{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T05:11:08Z","timestamp":1776489068838,"version":"3.51.2"},"reference-count":62,"publisher":"Emerald","issue":"7","license":[{"start":{"date-parts":[[2015,8,10]],"date-time":"2015-08-10T00:00:00Z","timestamp":1439164800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,8,10]]},"abstract":"\n Purpose<\/jats:title>\n \u2013 The purpose of this paper is to perform an extensive literature review in the area of decision making for condition-based maintenance (CBM) and identify possibilities for proactive online recommendations by considering real-time sensor data. Based on these, the paper aims at proposing a framework for proactive decision making in the context of CBM. <\/jats:p>\n <\/jats:sec>\n \n Design\/methodology\/approach<\/jats:title>\n \u2013 Starting with the manufacturing challenges and the main principles of maintenance, the paper reviews the main frameworks and concepts regarding CBM that have been proposed in the literature. Moreover, the terms of e-maintenance, proactivity and decision making are analysed and their potential relevance to CBM is identified. Then, an extensive literature review of methods and techniques for the various steps of CBM is provided, especially for prognosis and decision support. Based on these, limitations and gaps are identified and a framework for proactive decision making in the context of CBM is proposed. <\/jats:p>\n <\/jats:sec>\n \n Findings<\/jats:title>\n \u2013 In the proposed framework for proactive decision making, the CBM concept is enriched in the sense that it is structured into two components: the information space and the decision space. Moreover, it is extended in a way that decision space is further analyzed according to the types of recommendations that can be provided. Moreover, possible inputs and outputs of each step are identified. <\/jats:p>\n <\/jats:sec>\n \n Practical implications<\/jats:title>\n \u2013 The paper provides a framework for CBM representing the steps that need to be followed for proactive recommendations as well as the types of recommendations that can be given. The framework can be used by maintenance management of a company in order to conduct CBM by utilizing real-time sensor data depending on the type of decision required. <\/jats:p>\n <\/jats:sec>\n \n Originality\/value<\/jats:title>\n \u2013 The results of the work presented in this paper form the basis for the development and implementation of proactive Decision Support System (DSS) in the context of maintenance.<\/jats:p>\n <\/jats:sec>","DOI":"10.1108\/imds-03-2015-0071","type":"journal-article","created":{"date-parts":[[2015,7,28]],"date-time":"2015-07-28T10:16:55Z","timestamp":1438078615000},"page":"1225-1250","source":"Crossref","is-referenced-by-count":78,"title":["A proactive decision making framework for condition-based maintenance"],"prefix":"10.1108","volume":"115","author":[{"given":"Alexandros","family":"Bousdekis","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Babis","family":"Magoutas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dimitris","family":"Apostolou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gregoris","family":"Mentzas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2020122204595829500_b1","doi-asserted-by":"crossref","unstructured":"Aissani, N.