{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T18:34:23Z","timestamp":1776191663450,"version":"3.50.1"},"reference-count":137,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,8,29]],"date-time":"2022-08-29T00:00:00Z","timestamp":1661731200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,8,29]],"date-time":"2022-08-29T00:00:00Z","timestamp":1661731200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100006070","name":"University of the Andes","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100006070","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Intell Manuf"],"published-print":{"date-parts":[[2023,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The last decade saw the rise of digitalization and data-supported decision making in the manufacturing industry: the Fourth Industrial Revolution. This trend, also known as Industry 4.0, allows manufacturing enterprises to discover manufacturing uncertainties and measure their real manufacturing capability. One of the ways in which Industry 4.0 trends have been exploited is in the improvement of maintenance, which went from following planning-focused paradigms to more proactive-focused stances. Enabling the Industry 4.0 vision for maintenance purposes has historically required companies to either replace or upgrade their existing legacy devices. It is through the latter course of action that Smart retrofitting in maintenance (SRM) intends to bring value to enterprises. This work aims to present a systematic literature review on SRM, utilizing the oft-cited PRISMA methodology. Through this analysis, a definition of SRM that reflects the current state of the art is proposed. Furthermore, the research in SRM applied in the context of different maintenance strategies is assessed (i.e. reactive, planned, proactive and strategic maintenance), and the most common drivers and challenges in SRM are presented. Finally, a roadmap for the implementation of SRM is proposed. The analysis of the SRM literature reveals that there are important research opportunities in the exploitation of SRM for strategic maintenance and asset management. The authors hope that this document leads to the consolidation of a new research area that aims to add value to maintenance in enterprises through the application of smart retrofitting in preexisting legacy devices.<\/jats:p>","DOI":"10.1007\/s10845-022-02002-2","type":"journal-article","created":{"date-parts":[[2022,8,29]],"date-time":"2022-08-29T09:03:03Z","timestamp":1661763783000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["Smart retrofitting in maintenance: a systematic literature review"],"prefix":"10.1007","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0889-7954","authenticated-orcid":false,"given":"David","family":"Sanchez-Londono","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7051-2875","authenticated-orcid":false,"given":"Giacomo","family":"Barbieri","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3827-0546","authenticated-orcid":false,"given":"Luca","family":"Fumagalli","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,8,29]]},"reference":[{"issue":"1","key":"2002_CR1","first-page":"3","volume":"16","author":"RL Ackoff","year":"1989","unstructured":"Ackoff, R. L. (1989). From data to wisdom. Journal of Applied Systems Analysis, 16(1), 3\u20139.","journal-title":"Journal of Applied Systems Analysis"},{"key":"2002_CR2","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1016\/j.promfg.2018.10.064","volume":"17","author":"M \u00c5kerman","year":"2018","unstructured":"\u00c5kerman, M., Lundgren, C., B\u00e4rring, M., et al. (2018). Challenges building a data value chain to enable data-driven decisions: A predictive maintenance case in 5g-enabled manufacturing. Procedia Manufacturing, 17, 411\u2013418.","journal-title":"Procedia Manufacturing"},{"key":"2002_CR3","doi-asserted-by":"crossref","unstructured":"Al\u00a0Kindhi, B., & Pratama, I. S. (2021) .Fuzzy logic and iot for smart city lighting maintenance management. In 2021 3rd East Indonesia Conference on Computer and Information Technology (EIConCIT) (pp.