
Kurtoglu T, Tumer IY (2008) A graph-based fault identification and propagation framework for functional design of complex systems. J Mech Des 130(5):1–8CrossRef
21.
O'Halloran BM, Papakonstantinou N, Van Bossuyt DL (2015) Modeling of function failure propagation across uncoupled systems. In 2015 Annual Reliability and Maintainability Symposium (RAMS) IEEE, pp. 1-6
22.
Arunajadai SG, Stone RB, Tumer IY, Clancy D (2002) A Framework for creating a function based design tool for failure mode identification. Paper presented at the ASME 2002 International design engineering technical conferences and computers and information in engineering conference, Montreal, Canada
23.
Zheng HM, Liu WD, Xiao CD (2018) An activity-based defect management framework for product development. Comput Ind Eng 118:202–209CrossRef
24.
Zheng HM, Liu WD, Xiao CD (2018) Structural relationship model for design defects and influencing factors in the concurrent design process. Int J Prod Res 56(14):4897–4924CrossRef
25.
Li G, Gao J, Chen F (2009) A novel approach for failure modes and effects analysis based on polychromatic sets. Artif Intell Eng Des Anal Manuf 23(2):119–129CrossRef
26.
Struss P, Price C (2003) Model based systems in the automotive industry. AI Mag 24(4):1–17
27.
Xu Z, Dang Y, Munro P, Wang Y (2020) A data-driven approach for constructing the component failure mode matrix for FMEA. J Intell Manuf 31(1):249–265CrossRef
28.
Loganathan MK, Goswami P, Bhagawati B (2016) Failure evaluation and analysis of mechatronics-based production systems during design stage using structural modeling. Appl Mech Mater Trans Tech Publ Ltd 852:799–805CrossRef
29.
Tumer IY, Stone RB (2003) Mapping function to failure mode during component development. Res Eng Des 14(1):25–33CrossRef
30.
Loganathan MK, Gandhi MS, Gandhi OP (2015) Functional cause analysis of complex manufacturing systems using structure. Proc Inst Mech Eng B J Eng Manuf 229(3):533–545CrossRef
31.
Wani MF (2006) Failure analysis of mechanical systems based on function-cum-structure approach. In ASME 8th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers Digital Collection (pp. 975-983)
32.
Feng FZ, Luo JH, Liu YH et al (2016) A FMMEA analysis method based on function-structure-failure model. Journal of Vibration, Measurement & Diagnosis 36(03):413–418 598
33.
Zhang J, Roberts PD (1991) Process fault diagnosis with diagnostic rules based on structural decomposition. J Process Control 1(5):259–269CrossRef
34.
Nepal BP, Yadav OP, Monplaisir L (2008) A framework for capturing and analyzing the failures due to system/component interactions. Qual Reliab Eng Int 24(3):265–289CrossRef
35.
Augustine M, Yadav OP, Jain R (2012) Cognitive map-based system modeling for identifying interaction failure modes. Res Eng Des 23(2):105–124CrossRef
36.
Sun Y, Ma L, Mathew J, Zhang S (2006) An analytical model for interactive failures. Reliab Eng Syst Saf 91(5):495–504CrossRef
37.
Sun Y, Ma L, Mathew J (2009) Failure analysis of engineering systems with preventive maintenance and failure interactions. Comput Ind Eng 57(2):539–549CrossRef
38.
Ma H, Chu X, Xue D (2019) Identification of to-be-improved components for redesign of complex products and systems based on fuzzy QFD and FMEA. J Intell Manuf 30(2):623–639CrossRef
39.
Wang SY (2003) Failure mode and effect analysis (FMEA). Sun yat-sen university press
40.
Bluvband Z, Grabov P (2009) Failure analysis of FMEA. In 2009 Annual Reliability and Maintainability Symposium, IEEE, (pp. 344-347)
41.
Stone R, Tumer IY, Stock ME (2005) Linking product functionality to historic failures to improve failure analysis in design. Res Eng Des 16(1–2):96–108CrossRef
42.
Zhang X, Li Y, Ran Y, Zhang G (2019) A hybrid multilevel FTA-FMEA method for a flexible manufacturing cell based on meta-action and TOPSIS. IEEE Access 7:110306–110315CrossRef
43.
