The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A fully data-driven FMEA framework for risk assessment on manufacturing processes using a hybrid approach
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Conventional RPN-based prioritization has established limitations, including subjectivity in scoring and the possibility that different combinations of severity, occurrence, and detection generate identical RPN values.
“At the same time, the study recognizes established limitations of conventional RPN-based prioritization-including subjectivity in scoring and the possibility that different combinations of severity, occurrence, and detection generate identical RPN values (Ervural & Ayaz, 2023).”
From An FMEA-Based Framework for Operational Technology Security Risk Prioritization in Manufacturing (2026) · cites this paper as Ervural & Ayaz, 2023
Citations
Cites
Applying the concept of exponential approach to enhance the assessment capability of FMEA
Chang, K.-H., Chang, Y.-C., & Lai, P.-T. (2014) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-013-0747-9 · Cited by 81
Flagged first, then by citations
Research works printed but not linked: 67
- Bowles, 1995, Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis, Reliab. Eng. Syst. Saf., 50, 203, 10.1016/0951-8320(95)00068-D · DOI · Paper page
- Kumari, 2023, Failure mode and effects analysis of common effluent treatment plants of humid sub-tropical regions using fuzzy based MCDM methods, Eng. Fail. Anal., 145, 10.1016/j.engfailanal.2022.107010 · DOI
- Pillay, 2003, Modified failure mode and effects analysis using approximate reasoning, Reliab. Eng. Syst. Saf., 79, 69, 10.1016/S0951-8320(02)00179-5 · DOI · Paper page
- Wang, 2021, Primary failure mode and effects analysis with function-motion-action hierarchy structure for mechatronic systems, Eng. Fail. Anal., 130, 10.1016/j.engfailanal.2021.105775 · DOI
- Price, 1997, Combining functional and structural reasoning for safety analysis of electrical designs, Knowl. Eng. Rev., 12, 271, 10.1017/S0269888997003020 · DOI
- Dağsuyu, 2016, Classical and fuzzy FMEA risk analysis in a sterilization unit, Comput. Ind. Eng., 101, 286, 10.1016/j.cie.2016.09.015 · DOI
- Liu, 2019, Improved FMEA Methods for Proactive Healthcare Risk Analysis, Improv. FMEA Methods Proactive Healthc, Risk Anal., 1
- H.İ. Ayaz, M.C. Testik, Automation of FMEA for computer servers using log data with grey relational analysis, in: 2nd Int. Conf. Comput. Sci. Eng. UBMK 2017, Institute of Electrical and Electronics Engineers Inc., 2017: pp. 616–620. doi:10.1109/UBMK.2017.8093480. · DOI
- Park, 2019, Fuzzy-inference-based failure mode and effects analysis of the hydrogen production process using Thermococcus onnurineus NA1, Int. J. Hydrogen Energy, 44, 13135, 10.1016/j.ijhydene.2019.03.227 · DOI
- Ahn, 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, 10.1016/j.jpowsour.2017.08.028 · DOI
- Rajpathak, 2013, An ontology based text mining system for knowledge discovery from the diagnosis data in the automotive domain, Comput. Ind., 64, 565, 10.1016/j.compind.2013.03.001 · DOI
- Chang, 2013, Enhancing FMEA assessment by integrating grey relational analysis and the decision making trial and evaluation laboratory approach, Eng. Fail. Anal., 31, 211, 10.1016/j.engfailanal.2013.02.020 · DOI
- Liu, 2013, Risk evaluation approaches in failure mode and effects analysis: A literature review, Expert Syst. Appl., 40, 828, 10.1016/j.eswa.2012.08.010 · DOI
- Adhikary, 2014, Multi criteria FMECA for coal-fired thermal power plants using COPRAS-G, Int. J. Qual. Reliab. Manag., 31, 601, 10.1108/IJQRM-04-2013-0068 · DOI
- Kabak, 2017, Multiple attribute group decision making: A generic conceptual framework and a classification scheme, Knowledge-Based Syst., 123, 13, 10.1016/j.knosys.2017.02.011 · DOI
- Vahdani, 2014, A new FMEA method by integrating fuzzy belief structure and TOPSIS to improve risk evaluation process, Int. J. Adv. Manuf. Technol., 77, 357, 10.1007/s00170-014-6466-3 · DOI
- Peng Tian, 2018, An integrated approach for failure mode and effects analysis based on fuzzy best-worst, relative entropy, and VIKOR methods, Appl. Soft Comput. J., 72, 636, 10.1016/j.asoc.2018.03.037 · DOI
- Yucesan, 2021, Failure modes and effects analysis based on neutrosophic analytic hierarchy process: method and application, Soft. Comput., 25, 11035, 10.1007/s00500-021-05840-z · DOI
- Z. xuan Zhang, L. Yang, Y. ning Cao, Y, 2022, wei Xu, An Improved FMEA Method Based on ANP with Probabilistic Linguistic Term Sets, Int. J. Fuzzy Syst.