\u00a0369\u2013373). IEEE.","DOI":"10.1109\/EIConCIT50028.2021.9431917"},{"key":"2002_CR4","doi-asserted-by":"publisher","first-page":"1079","DOI":"10.1016\/j.procs.2014.05.536","volume":"32","author":"MB Alaya","year":"2014","unstructured":"Alaya, M. B., Banouar, Y., Monteil, T., et al. (2014). Om2m: Extensible etsi-compliant m2m service platform with self-configuration capability. Procedia Computer Science, 32, 1079\u20131086.","journal-title":"Procedia Computer Science"},{"key":"2002_CR5","doi-asserted-by":"crossref","unstructured":"Alexandru, A. M., Fiasch\u00e9, M., & Pinna, C., et al . (2016) . Building a smart maintenance architecture using smart devices: A web 2.0 based approach. In 2016 IEEE 2nd International Forum on Research and Technologies for Society and Industry Leveraging a Better Tomorrow (RTSI) (pp.\u00a01\u20136). IEEE.","DOI":"10.1109\/RTSI.2016.7740632"},{"issue":"7","key":"2002_CR6","doi-asserted-by":"publisher","first-page":"2226","DOI":"10.3390\/s18072226","volume":"18","author":"\u00c1 Alonso","year":"2018","unstructured":"Alonso, \u00c1., Pozo, A., Cantera, J. M., et al. (2018). Industrial data space architecture implementation using fiware. Sensors, 18(7), 2226.","journal-title":"Sensors"},{"key":"2002_CR7","doi-asserted-by":"crossref","unstructured":"Alves, F., Badikyan, H., & Moreira, H. A., et al . (2020) . Deployment of a smart and predictive maintenance system in an industrial case study. In 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE). IEEE (pp.\u00a0493\u2013498).","DOI":"10.1109\/ISIE45063.2020.9152441"},{"key":"2002_CR8","doi-asserted-by":"publisher","first-page":"17365","DOI":"10.1109\/ACCESS.2021.3051583","volume":"9","author":"P Aqueveque","year":"2021","unstructured":"Aqueveque, P., Radrigan, L., Pastene, F., et al. (2021). Data-driven condition monitoring of mining mobile machinery in non-stationary operations using wireless accelerometer sensor modules. IEEE Access, 9, 17365\u201317381.","journal-title":"IEEE Access"},{"key":"2002_CR9","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1016\/j.promfg.2020.02.044","volume":"42","author":"A Ardila","year":"2020","unstructured":"Ardila, A., Martinez, F., Garces, K., et al. (2020). Xrepo-towards an information system for prognostics and health management analysis. Procedia Manufacturing, 42, 146\u2013153.","journal-title":"Procedia Manufacturing"},{"key":"2002_CR10","doi-asserted-by":"crossref","unstructured":"Arosio, G., Giordani, I., & Arieni, L., et al . (2014) . Visual support and interaction for error prevention in aircraft maintenance. In 2014 IEEE Metrology for Aerospace (MetroAeroSpace) (pp.\u00a0372\u2013376). IEEE.","DOI":"10.1109\/MetroAeroSpace.2014.6865952"},{"key":"2002_CR11","doi-asserted-by":"crossref","unstructured":"Ashjaei, M., & Bengtsson, M .(2017) . Enhancing smart maintenance management using fog computing technology. In 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp.\u00a01561\u20131565). IEEE.","DOI":"10.1109\/IEEM.2017.8290155"},{"issue":"5","key":"2002_CR12","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1007\/s00170-011-3405-4","volume":"58","author":"S Atluru","year":"2012","unstructured":"Atluru, S., Huang, S. H., & Snyder, J. P. (2012). A smart machine supervisory system framework. The International Journal of Advanced Manufacturing Technology, 58(5), 563\u2013572.","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"key":"2002_CR13","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1016\/j.compind.2016.02.004","volume":"81","author":"RF Babiceanu","year":"2016","unstructured":"Babiceanu, R. F., & Seker, R. (2016). Big data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future outlook. Computers in Industry, 81, 128\u2013137.","journal-title":"Computers in Industry"},{"key":"2002_CR14","doi-asserted-by":"crossref","unstructured":"Balogh, Z., Gatial, E., & Barbosa, J., et al . (2018) . Reference architecture for a collaborative predictive platform for smart maintenance in manufacturing. In 2018 IEEE 22nd International Conference on Intelligent Engineering Systems (INES) (pp.