Zhang X, Zhang G, Li Y, Wang H, Gong X (2019) A novel fault diagnosis approach of a mechanical system based on meta-action unit. Adv Mech Eng 11(2):1687814019826644CrossRef
44.
Hurdle EE, Bartlett LM, Andrews JD (2007) System fault diagnostics using fault tree analysis. Proc Inst Mech Eng O J Risk Reliab 221(1):43–55
45.
Deng Y, Li Q, Lu Y (2015) A research on subway physical vulnerability based on network theory and FMECA. Saf Sci 80:127–134CrossRef
46.
Rao RV, Gandhi OP (2002) Failure cause analysis of machine tools using digraph and matrix methods. Int J Mach Tools Manuf 42(4):521–528CrossRef
47.
Bartlett LM, Hurdle EE, Kelly EM (2009) Integrated system fault diagnostics utilising digraph and fault tree-based approaches. Reliab Eng Syst Saf 94(6):1107–1115CrossRef
48.
Chen X, Li WQ, Li Y (2014) Integrated analysis of fishbone and evolution laws on product failure prediction and problem solving. Chin J Eng Des 21(02):109–114
49.
Hata T, Kobayashi N, Kimura F, Suzuki H (2000) Representation of functional relations among parts and its application to product failure reasoning. J Manuf Sci Prod 3(2–4):77–84
50.
Liu L, Fan D, Wang Z, Yang D, Cui J, Ma X, Ren Y (2019) Enhanced GO methodology to support failure mode, effects and criticality analysis. J Intell Manuf 30(3):1451–1468CrossRef
51.
Arvanitoyannis IS, Varzakas TH (2008) Application of ISO 22000 and failure mode and effect analysis (FMEA) for industrial processing of salmon: a case study. Crit Rev Food Sci Nutr 48(5):411–429CrossRef
52.
Eubanks F (2012) HAZOP analysis of product requirements for early failure mode identification. In INCOSE International Symposium (Vol. 22, No. 1, pp. 1977-1985)
53.
James AT, Gandhi OP, Deshmukh SG (2018) Fault diagnosis of automobile systems using fault tree based on digraph modeling. Int J Syst Assur Eng Manag 9(2):494–508CrossRef
54.
Kelly EM, Bartlett LM (2007) Aircraft fuel rig system fault diagnostics based on the application of digraphs. Proc Inst Mech Eng O J Risk Reliab 221(4):275–284
55.
Noh KW, Jun HB, Lee JH (2011) Module based failure propagation (MFP) model for FMEA. Int J Adv Manuf Technol 55(5–8):581–600CrossRef
56.
Sierla S, Tumer I, Papakonstantinou N (2012) Early integration of safety to the mechatronic system design process by the functional failure identification and propagation framework. Mechatronics 22(2):137–151CrossRef
57.
Tumer I Y, Stone R B, Bell D G (2003). Requirements for a failure mode taxonomy for use in conceptual design. In DS 31: Proceedings of ICED 03, the 14th International Conference on Engineering Design, Stockholm
58.
Arunajadai SG, Uder SJ, Stone RB (2004) Failure mode identification through clustering analysis. Qual Reliab Eng Int 20(5):511–526CrossRef
59.
Wu LL, Liu WD, Xiao SH et al (2018) Information extraction method of process components based on fusion of word vector and neural network. J Nanchang Univ (Nat Sci) 42(03):274–282
60.
Zheng HM, Liu WD, Xiao CD, Hu WL (2014) Formation and assessment modeling of mechanical product design defect based on analyzing design activity. Comput Integr Manuf Syst 2015 21(1):31–39
61.
Yang LB, Li P, Xue R, Ma XN, Wu YH, Zou D (2018) Intelligent classification of faults of railway signal equipment based on imbalanced text data mining. J Chin Railw Soc 40(02):59–66
62.
Wani MF, Jan M (2006) Failure mode analysis of mechanical systems at conceptual design stage. In ASME 8th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers Digital Collection, (pp. 985-995)
63.
Chen L, Nayak DR (2007) A case study of failure mode analysis with text mining methods. In Proceedings of the 2nd international workshop on Integrating artificial intelligence and data mining-Volume 84 (pp. 49-60). Australian Computer Society, Inc.
64.
Rajpathak DG (2013) An ontology based text mining system for knowledge discovery from the diagnosis data in the automotive domain. Comput Ind 64(5):565–580CrossRef
65.