\n , \n Beldjilali, B.\n and \n Trentesaux, D.\n (2009), \u201cDynamic scheduling of maintenance tasks in the petroleum industry: a reinforcement approach\u201d, \n Engineering Applications of Artificial Intelligence\n , Vol. 22 No. 7, pp. 1089-1103.","DOI":"10.1016\/j.engappai.2009.01.014"},{"key":"key2020122204595829500_b2","doi-asserted-by":"crossref","unstructured":"Artikis, A.\n , \n Baber, C.\n , \n Bizarro, P.\n , \n Canudas-de-Wit, C.\n , \n Etzion, O.\n , \n Fournier, F.\n , \n Goulart P.\n , \n Howes, A.\n , \n Lygeros, J.\n , \n Paliouras, G.\n , \n Sharfman, I.\n and \n Schuster, A.\n (2014), \u201cScalable proactive event-driven decision-making\u201d, \n Technology and Society Magazine, IEEE\n , Vol. 33 No. 3, pp. 35-41.","DOI":"10.1109\/MTS.2014.2345131"},{"key":"key2020122204595829500_b3","doi-asserted-by":"crossref","unstructured":"Bangalore, P.\n and \n Tjernberg, L.B.\n (2013), \u201cAn approach for self-evolving neural network based algorithm for fault prognosis in wind turbine\u201d, 2013 IEEE Grenoble PowerTech (POWERTECH), IEEE, Vol. 1 No. 1, pp. 1-6.","DOI":"10.1109\/PTC.2013.6652218"},{"key":"key2020122204595829500_b4","doi-asserted-by":"crossref","unstructured":"Banjevic, D.\n and \n Jardine, A.K.S.\n (2006), \u201cCalculation of reliability function and remaining useful life for a Markov failure time process\u201d, \n IMA Journal of Management Mathematics\n , Vol. 17 No. 2, pp. 115-130.","DOI":"10.1093\/imaman\/dpi029"},{"key":"key2020122204595829500_b5","doi-asserted-by":"crossref","unstructured":"Benedettini, O.\n , \n Baines, T.S.\n , \n Lightfoot, H.W.\n and \n Greenough, R.M.\n (2009), \u201cState-of-the-art in integrated vehicle health management\u201d, \n Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering\n , Vol. 223 No. 2, pp. 157-170.","DOI":"10.1243\/09544100JAERO446"},{"key":"key2020122204595829500_b6","doi-asserted-by":"crossref","unstructured":"Bennouna, O.\n and \n Roux, J.P.\n (2013), \u201cReal time diagnosis \n\t\t\t\t\t&\n\t\t\t\t fault detection for the reliability improvement of the embedded systems\u201d, \n Journal of Signal Processing Systems\n , Vol. 73 No. 2, pp. 153-160.","DOI":"10.1007\/s11265-013-0739-1"},{"key":"key2020122204595829500_b7","doi-asserted-by":"crossref","unstructured":"Besnard, F.\n and \n Bertling, L.\n (2010), \u201cAn approach for condition-based maintenance optimization applied to wind turbine blades\u201d, \n Sustainable Energy, IEEE Transactions On\n , Vol. 1 No. 2, pp. 77-83.","DOI":"10.1109\/TSTE.2010.2049452"},{"key":"key2020122204595829500_b8","doi-asserted-by":"crossref","unstructured":"Besnard, F.\n , \n Patriksson, M.\n , \n Stromberg, A.\n , \n Wojciechowski, A.\n , \n Fischer, K.\n and \n Bertling, L.\n (2011), \u201cA stochastic model for opportunistic maintenance planning of offshore wind farms\u201d, 2011 IEEE Trondheim PowerTech, IEEE, pp. 1-8.","DOI":"10.1109\/PTC.2011.6019376"},{"key":"key2020122204595829500_b9","doi-asserted-by":"crossref","unstructured":"Bouvard, K.\n , \n Artus, S.\n , \n Berenguer, C.\n and \n Cocquempot, V.