\u00a0299\u2013304). IEEE","DOI":"10.1109\/INES.2018.8523969"},{"key":"2002_CR15","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.procs.2021.01.122","volume":"180","author":"G Barbieri","year":"2021","unstructured":"Barbieri, G., & Gutierrez, D. A. (2021). A gemma-grafcet methodology to enable digital twin based on real-time coupling. Procedia Computer Science, 180, 13\u201323.","journal-title":"Procedia Computer Science"},{"issue":"3","key":"2002_CR16","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.ifacol.2020.11.017","volume":"53","author":"G Barbieri","year":"2020","unstructured":"Barbieri, G., Sanchez-Londono, D., Cattaneo, L., et al. (2020). A case study for problem-based learning education in fault diagnosis assessment. IFAC-PapersOnLine, 53(3), 107\u2013112.","journal-title":"IFAC-PapersOnLine"},{"key":"2002_CR17","doi-asserted-by":"crossref","unstructured":"Barksdale, H., Smith, Q., & Khan, M . (2018) . Condition monitoring of electrical machines with internet of things. In SoutheastCon 2018 (pp.\u00a01\u20134). IEEE","DOI":"10.1109\/SECON.2018.8478989"},{"key":"2002_CR18","doi-asserted-by":"publisher","first-page":"1331","DOI":"10.1016\/j.procir.2019.04.022","volume":"81","author":"D Barton","year":"2019","unstructured":"Barton, D., G\u00f6nnheimer, P., Schade, F., et al. (2019). Modular smart controller for industry 4.0 functions in machine tools. Procedia CIRP, 81, 1331\u20131336.","journal-title":"Procedia CIRP"},{"key":"2002_CR19","doi-asserted-by":"publisher","DOI":"10.1002\/9781118926581","volume-title":"Introduction to maintenance engineering: Modelling, optimization and management","author":"M Ben-Daya","year":"2016","unstructured":"Ben-Daya, M., Kumar, U., & Murthy, D. P. (2016). Introduction to maintenance engineering: Modelling, optimization and management. Wiley."},{"issue":"1","key":"2002_CR20","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/JSEN.2018.2875160","volume":"19","author":"E Bernal","year":"2018","unstructured":"Bernal, E., Spiryagin, M., & Cole, C. (2018). Onboard condition monitoring sensors, systems and techniques for freight railway vehicles: A review. IEEE Sensors Journal, 19(1), 4\u201324.","journal-title":"IEEE Sensors Journal"},{"key":"2002_CR21","doi-asserted-by":"crossref","unstructured":"Bhandari, G., Joglekar, A., & Kulkarni, A., et al .(2020) . An implementation of an industrial internet of things on an smt assembly line. In 2020 International Conference on COMmunication Systems & NETworkS (COMSNETS) (pp.\u00a0688\u2013690). IEEE.","DOI":"10.1109\/COMSNETS48256.2020.9027475"},{"key":"2002_CR22","doi-asserted-by":"crossref","unstructured":"Bousdekis, A., Lepenioti, K., & Ntalaperas, D., et al . (2019) . A rami 4.0 view of predictive maintenance: software architecture, platform and case study in steel industry. In International Conference on Advanced Information Systems Engineering (pp.