- Akram, 2022, An integrated ELECTRE-I approach for risk evaluation with hesitant Pythagorean fuzzy information, Expert Syst. Appl., 200, 10.1016/j.eswa.2022.116945 · DOI
- Liu, 2021, An improved failure mode and effect analysis method for multi-criteria group decision-making in green logistics risk assessment, Reliab. Eng. Syst. Saf., 215, 10.1016/j.ress.2021.107826 · DOI
- Filz, 2021, Data-driven failure mode and effect analysis (FMEA) to enhance maintenance planning, Comput. Ind., 129, 10.1016/j.compind.2021.103451 · DOI
- Yang, 2013, Data mining based fault isolation with FMEA rank: A case study of APU fault identification, IEEE Conf. Progn. Heal. Manag. IEEE, 2013, 1
- Lai, 2022, A data-driven ensemble ranking system of production quality across manufacturers—A case study for risk assessment in the solar industry, Qual. Reliab. Eng. Int., 1
- Antomarioni, 2020, A data-driven approach to extend failure analysis: A framework development and a case study on a hydroelectric power plant, Energies, 13, 10.3390/en13236400 · DOI
- Biswas, 2022, ABAC: Alternative by alternative comparison based multi-criteria decision making method, Expert Syst. Appl., 208, 10.1016/j.eswa.2022.118174 · DOI
- Xu, 2020, A data-driven approach for constructing the component-failure mode matrix for FMEA, J. Intell. Manuf., 31, 249, 10.1007/s10845-019-01466-z · DOI
- Boral, 2020, An integrated approach for fuzzy failure modes and effects analysis using fuzzy AHP and fuzzy MAIRCA, Eng. Fail. Anal., 108, 10.1016/j.engfailanal.2019.104195 · DOI · Paper page
- Testik, 2023, Fuzzy FMEA in risk assessment for test and calibration laboratories, Qual. Reliab. Eng. Int., 39, 575, 10.1002/qre.3198 · DOI
- Boral, 2021, Failure analysis of CNC machines due to human errors: An integrated IT2F-MCDM-based FMEA approach, Eng. Fail. Anal., 130, 10.1016/j.engfailanal.2021.105768 · DOI
- Sharma, 2005, Systematic failure mode effect analysis (FMEA) using fuzzy linguistic modelling, Int. J. Qual. Reliab. Manag., 22, 986, 10.1108/02656710510625248 · DOI
- Liu, 2019, Failure mode and effect analysis using multi-criteria decision making methods: A systematic literature review, Comput. Ind. Eng., 135, 881, 10.1016/j.cie.2019.06.055 · DOI
- Lo, 2018, A novel multiple-criteria decision-making-based FMEA model for risk assessment, Appl. Soft Comput. J., 73, 684, 10.1016/j.asoc.2018.09.020 · DOI
- Wang, 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. J., 70, 633, 10.1016/j.asoc.2018.06.015 · DOI
- Liu, 2015, A novel approach for failure mode and effects analysis using combination weighting and fuzzy VIKOR method, Appl. Soft Comput. J., 28, 579, 10.1016/j.asoc.2014.11.036 · DOI
- Li, 2020, Advanced FMEA method based on interval 2-tuple linguistic variables and TOPSIS, Qual. Eng., 32, 653, 10.1080/08982112.2019.1677913 · DOI
- Nabizadeh, 2021, Developing a fuzzy goal programming model for health, safety and environment risks based on hybrid fuzzy FMEA-VIKOR method, J. Eng. Des. Technol., 19, 317