\n (2011), \u201cCondition-based dynamic maintenance operations planning \n\t\t\t\t\t&\n\t\t\t\t grouping, application to commercial heavy vehicles\u201d, \n Reliability Engineering & System Safety\n , Vol. 96 No. 6, pp. 601-610.","DOI":"10.1016\/j.ress.2010.11.009"},{"key":"key2020122204595829500_b11","doi-asserted-by":"crossref","unstructured":"Caesarendra, W.\n , \n Widodo, A.\n , \n Thom, P.H.\n , \n Yang, B.S.\n and \n Setiawan, J.D.\n (2011), \u201cCombined probability approach and indirect data-driven method for bearing degradation prognostics\u201d, \n IEEE Transactions On Reliability\n , Vol. 60 No. 1, pp. 14-20.","DOI":"10.1109\/TR.2011.2104716"},{"key":"key2020122204595829500_b12","unstructured":"Castro, I.T.\n , \n Huynh, K.T.\n , \n Barros, A.\n and \n Berenguer, C.\n (2012), \u201cA predictive maintenance strategy based on mean residual life for systems subject to competing failures due to degradation and shocks\u201d, Proceedings of the 11th International Probabilistic Safety Assessment and Management Conference \n\t\t\t\t\t&\n\t\t\t\t the 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monitoring: value of online information and impact of measurement uncertainty\u201d, \n IEEE Transactions on Reliability\n , Vol. 61 No. 2, pp. 410-425.","DOI":"10.1109\/TR.2012.2194174"},{"key":"key2020122204595829500_b28","doi-asserted-by":"crossref","unstructured":"Irigaray, A.A.\n , \n Gilabert, E.\n , \n Jantunen, E.\n and \n Adgar, A.\n (2009), \u201cUbiquitous computing for dynamic condition-based maintenance\u201d, \n Journal of Quality in Maintenance Engineering\n , Vol. 15 No. 2, pp. 151-166.","DOI":"10.1108\/13552510910961101"},{"key":"key2020122204595829500_b29","doi-asserted-by":"crossref","unstructured":"Iung, B.\n , \n Levrat, E.\n , \n Marquez, A.C.\n and \n Erbe, H.\n (2009), \u201cConceptual framework for e-maintenance: illustration by e-maintenance technologies and platforms\u201d, \n Annual Reviews in Control\n , Vol. 33 No. 2, pp. 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Electronics\n , Vol. 53 No. 6, pp. 1842-1852.","DOI":"10.1109\/TIE.2006.885131"},{"key":"key2020122204595829500_b34","doi-asserted-by":"crossref","unstructured":"Kaiser, K.A.\n and \n Gebraeel, N.Z.\n (2009), \u201cPredictive maintenance management using sensor-based degradation models\u201d, \n IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans\n , Vol. 39 No. 4, pp. 840-849.","DOI":"10.1109\/TSMCA.2009.2016429"},{"key":"key2020122204595829500_b35","doi-asserted-by":"crossref","unstructured":"Kim, H.E.\n , \n Tan, A.C.\n , \n Mathew, J.\n and \n Choi, B.K.\n (2012), \u201cBearing fault prognosis based on health state probability estimation\u201d, \n Expert Systems with Applications\n , Vol. 39 No. 5, pp. 5200-5213.","DOI":"10.1016\/j.eswa.2011.11.019"},{"key":"key2020122204595829500_b37","unstructured":"Lebold, M.\n and \n Thurston, M.\n (2001), \u201cOpen standards for condition-based maintenance and prognostic systems\u201d, 5th Annual Maintenance and Reliability Conference (MARCON 2001), Gatlinburg, TN, May 25-27."},{"key":"key2020122204595829500_b38","unstructured":"Lee, J.\n , \n Abujamra, R.\n , \n Jardine, A.K.\n , \n Lin, D.\n and \n Banjevic, D.\n (2004), \u201cAn integrated platform for diagnostics, prognostics and maintenance optimization\u201d, Proceedings of the Intelligent Maintenance Systems, pp. 15-27."