\u00a095\u2013106). Springer","DOI":"10.1007\/978-3-030-20948-3_9"},{"key":"2002_CR23","unstructured":"BSI (2008) Asset management. Standard BSI PAS 55-1:2008, British Standards Institution., London, England"},{"key":"2002_CR24","doi-asserted-by":"crossref","unstructured":"Bucci, G., Ciancetta, F., & Fiorucci, E., et al . (2020) . An iot condition monitoring system for resilience based on spectral analysis of vibration. In: 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT, IEEE, pp 38\u201343","DOI":"10.1109\/MetroInd4.0IoT48571.2020.9138177"},{"key":"2002_CR25","doi-asserted-by":"crossref","unstructured":"Calabrese, M., Cimmino, M., & Fiume, F., et al . (2020) . Sophia: An event-based iot and machine learning architecture for predictive maintenance in industry 4.0. Information 11(4):202","DOI":"10.3390\/info11040202"},{"issue":"1","key":"2002_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.compind.2008.09.007","volume":"60","author":"J Campos","year":"2009","unstructured":"Campos, J. (2009). Development in the application of ict in condition monitoring and maintenance. Computers in industry, 60(1), 1\u201320.","journal-title":"Computers in industry"},{"key":"2002_CR27","doi-asserted-by":"publisher","first-page":"106024","DOI":"10.1016\/j.cie.2019.106024","volume":"137","author":"TP Carvalho","year":"2019","unstructured":"Carvalho, T. P., Soares, F. A., Vita, R., et al. (2019). A systematic literature review of machine learning methods applied to predictive maintenance. Computers & Industrial Engineering, 137, 106024.","journal-title":"Computers & Industrial Engineering"},{"key":"2002_CR28","doi-asserted-by":"crossref","unstructured":"Catenazzo, D., O\u2019Flynn, B., & Walsh, M. (2018). On the use of wireless sensor networks in preventative maintenance for industry 4.0. In 2018 12th International Conference on Sensing Technology (ICST) (pp.\u00a0256\u2013262). IEEE.","DOI":"10.1109\/ICSensT.2018.8603669"},{"issue":"10","key":"2002_CR29","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.ifacol.2019.10.016","volume":"52","author":"L Cattaneo","year":"2019","unstructured":"Cattaneo, L., & Macchi, M. (2019). A digital twin proof of concept to support machine prognostics with low availability of run-to-failure data. IFAC-PapersOnLine, 52(10), 37\u201342.","journal-title":"IFAC-PapersOnLine"},{"key":"2002_CR30","doi-asserted-by":"crossref","unstructured":"Chau, H. K., Li, R. C., & Lee, T. S., et al. (2015). Implementation of computerized maintenance management system in upgraded pillar point sewage treatment works. In Engineering asset management-Systems, professional practices and certification (pp.\u00a0889\u2013900). Springer.","DOI":"10.1007\/978-3-319-09507-3_77"},{"key":"2002_CR31","doi-asserted-by":"publisher","first-page":"6505","DOI":"10.1109\/ACCESS.2017.2783682","volume":"6","author":"B Chen","year":"2017","unstructured":"Chen, B., Wan, J., Shu, L., et al. (2017). Smart factory of industry 4.0: Key technologies, application case, and challenges. Ieee Access, 6, 6505\u20136519.","journal-title":"Ieee Access"},{"issue":"9","key":"2002_CR32","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1109\/MCOM.2018.1701231","volume":"56","author":"B Chen","year":"2018","unstructured":"Chen, B., Wan, J., Celesti, A., et al. (2018). Edge computing in iot-based manufacturing. IEEE Communications Magazine, 56(9), 103\u2013109.","journal-title":"IEEE Communications Magazine"},{"key":"2002_CR33","doi-asserted-by":"crossref","unstructured":"Chen, H. F., Liao, Y. K., & Liou, B. L., et al. (2016). Smart iot system design for after-sales maintenances of 3-phase generators. In 2016 International Conference on Applied System Innovation (ICASI) (pp.