Jensen DC, Hoyle C, Tumer IY (2012) Clustering function-based failure analysis results to evaluate and reduce system-level risks. In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference American Society of Mechanical Engineers Digital Collection, (pp. 1055-1064)
66.
Chang WL, Tay KM, Lim CP (2015) Clustering and visualization of failure modes using an evolving tree. Expert Syst Appl 42(20):7235–7244CrossRef
67.
Jensen DC, Bello O, Hoyle C, Tumer IY (2014) Reasoning about system-level failure behavior from large sets of function-based simulations. AI EDAM 28(4):385–398
68.
Kurtoglu T, Tumer IY, Jensen DC (2010) A functional failure reasoning methodology for evaluation of conceptual system architectures. Res Eng Des 21(4):209–234CrossRef
69.
Liu SC, Liu SY (2003) An efficient expert system for machine fault diagnosis. Int J Adv Manuf Technol 21(9):691–698CrossRef
70.
Li B, Han T, Kang F (2013) Fault diagnosis expert system of semiconductor manufacturing equipment using a Bayesian network. Int J Comput Integr Manuf 26(12):1161–1171CrossRef
71.
Boral S, Chaturvedi SK, Naikan VNA (2019) A case-based reasoning system for fault detection and isolation: a case study on complex gearboxes. J Qual Maint Eng 25(2):213–235CrossRef
72.
Jacobo VH, Ortiz A, Cerrud Y (2007) Hybrid expert system for the failure analysis of mechanical elements. Eng Fail Anal 14(8):1435–1443CrossRef
73.
Wang HC, Wang HS (2005) A hybrid expert system for equipment failure analysis. Expert Syst Appl 28(4):615–622CrossRef
74.
Zhong Z, Xu T, Wang F, Tang T (2018) Text Case-Based Reasoning Framework for Fault Diagnosis and Predication by Cloud Computing. Math Probl Eng:2018
75.
Xu F, Liu X, Chen W, Zhou C, Cao B (2018) Ontology-based method for fault diagnosis of loaders. Sensors 18(3):729CrossRef
76.
Dendani-Hadiby N, Khadir MT (2013) A fault diagnosis application based on a combination case-based reasoning and ontology approach. Int J Knowl Based Intell Eng Syst 17(4):305–317
77.
Thike PH, Xu Z, Cheng Y (2019) Materials failure analysis utilizing rule case based hybrid reasoning method. Eng Fail Anal 95:300–311CrossRef
78.
Rajpathak D, De S (2016) A data-and ontology-driven text mining based construction of reliability model to analyze and predict component failures. Knowl Inf Syst 46(1):87–113CrossRef
79.
Wang CY, Jiang QY, Tang YJ (2019) Fault diagnosis of power dispatching based on alarm signal text mining. Electr Power Autom Equip 39(04):126–132
80.
Wang F, Xu T, Tang T, Zhou M, Wang H (2016) Bilevel feature extraction-based text mining for fault diagnosis of railway systems. IEEE Trans Intell Transp Syst 18(1):49–58CrossRef
81.
Du XM, Qin JF, Guo SY (2018) Text Mining of Typical Defects in power equipment. High Voltage Eng 44(04):1078–1084
82.
Nie WB, Liu WD, et al (2019) Method for automatically identifying process failure mode. China:CN201610373015.1
83.
Abrahams AS, Fan W, Wang GA, Zhang ZJ, Jiao J (2015) An integrated text analytic framework for product defect discovery. Prod Oper Manag 24(6):975–990CrossRef
84.
Zhang W, Xu H, Wan W (2012) Weakness finder: find product weakness from Chinese reviews by using aspects based sentiment analysis. Expert Syst Appl 39(11):10283–10291CrossRef
85.
Law D, Gruss R, Abrahams AS (2017) Automated defect discovery for dishwasher appliances from online consumer reviews. Expert Syst Appl 67:84–94CrossRef
86.
Winkler M, Abrahams S, Gruss R, Ehsani JP (2016) Toy safety surveillance from online reviews. Decis Support Syst 90:23–32CrossRef
87.
Chandrasekaran B, Josephson JR, Benjamins VR (1999) What are ontologies, and why do we need them? IEEE Intell Syst 14(1):20–26CrossRef
88.
Liu B, Wu J, Yao L, Ding Z (2019) Ontology-based fault diagnosis: a decade in review. In Proceedings of the 11th International Conference on Computer Modeling and Simulation (pp. 112-116)
89.