},{"key":"key2020122204595829500_b39","doi-asserted-by":"crossref","unstructured":"Lee, J.\n , \n Ni, J.\n , \n Djurdjanovic, D.\n , \n Qiu, H.\n and \n Liao, H.\n (2006), \u201cIntelligent prognostics tools and e-maintenance\u201d, \n Computers in Industry, Special Issue on e-Maintenance\n , Vol. 57 No. 6, pp. 476-489.","DOI":"10.1016\/j.compind.2006.02.014"},{"key":"key2020122204595829500_b40","doi-asserted-by":"crossref","unstructured":"L\u00e9ger, J.B.\n and \n Morel, G.\n (2001), \u201cIntegration of maintenance in the enterprise: towards an enterprise modeling-based framework compliant with proactive maintenance strategy\u201d, \n Production Planning and Control\n , Vol. 12 No. 2, pp. 176-187.","DOI":"10.1080\/09537280150501275"},{"key":"key2020122204595829500_b41","unstructured":"Levrat, E.\n and \n Iung, B.\n (2007), \u201cTELMA: a full e-maintenance platform\u201d, Proceedings of the Second World Congress on Engineering Asset Management (WCEAM), Harrogate, June 11-14."},{"key":"key2020122204595829500_b42","doi-asserted-by":"crossref","unstructured":"Macchi, M.\n , \n M\u00e1rquez, A.C.\n , \n Holgado, M.\n , \n Fumagalli, L.\n and \n Mart\u00ednez, L.B.\n (2014), \u201cValue-driven engineering of e-maintenance platforms\u201d, \n Journal of Manufacturing Technology Management\n , Vol. 25 No. 4, pp. 568-598.","DOI":"10.1108\/JMTM-04-2013-0039"},{"key":"key2020122204595829500_b43","unstructured":"Magoutas, B.\n , \n Stojanovic, N.\n , \n Bousdekis, A.\n , \n Apostolou, D.\n , \n Mentzas, G.\n and \n Stojanovic, L.\n (2014), \u201cAnticipation-driven architecture for proactive enterprise decision making\u201d, CAiSE (Forum\/Doctoral Consortium), pp. 121-128."},{"key":"key2020122204595829500_b46","doi-asserted-by":"crossref","unstructured":"Muller, A.\n , \n Crespo Marquez, A.\n and \n Iung, B.\n (2008b), \u201cOn the concept of e-maintenance: review and current research\u201d, \n Reliability Engineering & System Safety\n , Vol. 93 No. 8, pp. 1165-1187.","DOI":"10.1016\/j.ress.2007.08.006"},{"key":"key2020122204595829500_b45","doi-asserted-by":"crossref","unstructured":"Muller, A.\n , \n Suhner, M.C.\n and \n Iung, B.\n (2007), \u201cMaintenance alternative integration to prognosis process engineering\u201d, \n Journal of Quality in Maintenance Engineering\n , Vol. 13 No. 2, pp. 198-211.","DOI":"10.1108\/13552510710753096"},{"key":"key2020122204595829500_b44","doi-asserted-by":"crossref","unstructured":"Muller, A.\n , \n Suhner, M.C.\n and \n Iung, B.\n (2008a), \u201cFormalisation of a new prognosis model for supporting proactive maintenance implementation on industrial system\u201d, \n Reliability Engineering & System Safety\n , Vol. 93 No. 2, pp. 234-253.","DOI":"10.1016\/j.ress.2006.12.004"},{"key":"key2020122204595829500_b47","doi-asserted-by":"crossref","unstructured":"Nandi, S.\n , \n Toliyat, H.A.\n and \n Li, X.\n (2005), \u201cCondition monitoring and fault diagnosis of electrical motors-a review\u201d, \n IEEE Transactions on Energy Conversion\n , Vol. 20 No. 4, pp. 719-729.","DOI":"10.1109\/TEC.2005.847955"},{"key":"key2020122204595829500_b48","doi-asserted-by":"crossref","unstructured":"Pal, A.\n and \n Ceglarek, D.