- Yang, 2021, Improved FMEA based on IVF and fuzzy VIKOR method: A case study of workpiece box system of CNC gear milling machine, Qual. Reliab. Eng. Int., 37, 2478, 10.1002/qre.2870 · DOI
- Kulcsár, 2020, Pairwise comparison based failure mode and effects analysis (FMEA), MethodsX., 7, 10.1016/j.mex.2020.101007 · DOI
- Hassan, 2020, Fuzzy-analytical-hierarchy process in failure mode and effect analysis (FMEA) to identify process failure in the warehouse of a cement industry, J. Eng. Des. Technol., 18, 378
- Zandi, 2020, Agricultural risk management using fuzzy topsis analytical hierarchy process (Ahp) and failure mode and effects analysis (fmea), Agric., 10, 1
- Lian, 2022, An Integrated Approach for Failure Mode and Effects Analysis Based on Weight of Risk Factors and Fuzzy PROMETHEE II
- Deveci, 2020, A modified interval valued intuitionistic fuzzy CODAS method and its application to multi-criteria selection among renewable energy alternatives in Turkey, Appl. Soft Comput. J., 96, 10.1016/j.asoc.2020.106660 · DOI
- Almeraz-Durán, 2021, A proposed framework for developing fmea method using pythagorean fuzzy codas, Symmetry (Basel), 13
- S. Rahnamay Bonab, E. Osgooei, Environment risk assessment of wastewater treatment using FMEA method based on Pythagorean fuzzy multiple-criteria decision-making, in: Environ. Dev. Sustain., Springer Netherlands, 2022. doi:10.1007/s10668-022-02555-5. · DOI
- Huang, 2022, An improved reliability model for FMEA using probabilistic linguistic term sets and TODIM method, Ann. Oper. Res., 312, 235, 10.1007/s10479-019-03447-0 · DOI
- Koomsap, 2018, Improving risk assessment for customer-oriented FMEA, Total Qual. Manag. Bus. Excell., 29, 1563, 10.1080/14783363.2016.1274229 · DOI
- Maniram Kumar, 2018, Fuzzy based risk prioritisation in an auto LPG dispensing station, Saf. Sci., 101, 231, 10.1016/j.ssci.2017.09.011 · DOI
- Anes, 2018, A new risk prioritization model for failure mode and effects analysis, Qual. Reliab. Eng. Int., 34, 516, 10.1002/qre.2269 · DOI
- Mirghafoori, 2018, Analysis of the barriers affecting the quality of electronic services of libraries by VIKOR, FMEA and entropy combined approach in an intuitionistic-fuzzy environment, J. Intell. Fuzzy Syst., 34, 2441
- Uslu, 2022, A new multidimensional process type FMEA approach: Defense and aerospace industry application, J. Fac. Eng. Archit. Gazi Univ., 37, 1411
- Zhu, 2021, Failure mode and effect analysis: A three-way decision approach, Eng. Appl. Artif. Intel., 106, 10.1016/j.engappai.2021.104505 · DOI
- Yazdi, 2019, Improving failure mode and effect analysis (FMEA) with consideration of uncertainty handling as an interactive approach, Int. J. Interact. Des. Manuf., 13, 441, 10.1007/s12008-018-0496-2 · DOI
- Hajighasemi, 2018, A new approach in failure modes and effects analysis based on compromise solution by considering objective and subjective weights with interval-valued intuitionistic fuzzy sets, Iran. J. Fuzzy Syst., 15, 139
- Tavana, 2021, An integrated fuzzy framework for analyzing barriers to the implementation of continuous improvement in manufacturing, Int. J. Qual. Reliab. Manag., 38, 116, 10.1108/IJQRM-06-2019-0196 · DOI