Mikos WL, Ferreira JC, Botura PE, Freitas LS (2011) A system for distributed sharing and reuse of design and manufacturing knowledge in the PFMEA domain using a description logics-based ontology. J Manuf Syst 30(3):133–143CrossRef
90.
James AT, Gandhi OP, Deshmukh SG (2017) Knowledge management of automobile system failures through development of failure knowledge ontology from maintenance experience. J Adv Manag Res 14(4):425–445CrossRef
91.
Ebrahimipour V, Rezaie K, Shokravi S (2010) An ontology approach to support FMEA studies. Expert Syst Appl 37(1):671–677CrossRef
92.
Xiuxu Z, Yuming Z (2012) Application research of ontology-enabled process FMEA knowledge management method. Int J Intell Syst Appl 4(3):34–40
93.
Rehman Z, Kifor S (2014) A conceptual architecture of ontology based KM system for failure mode and effects analysis. Int J Comput Commun Control 9(4):463–470CrossRef
94.
Zhou A, Yu D, Zhang W (2015) A research on intelligent fault diagnosis of wind turbines based on ontology and FMECA. Adv Eng Inform 29(1):115–125CrossRef
95.
Li G (2013) Ontology based reuse of failure modes in existing databases for FMEA: methodology and tool. IEICE Trans Fundam Electron Commun Comput Sci 96(7):1645–1648CrossRef
96.
Rehman Z, Kifor CV (2016) An ontology to support semantic management of FMEA knowledge. Int J Comput Commun Control 11(4):507–521CrossRef
97.
Dittmann L, Rademacher T, Zelewski S (2004) Performing FMEA using ontologies. In 18th International Workshop on Qualitative Reasoning. Evanston USA (pp. 209-216)
98.
Lee BH (2001) Using FMEA models and ontologies to build diagnostic models. AI EDAM 15(4):281–293MATH
99.
Koji Y, Kitamura Y, Mizoguchi R (2005) Ontology based transformation from an extended functional model to FMEA. In ICED 05: 15th International Conference on Engineering Design: Engineering Design and the Global Economy (p. 1984). Engineers Australia
100.
Molhanec M, Zhuravskaya O, Povolotskaya E, Tarba L (2011) The ontology based FMEA of lead free soldering process. In Proceedings of the 2011 34th International Spring Seminar on Electronics Technology (ISSE) (pp. 267-273). IEEE
101.
Zhao X, Zhu Y (2010) Research of FMEA knowledge sharing method based on ontology and the application in manufacturing process. In 2010 2nd International Workshop on Database Technology and Applications (pp. 1-4). IEEE
102.
Gen XL, Chu XN (2009) Risk evaluation method in failure mode and effects analysis based on failure cause-effect chain. Comput Integr Manuf Syst 15(12):2473–2480
103.
Liu WD, Hu K, Zheng HM (2016) PFMEA technology of multi-varieties and small batch customization mode. Comput Integr Manuf Syst 22(06):1485–1493
104.
Braglia M, Fantoni G, Frosolini M (2007) The house of reliability. Int J Qual Reliab Manag 24(4):420–440CrossRef
105.
Guide to Failure Mode Impact and Hazard Analysis (2006) GJB/Z 1391—2006. General armament department of the PLA, BeiJing
106.
Nie WB, Liu WD, Xiao SH et al (2018) The construction and optimization of dimension system of severity evaluation of manufacturing process failure modes. Sci Technol Manag Res 38(03):205–212
107.
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 159:69–79CrossRef
108.
Liu HC, You JX, Lin QL, Li H (2015) Risk assessment in system FMEA combining fuzzy weighted average with fuzzy decision-making trial and evaluation laboratory. Int J Comput Integr Manuf 28(7):701–714CrossRef
109.
Nazeri A, Naderikia R (2017) A new fuzzy approach to identify the critical risk factors in maintenance management. Int J Adv Manuf Technol 92(9–12):3749–3783CrossRef
110.
Baykasoğlu A, Gölcük İ (2017) Comprehensive fuzzy FMEA model: a case study of ERP implementation risks. Oper Res:1–32
111.
Fattahi R, Khalilzadeh M (2018) Risk evaluation using a novel hybrid method based on FMEA, extended MULTIMOORA, and AHP methods under fuzzy environment. Saf Sci 102:290–300CrossRef
112.
Liu HC, Chen YZ, You JX, Li H (2016) Risk evaluation in failure mode and effects analysis using fuzzy digraph and matrix approach. J Intell Manuf 27(4):805–816CrossRef