\u00a01\u20133). IEEE.","DOI":"10.1109\/ICASI.2016.7539826"},{"issue":"3","key":"2002_CR34","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1016\/j.ifacol.2020.11.028","volume":"53","author":"IT Christou","year":"2020","unstructured":"Christou, I. T., Kefalakis, N., Zalonis, A., et al. (2020). End-to-end industrial iot platform for actionable predictive maintenance. IFAC-PapersOnLine, 53(3), 173\u2013178.","journal-title":"IFAC-PapersOnLine"},{"issue":"3","key":"2002_CR35","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1016\/j.ifacol.2020.11.047","volume":"53","author":"V Ciancio","year":"2020","unstructured":"Ciancio, V., Homri, L., Dantan, J. Y., et al. (2020). Towards prediction of machine failures: Overview and first attempt on specific automotive industry application. IFAC-PapersOnLine, 53(3), 289\u2013294.","journal-title":"IFAC-PapersOnLine"},{"key":"2002_CR36","doi-asserted-by":"publisher","first-page":"103130","DOI":"10.1016\/j.compind.2019.103130","volume":"113","author":"C Cimino","year":"2019","unstructured":"Cimino, C., Negri, E., & Fumagalli, L. (2019). Review of digital twin applications in manufacturing. Computers in Industry, 113, 103130.","journal-title":"Computers in Industry"},{"key":"2002_CR37","doi-asserted-by":"crossref","unstructured":"Cofre-Martel, S., Lopez\u00a0Droguett, E., & Modarres, M. (2021). Remaining useful life estimation through deep learning partial differential equation models: A framework for degradation dynamics interpretation using latent variables. Shock and Vibration.","DOI":"10.1155\/2021\/9937846"},{"issue":"3","key":"2002_CR38","doi-asserted-by":"publisher","first-page":"822","DOI":"10.1016\/j.ifacol.2015.06.185","volume":"48","author":"AL Cologni","year":"2015","unstructured":"Cologni, A. L., Fasanotti, L., Dovere, E., et al. (2015). Smartphone based video-telemetry logger for remote maintenance services. IFAC-PapersOnLine, 48(3), 822\u2013827.","journal-title":"IFAC-PapersOnLine"},{"key":"2002_CR39","doi-asserted-by":"crossref","unstructured":"Damanik, I., Rumbara, R., & Juhana, N. (2020). Online monitoring for processes and condition of a machine using smart management card. In IOP Conference Series: Materials Science and Engineering. IOP Publishing.","DOI":"10.1088\/1757-899X\/980\/1\/012047"},{"key":"2002_CR40","doi-asserted-by":"crossref","unstructured":"Deroussi, A., Abdessalam, A., & Addaim, A., et al. (2018). New scalable smart telemetry for industrial systems: Iot solutions. 2018 International Conference on Electronics (pp. 1\u20134). Optimization and Computer Science (ICECOCS), IEEE: Control.","DOI":"10.1109\/ICECOCS.2018.8610510"},{"issue":"9","key":"2002_CR41","first-page":"2410","volume":"12","author":"T Eiskop","year":"2017","unstructured":"Eiskop, T., Snatkin, A., & Karjust, K. (2017). Production monitoring system with predictive functionality. Journal of Engineering Science & Technology, 12(9), 2410\u20132425.","journal-title":"Journal of Engineering Science & Technology"},{"key":"2002_CR42","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.procs.2021.01.130","volume":"180","author":"CF Erazo Navas","year":"2021","unstructured":"Erazo Navas, C. F., Yepes, A. E., Abolghasem, S., et al. (2021). Mtconnect-based decision support system for local machine tool monitoring. Procedia Computer Science, 180, 69\u201378.","journal-title":"Procedia Computer Science"},{"key":"2002_CR43","doi-asserted-by":"publisher","first-page":"121065","DOI":"10.1016\/j.jclepro.2020.121065","volume":"260","author":"C Franciosi","year":"2020","unstructured":"Franciosi, C., Voisin, A., Miranda, S., et al. (2020). Measuring maintenance impacts on sustainability of manufacturing industries: From a systematic literature review to a framework proposal. Journal of Cleaner Production, 260, 121065.","journal-title":"Journal of Cleaner Production"},{"issue":"6","key":"2002_CR44","doi-asserted-by":"publisher","first-page":"778","DOI":"10.1080\/10494820.2013.815221","volume":"23","author":"N Gavish","year":"2015","unstructured":"Gavish, N., Guti\u00e9rrez, T., Webel, S., et al. (2015). Evaluating virtual reality and augmented reality training for industrial maintenance and assembly tasks. Interactive Learning Environments, 23(6), 778\u2013798.","journal-title":"Interactive Learning Environments"},{"issue":"4","key":"2002_CR45","first-page":"361","volume":"6","author":"R Gayathri","year":"2018","unstructured":"Gayathri, R., & Vasudevan, S. K. (2018). Internet of things based smart health monitoring of industrial standard motors. