{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T19:34:33Z","timestamp":1777491273865,"version":"3.51.4"},"reference-count":53,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2019,4,24]],"date-time":"2019-04-24T00:00:00Z","timestamp":1556064000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100009697","name":"hashemite university","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100009697","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Concurrent Engineering"],"published-print":{"date-parts":[[2019,6]]},"abstract":"<jats:p>Failure modes and effect analysis (FMEA) is a proactive, highly structured and systematic approach for failure analysis. It has been also applied as a risk assessment tool, by ranking potential risks based on the estimation of risk priority numbers (RPNs). This article develops an improved FMEA methodology for strategic risk analysis. The proposed approach combines the analytic hierarchy process (AHP) technique with the exponential and weighted geometric mean method (EWGM) to support risk analysis. AHP is applied to estimate the weights of three risk factors: Severity (S), Occurrence (O) and Detection (D), which integrate the RPN for each risk. The EWGM method is applied for ranking RPNs. Combining AHP with EWGM allows avoiding repetition of FMEA results. The results of the developed methodology reveal that duplication of RPNs has been decreased, facilitating an effective risk ranking by offering a unique value for each risk. The proposed methodology not only focuses on high severity values for risk ranking but it also considers other risk factors (O and D), resulting in an enhanced risk assessment process. Furthermore, the weights of the three risk factors are considered. In this way, the developed methodology offers unique value for each risk in a simple way which makes the risk assessment results more accurate. This methodology provides a practical and systematic approach to support decision makers in assessing and ranking risks that could affect long-term strategy implementation. The methodology was validated through the case study of a power plant in the Middle East, assessing 84 risks within 9 risk categories. The case study revealed that top management should pay more attention to key risks associated with electricity price, gas emissions, lost-time injuries, bad odour and production.<\/jats:p>","DOI":"10.1177\/1063293x19844302","type":"journal-article","created":{"date-parts":[[2019,4,25]],"date-time":"2019-04-25T02:22:08Z","timestamp":1556158928000},"page":"144-154","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":15,"title":["Using EWGM method to optimise the FMEA as a risk assessment methodology"],"prefix":"10.1177","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8939-2981","authenticated-orcid":false,"given":"Sahar","family":"AL Mashaqbeh","sequence":"first","affiliation":[{"name":"Mechanical and Automotive Engineering, School of Engineering, Faculty of Engineering and Informatics, University of Bradford, Bradford, UK"},{"name":"Faculty of Engineering, The Hashemite University, Zarqa, Jordan"}]},{"given":"Jose Eduardo","family":"Munive-Hernandez","sequence":"additional","affiliation":[{"name":"Mechanical and Automotive Engineering, School of Engineering, Faculty of Engineering and Informatics, University of Bradford, Bradford, UK"}]},{"given":"Mohammed","family":"Khurshid Khan","sequence":"additional","affiliation":[{"name":"Mechanical and Automotive Engineering, School of Engineering, Faculty of Engineering and Informatics, University of Bradford, Bradford, UK"}]}],"member":"179","published-online":{"date-parts":[[2019,4,24]]},"reference":[{"key":"e_1_3_3_2_1","doi-asserted-by":"crossref","unstructured":"Achebe KO (2011). Risk Based Models for the Optimization of Oil and Gas Supply Chain Critical Infrastructure. NJIT. New Jersey Institute of Technology. Available at: https:\/\/doi.org\/10.3141\/2100-07","DOI":"10.3141\/2100-07"},{"key":"e_1_3_3_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/0022-2496(83)90028-7"},{"key":"e_1_3_3_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jece.2017.02.006"},{"key":"e_1_3_3_5_1","volume-title":"Proceedings of the world congress on engineering (WCE) 2015","author":"Aldairi J","year":"2015","unstructured":"Aldairi J, Khan MK, Munive-Hernandez JE (2015) A conceptual model for a hybrid knowledge-based lean six sigma maintenance system for sustainable buildings. In: Proceedings of the world congress on engineering (WCE) 2015, Vol. II, London, 1\u20133 July."