113.
Chen JK (2017) Prioritization of corrective actions from utility viewpoint in FMEA application. Qual Reliab Eng Int 33(4):883–894CrossRef
114.
Kutlu AC, MEkmekçioğlu M (2012) Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP. Expert Syst Appl 39(1):61–67CrossRef
115.
Mandal S, Maiti J (2014) Risk analysis using FMEA: fuzzy similarity value and possibility theory based approach. Expert Syst Appl 41(7):3527–3537CrossRef
116.
Ghoushchi SJ, Yousefi S, Khazaeili M (2019) An extended FMEA approach based on the Z-MOORA and fuzzy BWM for prioritization of failures. Appl Soft Comput 81:1–13CrossRef
117.
Liu HC, Liu L, Bian QH, Lin QL, Dong N, Xu PC (2011) Failure mode and effects analysis using fuzzy evidential reasoning approach and grey theory. Expert Syst Appl 38(4):4403–4415CrossRef
118.
Deng X, Jiang W (2017) Fuzzy risk evaluation in failure mode and effects analysis using a D numbers based multi-sensor information fusion method. Sensors 17(9):2086CrossRef
119.
Wang W, Liu X, Chen X, Qin Y (2019) Risk assessment based on hybrid FMEA framework by considering decision maker’s psychological behavior character. Comput Ind Eng 136:516–527CrossRef
120.
Liu S, Guo X, Zhang L (2019) An improved assessment method for FMEA for a shipboard integrated electric propulsion system using fuzzy logic and DEMATEL theory. Energies 12(16):3162CrossRef
121.
Carpitella S, Certa A, Izquierdo J, La Fata CM (2018) A combined multi-criteria approach to support FMECA analyzes: a real-world case. Reliab Eng Syst Saf 169:394–402CrossRef
122.
Helvacioglu S, Ozen E (2014) Fuzzy based failure modes and effect analysis for yacht system design. Ocean Eng 79:131–141CrossRef
123.
Zhang Z, Chu X (2011) Risk prioritization in failure mode and effects analysis under uncertainty. Expert Syst Appl 38(1):206–214CrossRef
124.
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):12926–12934CrossRef
125.
Gargama H, Chaturvedi SK (2011) Criticality assessment models for failure mode effects and criticality analysis using fuzzy logic. IEEE Trans Reliab 60(1):102–110CrossRef
126.
Gupta G, Mishra RP (2017) A failure mode effect and criticality analysis of conventional milling machine using fuzzy logic: case study of RCM. Qual Reliab Eng Int 33(2):347–356CrossRef
127.
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 207:163–172CrossRef
128.
Liu HC, You JX, Shan MM, Shao LN (2015) Failure mode and effects analysis using intuitionistic fuzzy hybrid TOPSIS approach. Soft Comput 19(4):1085–1098CrossRef
129.
Foroozesh N, Tavakkoli-Moghaddam R, Mousavi SM (2018) Sustainable-supplier selection for manufacturing services: a failure mode and effects analysis model based on interval-valued fuzzy group decision-making. Int J Adv Manuf Technol 95(9–12):3609–3629CrossRef
130.
Zhao H, You JX, Liu HC (2017) Failure mode and effect analysis using MULTIMOORA method with continuous weighted entropy under interval-valued intuitionistic fuzzy environment. Soft Comput 21(18):5355–5367CrossRef
131.
Guo J (2016) A risk assessment approach for failure mode and effects analysis based on intuitionistic fuzzy sets and evidence theory. J Intell Fuzzy Syst 30(2):869–881MATHCrossRef
132.
Chang KH, Cheng CH (2010) A risk assessment methodology using intuitionistic fuzzy set in FMEA. Int J Syst Sci 41(12):1457–1471MathSciNetCrossRef
133.
Liu HC, Liu L, Li P (2014) Failure mode and effects analysis using intuitionistic fuzzy hybrid weighted Euclidean distance operator. Int J Syst Sci 45(10):2012–2030MathSciNetMATHCrossRef
134.
Chang KH, Wen TC, Chung HY (2018) Soft failure mode and effects analysis using the OWG operator and hesitant fuzzy linguistic term sets. J Intell Fuzzy Syst 34(4):2625–2639CrossRef
135.
136.
Liu HC, You JX, Li P, Su Q (2016) Failure mode and effect analysis under uncertainty: an integrated multiple criteria decision making approach. IEEE Trans Reliab 65(3):1380–1392CrossRef