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 6(4), 361\u2013367.","journal-title":"Indonesian Journal of Electrical Engineering and Informatics (IJEEI)"},{"key":"2002_CR46","doi-asserted-by":"crossref","unstructured":"Ge, X., Zhu, J., & Xie, R., et al. (2019). Research on intelligent terminal unit for power distribution automation and maintenance. In 2019 4th International Conference on Intelligent Green Building and Smart Grid (IGBSG) (pp.\u00a0414\u2013417). IEEE.","DOI":"10.1109\/IGBSG.2019.8886203"},{"key":"2002_CR47","volume-title":"The GFMAM maintenance framework","author":"GFMAM","year":"2016","unstructured":"GFMAM. (2016). The GFMAM maintenance framework (1st ed.). The Global Forum on Maintenance and Asset Management.","edition":"1"},{"key":"2002_CR48","volume-title":"The GFMAM maintenance framework","author":"GFMAM","year":"2021","unstructured":"GFMAM. (2021). The GFMAM maintenance framework (2nd ed.). The Global Forum on Maintenance and Asset Management.","edition":"2"},{"key":"2002_CR49","doi-asserted-by":"crossref","unstructured":"Guerreiro, B. V., Lins, R. G., & Sun, J., et al. (2018). Definition of smart retrofitting: First steps for a company to deploy aspects of industry 4.0. In Advances in Manufacturing (pp.\u00a0161\u2013170). Springer.","DOI":"10.1007\/978-3-319-68619-6_16"},{"key":"2002_CR50","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.mfglet.2018.11.001","volume":"19","author":"DF Hesser","year":"2019","unstructured":"Hesser, D. F., & Markert, B. (2019). Tool wear monitoring of a retrofitted cnc milling machine using artificial neural networks. Manufacturing Letters, 19, 1\u20134.","journal-title":"Manufacturing Letters"},{"key":"2002_CR51","doi-asserted-by":"crossref","unstructured":"Hsu, C. N., Lin, Y. C., & Yang, C. C., et al. (2019). Low-cost vibration and acceleration sensors module for the drilling processes monitoring. In 2019 IEEE Sensors Applications Symposium (SAS) (pp.\u00a01\u20135). IEEE.","DOI":"10.1109\/SAS.2019.8705991"},{"key":"2002_CR52","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1016\/j.procir.2019.02.106","volume":"79","author":"S Huber","year":"2019","unstructured":"Huber, S., Wiemer, H., Schneider, D., et al. (2019). Dmme: Data mining methodology for engineering applications-a holistic extension to the crisp-dm model. Procedia Cirp, 79, 403\u2013408.","journal-title":"Procedia Cirp"},{"issue":"12","key":"2002_CR53","doi-asserted-by":"publisher","first-page":"9484","DOI":"10.1109\/JIOT.2020.2986342","volume":"8","author":"S Hussain","year":"2020","unstructured":"Hussain, S., Mahmud, U., & Yang, S. (2020). Car e-talk: An iot-enabled cloud-assisted smart fleet maintenance system. IEEE Internet of Things Journal, 8(12), 9484\u20139494.","journal-title":"IEEE Internet of Things Journal"},{"key":"2002_CR54","doi-asserted-by":"crossref","unstructured":"Iqbal, MIB., Mohsin, M., & Gula, F. (2019). Smart-genie: An iot-enabled predictive health monitoring system for power generators. In 2019 15th International Conference on Emerging Technologies (ICET) (pp.\u00a01\u20135). IEEE.","DOI":"10.1109\/ICET48972.2019.8994453"},{"key":"2002_CR55","unstructured":"ISO. (2014). Asset management\u2014Overview, principles and terminology. Standard ISO 55000:2014, International Organization for Standardization, Geneva, Switzerland."