},{"key":"e_1_3_3_6_1","volume-title":"Proceedings of the World Congress on Engineering","author":"ALMashaqbeh S","year":"2018","unstructured":"ALMashaqbeh S, Munive-Hernandez JE, Khan MK (2018) Developing a FMEA Methodology to Assess Risk Indicators in Power Plants, in: Proceedings of the World Congress on Engineering, London, UK, 4\u20136 July."},{"key":"e_1_3_3_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/1099-1638(200007\/08)16:4<313::AID-QRE434>3.0.CO;2-U"},{"key":"e_1_3_3_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/0951-8320(95)00068-D"},{"key":"e_1_3_3_9_1","doi-asserted-by":"publisher","DOI":"10.1108\/02656710010353885"},{"key":"e_1_3_3_10_1","doi-asserted-by":"publisher","DOI":"10.1177\/1063293X9900700307"},{"key":"e_1_3_3_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2016.01.007"},{"key":"e_1_3_3_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.microrel.2009.07.057"},{"key":"e_1_3_3_13_1","first-page":"90","article-title":"Generalized multi-attribute failure mode analysis","author":"Chang KH","year":"2015","unstructured":"Chang KH (2015) Generalized multi-attribute failure mode analysis. Neurocomputing 175(Part A): 90\u2013100.","journal-title":"Neurocomputing"},{"key":"e_1_3_3_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-009-0266-x"},{"key":"e_1_3_3_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-013-0747-9"},{"key":"e_1_3_3_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-006-0898-3"},{"key":"e_1_3_3_17_1","doi-asserted-by":"publisher","DOI":"10.3390\/s17092086"},{"key":"e_1_3_3_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10100-011-0212-9"},{"key":"e_1_3_3_19_1","doi-asserted-by":"publisher","DOI":"10.4236\/ojsst.2015.52003"},{"key":"e_1_3_3_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2011.07.005"},{"key":"e_1_3_3_21_1","volume-title":"Optimal Supply Chain Management in Oil, Gas, and Power Generation","author":"Jacoby D","year":"2012","unstructured":"Jacoby D (2012) Optimal Supply Chain Management in Oil, Gas, and Power Generation. Tulsa, OK: PennWell Corporation."},{"key":"e_1_3_3_22_1","volume-title":"Supply Chain Risk Assessment","author":"J\u00f3hannsson \u00fe","year":"2015","unstructured":"J\u00f3hannsson \u00fe 2015. Supply Chain Risk Assessment. Reykjav\u00edk University."},{"key":"e_1_3_3_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0950-4230(97)00051-X"},{"key":"e_1_3_3_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.06.060"},{"key":"e_1_3_3_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.06.044"},{"key":"e_1_3_3_26_1","doi-asserted-by":"publisher","DOI":"10.1002\/qre.2075"},{"issue":"1","key":"e_1_3_3_27_1","first-page":"90","article-title":"Failure mode and effect analysis of active magnetic bearings","volume":"38","author":"Lijesh KP","year":"2016","unstructured":"Lijesh KP, Hirani H (2016) Failure mode and effect analysis of active magnetic bearings. Tribology in Industry 38(1): 90\u2013101.","journal-title":"Tribology in Industry"},{"key":"e_1_3_3_28_1","doi-asserted-by":"publisher","DOI":"10.3390\/sym9080162"},{"key":"e_1_3_3_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2012.08.010"},{"key":"e_1_3_3_30_1","doi-asserted-by":"publisher","DOI":"10.1108\/IJQRM-10-2013-0169"},{"key":"e_1_3_3_31_1","doi-asserted-by":"publisher","DOI":"10.1080\/0951192X.2014.900865"},{"key":"e_1_3_3_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.enpol.2011.07.017"},{"key":"e_1_3_3_33_1","doi-asserted-by":"publisher","DOI":"10.1177\/1063293X16665662"},{"issue":"1","key":"e_1_3_3_34_1","first-page":"524","article-title":"A