137.
Li XY, Wang ZL, Xiong Y, Liu HC (2019) A novel failure mode and effect analysis approach integrating probabilistic linguistic term sets and fuzzy petri nets. IEEE Access 7:54918–54928CrossRef
138.
Huang J, Liu HC, Duan CY, Song MS (2019) An improved reliability model for FMEA using probabilistic linguistic term sets and TODIM method. Ann Oper Res:1–24
139.
Liu HC, You JX, You XY (2014) Evaluating the risk of healthcare failure modes using interval 2-tuple hybrid weighted distance measure. Comput Ind Eng 78:249–258CrossRef
140.
Chang KH (2016) Generalized multi-attribute failure mode analysis. Neurocomputing 175:90–100CrossRef
141.
Chang KH, Wen TC (2010) A novel efficient approach for DFMEA combining 2-tuple and the OWA operator. Expert Syst Appl 37(3):2362–2370CrossRef
142.
Bozdag E, Asan U, Soyer A, Serdarasan S (2015) Risk prioritization in failure mode and effects analysis using interval type-2 fuzzy sets. Expert Syst Appl 42(8):4000–4015CrossRef
143.
Liu HC, Li P, You JX, Chen YZ (2015) A novel approach for FMEA: combination of interval 2-tuple linguistic variables and gray relational analysis. Qual Reliab Eng Int 31(5):761–772CrossRef
144.
Li GF, Li Y, Chen CH, He JL, Hou TW, Chen JH (2019) Advanced FMEA method based on interval 2-tuple linguistic variables and TOPSIS. Qual Eng:1–10
145.
Wang L, Hu YP, Liu HC, Shi H (2019) A linguistic risk prioritization approach for failure mode and effects analysis: a case study of medical product development. Qual Reliab Eng Int 35(6):1735–1752CrossRef
146.
Liu HC, Hu YP, Wang JJ, Sun M (2018) Failure mode and effects analysis using two-dimensional uncertain linguistic variables and alternative queuing method. IEEE Trans Reliab 68(2):554–565CrossRef
147.
Hu YP, You XY, Wang L, Liu HC (2019) An integrated approach for failure mode and effect analysis based on uncertain linguistic GRA–TOPSIS method. Soft Comput 23(18):8801–8814CrossRef
148.
Liu HC, Wang LE, You XY (2019) Failure mode and effect analysis with extended grey relational analysis method in cloud setting. Total Qual Manag Bus Excell 30(7–8):745–767CrossRef
149.
Liu HC, Wang LE, Li Z, Hu YP (2018) Improving risk evaluation in FMEA with cloud model and hierarchical TOPSIS method. IEEE Trans Fuzzy Syst 27(1):84–95CrossRef
150.
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):1058–1072CrossRef
151.
Vahdani B, Salimi M, Charkhchian M (2015) A new FMEA method by integrating fuzzy belief structure and TOPSIS to improve risk evaluation process. Int J Adv Manuf Technol 77(1–4):357–368CrossRef
152.
Li Z, Chen L (2019) A novel evidential FMEA method by integrating fuzzy belief structure and grey relational projection method. Eng Appl Artif Intell 77:136–147CrossRef
153.
Chen L, Deng Y (2018) A new failure mode and effects analysis model using Dempster–Shafer evidence theory and grey relational projection method. Eng Appl Artif Intell 76:13–20CrossRef
154.
Li Z, Xiao F, Fei L, Mahadevan S, Deng Y (2017) An evidential failure mode and effects analysis using linguistic terms. Qual Reliab Eng Int 33(5):993–1010CrossRef
155.
Huang J, Li ZS, Liu HC (2017) New approach for failure mode and effect analysis using linguistic distribution assessments and TODIM method. Reliab Eng Syst Saf 167:302–309CrossRef
156.
Lo HW, Liou JJH (2018) A novel multiple-criteria decision-making-based FMEA model for risk assessment. Appl Soft Comput 73:684–696CrossRef
157.
Shi H, Wang L, Li XY, Liu HC (2019) A novel method for failure mode and effects analysis using fuzzy evidential reasoning and fuzzy Petri nets. J Ambient Intell Humaniz Comput:1–15
158.
Can GF (2018) An intutionistic approach based on failure mode and effect analysis for prioritizing corrective and preventive strategies. Hum Factors Ergon Manuf Serv Ind 28(3):130–147CrossRef
159.