},{"issue":"7","key":"2002_CR56","doi-asserted-by":"publisher","first-page":"1483","DOI":"10.1016\/j.ymssp.2005.09.012","volume":"20","author":"AK Jardine","year":"2006","unstructured":"Jardine, A. K., Lin, D., & Banjevic, D. (2006). A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, 20(7), 1483\u20131510.","journal-title":"Mechanical Systems and Signal Processing"},{"key":"2002_CR57","doi-asserted-by":"publisher","first-page":"127555","DOI":"10.1016\/j.jclepro.2021.127555","volume":"312","author":"D Jaspert","year":"2021","unstructured":"Jaspert, D., Ebel, M., Eckhardt, A., et al. (2021). Smart retrofitting in manufacturing: A systematic review. Journal of Cleaner Production, 312, 127555.","journal-title":"Journal of Cleaner Production"},{"key":"2002_CR58","doi-asserted-by":"crossref","unstructured":"J\u00f3nasd\u00f3ttir, H., Dhanani, K., & McRae, K., et al. (2018). Upgrading legacy equipment to industry 4.0 through a cyber-physical interface. In IFIP International Conference on Advances in Production Management Systems (pp.\u00a03\u201310). Springer.","DOI":"10.1007\/978-3-319-99707-0_1"},{"key":"2002_CR59","doi-asserted-by":"crossref","unstructured":"Jung, J., & Jin, K. (2018). Case studies for the establishment of the optimized smart factory with small and medium-sized enterprises. In Proceedings of the 2nd International Symposium on Computer Science and Intelligent Control (pp.\u00a01\u20135).","DOI":"10.1145\/3284557.3284692"},{"key":"2002_CR60","doi-asserted-by":"crossref","unstructured":"Kaisler, S., Armour, F., & Espinosa, JA., et al. (2013). Big data: Issues and challenges moving forward. In 2013 46th Hawaii International Conference on System Sciences (pp.\u00a0995\u20131004). IEEE.","DOI":"10.1109\/HICSS.2013.645"},{"key":"2002_CR61","doi-asserted-by":"crossref","unstructured":"Khademi, A., Raji, F., & Sadeghi, M. (2019). Iot enabled vibration monitoring toward smart maintenance. In 2019 3rd International Conference on Internet of Things and Applications (IoT) (pp.\u00a01\u20136). IEEE.","DOI":"10.1109\/IICITA.2019.8808837"},{"issue":"1","key":"2002_CR62","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1109\/LCOMM.2018.2875978","volume":"23","author":"H Khelifi","year":"2018","unstructured":"Khelifi, H., Luo, S., Nour, B., et al. (2018). Bringing deep learning at the edge of information-centric internet of things. IEEE Communications Letters, 23(1), 52\u201355.","journal-title":"IEEE Communications Letters"},{"issue":"9","key":"2002_CR63","doi-asserted-by":"publisher","first-page":"3251","DOI":"10.1007\/s00170-018-2093-8","volume":"97","author":"KS Kiangala","year":"2018","unstructured":"Kiangala, K. S., & Wang, Z. (2018). Initiating predictive maintenance for a conveyor motor in a bottling plant using industry 4.0 concepts. The International Journal of Advanced Manufacturing Technology, 97(9), 3251\u20133271.","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"issue":"1","key":"2002_CR64","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1016\/j.infsof.2008.09.009","volume":"51","author":"B Kitchenham","year":"2009","unstructured":"Kitchenham, B., Brereton, O. P., Budgen, D., et al. (2009). Systematic literature reviews in software engineering\u2014A systematic literature review. Information and Software Technology, 51(1), 7\u201315.","journal-title":"Information and Software Technology"},{"issue":"1","key":"2002_CR65","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1109\/MIC.2017.18","volume":"21","author":"P Lalanda","year":"2017","unstructured":"Lalanda, P., Morand, D., & Chollet, S. (2017). Autonomic mediation middleware for smart manufacturing. IEEE Internet Computing, 21(1), 32\u201339.","journal-title":"IEEE Internet Computing"},{"issue":"4","key":"2002_CR66","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1007\/s40436-017-0197-2","volume":"5","author":"C Lee","year":"2017","unstructured":"Lee, C., Zhang, S., & Ng, K. (2017). Development of an industrial internet of things suite for smart factory towards re-industrialization. Advances in Manufacturing, 5(4), 335\u2013343.","journal-title":"Advances in