new approach for prioritization of failure modes in design FMEA using ANOVA","volume":"3","author":"Narayanagounder S","year":"2009","unstructured":"Narayanagounder S, Gurusami K (2009) A new approach for prioritization of failure modes in design FMEA using ANOVA. World Academy of Science, Engineering and Technology 3(1): 524\u2013531.","journal-title":"World Academy of Science, Engineering and Technology"},{"issue":"2","key":"e_1_3_3_35_1","first-page":"127","article-title":"Commentary arising from axiomatic measurement theory","volume":"4","author":"Narens L","year":"1993","unstructured":"Narens L, Luce RD (1993) Commentary arising from axiomatic measurement theory. Social Science 4(2): 127\u2013130.","journal-title":"Social Science"},{"key":"e_1_3_3_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijome.2016.12.001"},{"key":"e_1_3_3_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compchemeng.2016.03.010"},{"key":"e_1_3_3_38_1","doi-asserted-by":"publisher","DOI":"10.1504\/IJMOR.2018.089678"},{"key":"e_1_3_3_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jlp.2018.03.006"},{"key":"e_1_3_3_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0951-8320(02)00179-5"},{"key":"e_1_3_3_41_1","doi-asserted-by":"publisher","DOI":"10.1080\/13669877.2013.808689"},{"key":"e_1_3_3_42_1","doi-asserted-by":"publisher","DOI":"10.1016\/0377-2217(90)90057-I"},{"key":"e_1_3_3_43_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF03191825"},{"key":"e_1_3_3_44_1","doi-asserted-by":"publisher","DOI":"10.1108\/02656710110383737"},{"issue":"4","key":"e_1_3_3_45_1","first-page":"27","article-title":"Modified prioritization methodology for risk priority number in failure mode and effects analysis","volume":"3","author":"Sellappan N","year":"2013","unstructured":"Sellappan N, Oman S, Palanikumar K (2013) Modified prioritization methodology for risk priority number in failure mode and effects analysis. International Journal of Applied Science and Technology 3(4): 27\u201336.","journal-title":"International Journal of Applied Science and Technology"},{"key":"e_1_3_3_46_1","volume-title":"Failure Mode and Effect Analysis: FMEA from Theory to Execution","author":"Stamatis DH","year":"2003","unstructured":"Stamatis DH (2003) Failure Mode and Effect Analysis: FMEA from Theory to Execution. Milwaukee, WI: ASQ Quality Press."},{"key":"e_1_3_3_47_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2007.05.014"},{"key":"e_1_3_3_48_1","doi-asserted-by":"publisher","DOI":"10.1201\/9780203913307"},{"key":"e_1_3_3_49_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-014-6466-3"},{"key":"e_1_3_3_50_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2007.11.028"},{"key":"e_1_3_3_51_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0951-8320(01)00101-6"},{"key":"e_1_3_3_52_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.oceaneng.2014.11.037"},{"key":"e_1_3_3_53_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.psep.2017.08.015"},{"key":"e_1_3_3_54_1","doi-asserted-by":"publisher","DOI":"10.1177\/1063293X18795210"}],"container-title":["Concurrent Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/1063293X19844302","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/1063293X19844302","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/1063293X19844302","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T14:49:08Z","timestamp":1777387748000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/1063293X19844302"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,24]]},"references-count":53,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2019,6]]}},"alternative-id":["10.1177\/1063293X19844302"],"URL":"https:\/\/doi.org\/10.1177\/1063293x19844302","relation":{},"ISSN":["1063-293X","1531-2003"],"issn-type":[{"value":"1063-293X","type":"print"},{"value":"1531-2003","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,24]]}}}