Mahmoudi M, Amoozad Mahdiraji H, Jafarnejad A, Safari H (2019) Dynamic prioritization of equipment and critical failure modes: an interval-valued intuitionistic fuzzy condition-based model. Kybernetes 48:1913–1941CrossRef
160.
Nie WB, Liu WD, Wu ZY, Chen BS, Wu LL (2019) Failure mode and effects analysis by integrating Bayesian fuzzy assessment number and extended gray relational analysis-technique for order preference by similarity to ideal solution method. Qual Reliab Eng Int 35(6):1676–1697CrossRef
161.
Liu A, Qiu H, Lu H, Guo X (2019) A consensus model of probabilistic linguistic preference relations in group decision making based on feedback mechanism. IEEE Access 7:148231–148244
162.
Gou X, Xu Z, Herrera F (2018) Consensus reaching process for large-scale group decision making with double hierarchy hesitant fuzzy linguistic preference relations. Knowl-Based Syst 157:20–33
163.
Zhang H, Xiao J, Dong Y (2019) Integrating a consensus-reaching mechanism with bounded confidences into failure mode and effect analysis under incomplete context. Knowl-Based Syst 183:104873CrossRef
164.
Zhang H, Dong Y, Palomares-Carrascosa I, Zhou H (2018) Failure mode and effect analysis in a linguistic context: a consensus-based multi-attribute group decision-making approach. IEEE Trans Reliab 68(2):566–582CrossRef
165.
Wang R, Li Y, Zhu J et al (2018) Improved FMEA method for risk evaluation considering expert consensus. J Zhejiang Univ (Eng Sci) 52(6):1058–1067
166.
Zhu J, Wang R, Li Y (2018) Failure mode and effects analysis considering consensus and preferences interdependence. Algorithms 11(4):34MathSciNetMATHCrossRef
167.
Dong Y, Zhang H, Herrera-Viedma E (2016) Integrating experts' weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors. Decis Support Syst 84:1–15CrossRef
168.
Baynal KASIM, Sarı T, Akpınar B (2018) Risk management in automotive manufacturing process based on FMEA and grey relational analysis: a case study. Adv Prod Eng Manag 13(1):69–80
169.
Bian T, Zheng H, Yin L, Deng Y (2018) Failure mode and effects analysis based on D numbers and TOPSIS. Qual Reliab Eng Int 34(4):501–515CrossRef
170.
Chang KH, Chang YC, Lee YT (2014) Integrating TOPSIS and DEMATEL methods to rank the risk of failure of FMEA. Int J Inf Technol Decis Mak 13(06):1229–1257CrossRef
171.
Kutlu AC (2012) Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP. Pergamon Press, Inc. 39 61–67
172.
Chang KH, Cheng CH (2011) Evaluating the risk of failure using the fuzzy OWA and DEMATEL method. J Intell Manuf 22(2):113–129CrossRef
173.
Jiang W, Xie C, Wei B, Tang Y (2017) Failure mode and effects analysis based on Z-numbers. Intell Autom Soft Comput:1–8
174.
Yang J, Huang HZ, He LP, Zhu SP, Wen D (2011) Risk evaluation in failure mode and effects analysis of aircraft turbine rotor blades using Dempster–Shafer evidence theory under uncertainty. Eng Fail Anal 18(8):2084–2092CrossRef
175.
Du Y, Lu X, Su X, Hu Y, Deng Y (2016) New failure mode and effects analysis: an evidential downscaling method. Qual Reliab Eng Int 32(2):737–746CrossRef
176.
Emovon I, Norman RA, Alan JM (2015) An integrated multicriteria decision making methodology using compromise solution methods for prioritising risk of marine machinery systems. Ocean Eng 105:92–103CrossRef
177.
Mohsen O, Fereshteh N (2017) An extended VIKOR method based on entropy measure for the failure modes risk assessment – a case study of the geothermal power plant (GPP). Saf Sci 92:160–172
178.
Akbarzade Khorshidi H, Gunawan I, Ibrahim MY (2016) Applying UGF concept to enhance the assessment capability of FMEA. Qual Reliab Eng Int 32(3):1085–1093CrossRef
179.
Al Mashaqbeh S, Munive-Hernandez JE, Khurshid Khan M (2019) Using EWGM method to optimise the FMEA as a risk assessment methodology. Concurr Eng 27(2):144–154CrossRef
180.
Gu Y, Fu Y, Liang L (2016) Sensitivity analysis method of failure modes and effect analysis based on TOPSIS theory. J China Coal Soc 41(S2):598–604