\n (2013), \u201cModeling of decision making process for product service failure diagnosis\u201d, \n Procedia CIRP\n , Vol. 11, pp. 32-37.","DOI":"10.1016\/j.procir.2013.07.067"},{"key":"key2020122204595829500_b49","unstructured":"Pal, A.\n , \n Franciosa, P.\n and \n Ceglarek, D.\n (2014), \u201cCorrective actions of product service failures via surrogate modelling of dimensional variations\u201d, in \n Guan, Y.\n and \n Liao, H.\n (Eds), \n Proceedings of the 2014 IIE Annual Conference Institute of Industrial Engineers-Publisher\n , pp. 2271-2280."},{"key":"key2020122204595829500_b50","doi-asserted-by":"crossref","unstructured":"Peng, Y.\n , \n Dong, M.\n and \n Zuo, M.J.\n (2010), \u201cCurrent status of machine prognostics in condition-based maintenance: a review\u201d, \n The International Journal of Advanced Manufacturing Technology\n , Vol. 50 Nos 1\/4, pp. 297-313.","DOI":"10.1007\/s00170-009-2482-0"},{"key":"key2020122204595829500_b51","doi-asserted-by":"crossref","unstructured":"Prakash, P.K.S.\n and \n Ceglarek, D.\n (2013), \u201cMulti-step functional process adjustments to reduce no-fault-found product failures in service caused by in-tolerance faults\u201d, \n Procedia CIRP\n , Vol. 11 No. 1, pp. 38-43.","DOI":"10.1016\/j.procir.2013.07.068"},{"key":"key2020122204595829500_b52","doi-asserted-by":"crossref","unstructured":"Qian, Y.\n , \n Xu, L.\n , \n Li, X.\n , \n Lin, L.\n and \n Kraslawski, A.\n (2008), \u201cLUBRES: an expert system development and implementation for real-time fault diagnosis of a lubricating oil refining process\u201d, \n Expert Systems with Applications\n , Vol. 35 No. 3, pp. 1252-1266.","DOI":"10.1016\/j.eswa.2007.07.061"},{"key":"key2020122204595829500_b53","doi-asserted-by":"crossref","unstructured":"Ruiz-Mezcua, B.\n , \n Garcia-Crespo, A.\n , \n Lopez-Cuadrado, J.L.\n and \n Gonzalez-Carrasco, I.\n (2011), \u201cAn expert system development tool for non AI experts\u201d, \n Expert Systems with Applications\n , Vol. 38 No. 1, pp. 597-609.","DOI":"10.1016\/j.eswa.2010.07.009"},{"key":"key2020122204595829500_b54","doi-asserted-by":"crossref","unstructured":"Salfner, F.\n and \n Malek, M.\n (2007), \u201cUsing hidden semi-Markov models for effective online failure prediction\u201d, 26th IEEE International Symposium on Reliable Distributed Systems, SRDS 2007, IEEE, pp. 161-174.","DOI":"10.1109\/SRDS.2007.35"},{"key":"key2020122204595829500_b55","doi-asserted-by":"crossref","unstructured":"Takata, S.\n , \n Kimura, F.\n , \n Van Houten, F.J.A.M.\n ,\n Westkamper, E.\n , \n Shpitalni, M.\n , \n Ceglarek, D.\n and \n Lee, J.\n (2004), \u201cMaintenance: changing role in life cycle management\u201d, \n Annals of the CIRP\n , Vol. 53 No. 2, pp. 643-656.","DOI":"10.1016\/S0007-8506(07)60033-X"},{"key":"key2020122204595829500_b56","doi-asserted-by":"crossref","unstructured":"Tobon-Mejia, D.A.\n , \n Medjaher, K.\n and \n Zerhouni, N.\n (2012a), \u201cCNC machine tool\n\t\t\t\t\t'\n\t\t\t\ts wear diagnostic and prognostic by using dynamic Bayesian networks\u201d, \n Mechanical Systems and Signal Processing\n , Vol. 28 No. 1, pp. 167-182.","DOI":"10.1016\/j.ymssp.2011.10.018"},{"key":"key2020122204595829500_b57","doi-asserted-by":"crossref","unstructured":"Tobon-Mejia, D.A.\n , \n Medjaher, K.\n , \n Zerhouni, N.\n and \n Tripot, G.