- Brun, 2018, Assessing risk through composite FMEA with pairwise matrix and Markov chains, Int. J. Qual. Reliab. Manag., 35, 1709, 10.1108/IJQRM-04-2017-0080 · DOI
- Huang, 2018, A new method to evaluate risk in failure mode and effects analysis under fuzzy information, Soft. Comput., 22, 4779, 10.1007/s00500-017-2664-x · DOI
- von Ahsen, 2008, Cost-oriented failure mode and effects analysis, Int. J. Qual. Reliab. Manag., 25, 466, 10.1108/02656710810873871 · DOI
- Srivastava, 2018, Mitigation of Risk Using Rule Based Fuzzy FMEA Approach, in, 26
- Qin, 2020, Failure mode and effects analysis (FMEA) for risk assessment based on interval type-2 fuzzy evidential reasoning method, Appl. Soft Comput. J., 89, 10.1016/j.asoc.2020.106134 · DOI
- Alizadeh, 2022, Risk assessment of physical unit operations of wastewater treatment plant using fuzzy FMEA method : a case study in the northwest of, Iran, 1
- Thoppil, 2020, On the Criticality Analysis of Computer Numerical Control Lathe Subsystems for Predictive Maintenance, Arab. J. Sci. Eng., 45, 5259, 10.1007/s13369-020-04397-7 · DOI
- Ouyang, 2020, An interval probability-based FMEA model for risk assessment: A real-world case, Qual. Reliab. Eng. Int., 36, 125, 10.1002/qre.2563 · DOI
- Zavadskas, 2016, Integrated Determination of Objective Criteria Weights in MCDM, Int. J. Inf. Technol. Decis. Mak., 15, 267, 10.1142/S0219622016500036 · DOI
- Sharkasi, 2022, A modified CRITIC with a reference point based on fuzzy logic and hamming distance, Knowledge-Based Syst., 10.1016/j.knosys.2022.109768 · DOI
- Diakoulaki, 1995, Determining objective weights in multiple criteria problems: The critic method, Comput. Oper. Res., 22, 763, 10.1016/0305-0548(94)00059-H · DOI
- Krishnan, 2021, A Modified CRITIC Method to Estimate the Objective Weights of Decision Criteria, Symmetry (Basel)., 13, 973, 10.3390/sym13060973 · DOI
Cited by
Sorted by citations
An FMEA-Based Framework for Operational Technology Security Risk Prioritization in Manufacturing
Nugraha, A. A. (2026) · Jurnal Rekayasa Industri (JRI) · doi:10.37631/jri.v8i2.2497
Metadata
- Authors
- Ervural, B., & Ayaz, H. I.
- Affiliations
- Necmettin Erbakan University (TR)
- ORCID
- Ervural, Bilal
- Venue
- Engineering Failure Analysis
- Publisher
- Elsevier BV
- Published
- 2023-10
- Volume
- 152
- Pages
- 107525
- ISSN
- 1350-6307 (ISSN-L)
- OpenAlex
- W4385494529
- Cited by
- 91
- References
- 1
- Citations by year
- 2026: 55 · 2025: 20 · 2024: 12 · 2023: 4
- FWCI
- 13.46
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Engineering Failure Analysis (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Multi-Criteria Decision Making
- Social Sciences › Business, Management and Accounting › Strategy and Management › Management and Optimization Techniques
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Risk and Safety Analysis
- Keywords
- failure mode and effects analysis, data-driven risk assessment, risk prioritization, failure mode ranking
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review