181.
Chen H (2016) Sensitivity analysis of random evaluation parameters for process failure risk assessment. (doctoral dissertation)
182.
Chen B S, (2019) Risk assessment model and sensitivity analysis of failure mode of small batch custom production process. (doctoral dissertation)
183.
US Department of Defense (1980) Procedures for performing a failure mode, effects and criticality analysis. MIL-STD-1629. Washington (DC)
184.
Mikulak RJ, McDermott R, Beau M The basics of FMEA 2nd Edition
185.
AIAG (2002) FMEA-3 potential failure mode and effects analysis, 2nd edn. Automotive Industry Action Group (AIAG)
186.
JEP131A (2005) Potential Failure Mode and Effects Analysis (FMEA).JEDEC Solid State Technology Association
187.
Automotive industry action group (AIAG) Potential failure mode and effect analysis (FMEA) Reference Manual, FMEA reference manual 4th edition, 2008
188.
SAE J1739 (2011) Potential failure mode and effects analysis in design (Design FMEA) and potential failure mode and effects analysis in manufacturing and assembly processes (Process FMEA) and Effects Analysis for Machinery (Machinery FMEA). SAE Standard
189.
Automotive Industry Action Group, Verband Der Automobilindustrie (2019) AIAG-VDA failure mode and effects analysis (FMEA) handbook. Automotive Industry Action Group, Southfield
190.
Liu WD, Chen BS, Nie WB, Wu LL (2018) Process failure mode and effects analysis based on generalized trapezoidal fuzzy. Ind Eng Manag 23(03):33–41
191.
Anes V, Henriques E, Freitas M, Reis L (2018) A new risk prioritization model for failure mode and effects analysis. Qual Reliab Eng Int 34(4):516–528CrossRef
192.
Garcia PAA, Junior L, Curty I (2013) A weight restricted DEA model for FMEA risk prioritization. Production 23(3):500–507CrossRef
193.
Ouyang L, Zheng W, Zhu Y (2019) An interval probability-based FMEA model for risk assessment: a real-world case. Qual Reliab Eng Int 36(1):125–143CrossRef
194.
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):491–498CrossRef
195.
Park J, Park C, Ahn S (2018) Assessment of structural risks using the fuzzy weighted Euclidean FMEA and block diagram analysis. Int J Adv Manuf Technol 99(9–12):2071–2080CrossRef
196.
Geramian A, Shahin A, Minaei B, Antony J (2019) Enhanced FMEA: an integrative approach of fuzzy logic-based FMEA and collective process capability analysis. J Oper Res Soc:1–13
197.
Nie RX, Tian ZP, Wang XK, Wang JQ, Wang TL (2018) Risk evaluation by FMEA of supercritical water gasification system using multi-granular linguistic distribution assessment. Knowl-Based Syst 162:185–201
Metadaten
Titel
Literature review and prospect of the development and application of FMEA in manufacturing industry
verfasst von
Zhongyi Wu
Weidong Liu
Wenbin Nie
Publikationsdatum
03.01.2021
Verlag
Springer London
Erschienen in
The International Journal of Advanced Manufacturing Technology / Ausgabe 5-6/2021
Print ISSN: 0268-3768
Elektronische ISSN: 1433-3015
DOI
https://doi.org/10.1007/s00170-020-06425-0

Weitere Artikel der Ausgabe 5-6/2021

The International Journal of Advanced Manufacturing Technology 5-6/2021 Zur Ausgabe

ORIGINAL ARTICLE

Stability of micro-milling thin-walled part process

ORIGINAL ARTICLE

Milling stability prediction based on the hybrid interpolation scheme of the Newton and Lagrange polynomials

ORIGINAL ARTICLE

Multi-objective robust evolutionary optimization of the boring process of AISI 4130 steel

ORIGINAL ARTICLE

Simulation of sheet metal forming processes by presenting a bending-dependent inverse isogeometric methodology

ORIGINAL ARTICLE

A digital twin-based layout optimization method for discrete manufacturing workshop

Critical Review

Biomimetic strategies for fabricating musculoskeletal tissue scaffolds: a review

Premium Partner

    Marktübersichten

    Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen. 

    Zur Marktübersicht
    Bildnachweise