\n (2012b), \u201cA data-driven failure prognostics method based on mixture of Gaussians hidden Markov models\u201d, \n IEEE Transactions on Reliability\n , Vol. 61 No. 2, pp. 491-503.","DOI":"10.1109\/TR.2012.2194177"},{"key":"key2020122204595829500_b58","doi-asserted-by":"crossref","unstructured":"Veldman, J.\n , \n Wortmann, H.\n and \n Klingenberg, W.\n (2011), \u201cTypology of condition based maintenance\u201d, \n Journal of Quality in Maintenance Engineering\n , Vol. 17 No. 2, pp. 183-202.","DOI":"10.1108\/13552511111134600"},{"key":"key2020122204595829500_b59","doi-asserted-by":"crossref","unstructured":"Venkatasubramanian, V.\n (2005), \u201cPrognostic and diagnostic monitoring of complex systems for product lifecycle management: challenges and opportunities\u201d, \n Computers & Chemical Engineering\n , Vol. 29 No. 6, pp. 1253-1263.","DOI":"10.1016\/j.compchemeng.2005.02.026"},{"key":"key2020122204595829500_b60","doi-asserted-by":"crossref","unstructured":"Voisin, A.\n , \n Levrat, E.\n , \n Cocheteux, P.\n and \n Iung, B.\n (2010), \u201cGeneric prognosis model for proactive maintenance decision support: application to pre-industrial e-maintenance test bed\u201d, \n Journal of Intelligent Manufacturing\n , Vol. 21 No. 2, pp. 177-193.","DOI":"10.1007\/s10845-008-0196-z"},{"key":"key2020122204595829500_b61","doi-asserted-by":"crossref","unstructured":"Waeyenbergh, G.\n and \n Pintelon, L.\n (2004), \u201cMaintenance concept development: a case study\u201d, \n International Journal of Production Economics\n , Vol. 89 No. 3, pp. 395-405.","DOI":"10.1016\/j.ijpe.2003.09.008"},{"key":"key2020122204595829500_b62","doi-asserted-by":"crossref","unstructured":"Wu, S.J.\n , \n Gebraeel, N.\n , \n Lawley, M.A.\n and \n Yih, Y.\n (2007), \u201cA neural network integrated decision support system for condition-based optimal predictive maintenance policy\u201d, \n IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans\n , Vol. 37 No. 2, pp. 226-236.","DOI":"10.1109\/TSMCA.2006.886368"},{"key":"key2020122204595829500_frd1","doi-asserted-by":"crossref","unstructured":"Brotherton, T.\n , \n Jahns, G.\n , \n Jacobs, J.\n and \n Wroblewski, D.\n (2000), \u201cPrognosis of faults in gas turbine engines\u201d, \n 2000 IEEE Aerospace Conference Proceedings\n , IEEE, Vol. 6 No. 1, pp. 163-171.","DOI":"10.1109\/AERO.2000.877892"},{"key":"key2020122204595829500_frd2","unstructured":"Dumbill, E.\n (2012), \n Planning for Big Data\n , O\u2019Reilly Media Inc., Sebastopol, CA."},{"key":"key2020122204595829500_frd3","doi-asserted-by":"crossref","unstructured":"Genc, E.\n , \n Duffie, N.\n and \n Reinhart, G.\n (2014), \u201cEvent-based supply chain early warning system for an adaptive production control\u201d, \n Procedia CIRP\n , Vol. 19 No. 1, pp. 39-44.","DOI":"10.1016\/j.procir.2014.04.076"},{"key":"key2020122204595829500_frd4","unstructured":"Holmberg, K.\n , \n Komonen, K.\n , \n Oedewald, P.\n , \n Peltonen, M.\n , \n Reiman, T.\n , \n Rouhiainen, V.\n , \n Tervo, J.\n and \n Heino, P.\n (2004), \u201cSafety and reliability technology review\u201d, VTT Industrial Systems, Espoo."},{"key":"key2020122204595829500_frd5","doi-asserted-by":"crossref","unstructured":"Iung, B.\n , \n Veron, M.\n , \n Suhner, M. 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