Manufacturing"},{"issue":"7","key":"2002_CR67","doi-asserted-by":"publisher","first-page":"150","DOI":"10.3182\/20130522-3-BR-4036.00107","volume":"46","author":"J Lee","year":"2013","unstructured":"Lee, J., Lapira, E., Yang, S., et al. (2013). Predictive manufacturing system - trends of next-generation production systems. Ifac Proceedings Volumes, 46(7), 150\u2013156.","journal-title":"Ifac Proceedings Volumes"},{"key":"2002_CR68","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.mfglet.2014.12.001","volume":"3","author":"J Lee","year":"2015","unstructured":"Lee, J., Bagheri, B., & Kao, H. A. (2015). A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manufacturing Letters, 3, 18\u201323.","journal-title":"Manufacturing Letters"},{"issue":"11","key":"2002_CR69","doi-asserted-by":"publisher","first-page":"110805","DOI":"10.1115\/1.4047856","volume":"142","author":"J Lee","year":"2020","unstructured":"Lee, J., Ni, J., Singh, J., et al. (2020). Intelligent maintenance systems and predictive manufacturing. Journal of Manufacturing Science and Engineering, 142(11), 110805.","journal-title":"Journal of Manufacturing Science and Engineering"},{"issue":"2","key":"2002_CR70","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1007\/s10845-020-01578-x","volume":"32","author":"WJ Lee","year":"2021","unstructured":"Lee, W. J., Xia, K., Denton, N. L., et al. (2021). Development of a speed invariant deep learning model with application to condition monitoring of rotating machinery. Journal of Intelligent Manufacturing, 32(2), 393\u2013406.","journal-title":"Journal of Intelligent Manufacturing"},{"key":"2002_CR71","doi-asserted-by":"publisher","first-page":"799","DOI":"10.1016\/j.ymssp.2017.11.016","volume":"104","author":"Y Lei","year":"2018","unstructured":"Lei, Y., Li, N., Guo, L., et al. (2018). Machinery health prognostics: A systematic review from data acquisition to rul prediction. Mechanical Systems and Signal Processing, 104, 799\u2013834.","journal-title":"Mechanical Systems and Signal Processing"},{"key":"2002_CR72","doi-asserted-by":"crossref","unstructured":"Lesjak, C., Ruprechter, T., & Bock, H., et al. (2014). Estado-enabling smart services for industrial equipment through a secured, transparent and ad-hoc data transmission online. In The 9th International Conference for Internet Technology and Secured Transactions (ICITST-2014) (pp.\u00a0171\u2013177). IEEE.","DOI":"10.1109\/ICITST.2014.7038800"},{"key":"2002_CR73","doi-asserted-by":"publisher","first-page":"106598","DOI":"10.1016\/j.ress.2019.106598","volume":"193","author":"R Li","year":"2020","unstructured":"Li, R., Verhagen, W. J., & Curran, R. (2020). A systematic methodology for prognostic and health management system architecture definition. Reliability Engineering & System Safety, 193, 106598.","journal-title":"Reliability Engineering & System Safety"},{"key":"2002_CR74","doi-asserted-by":"crossref","unstructured":"Liang, F., Liang, X., & Yang, S., et al. (2020). Research on service-oriented substation wide-area operation and maintenance system and its application. In 2020 IEEE Sustainable Power and Energy Conference (iSPEC) (pp.\u00a01742\u20131747). IEEE.","DOI":"10.1109\/iSPEC50848.2020.9350963"},{"issue":"10","key":"2002_CR75","doi-asserted-by":"publisher","first-page":"e1","DOI":"10.1016\/j.jclinepi.2009.06.006","volume":"62","author":"A Liberati","year":"2009","unstructured":"Liberati, A., Altman, D. G., Tetzlaff, J., et al. (2009). The prisma statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Journal of Clinical Epidemiology, 62(10), e1\u2013e34.","journal-title":"Journal of Clinical Epidemiology"},{"key":"2002_CR76","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1016\/j.autcon.2013.10.004","volume":"37","author":"YC Lin","year":"2014","unstructured":"Lin, Y. C., Cheung, W., & Siao, F. C. (2014). Developing mobile 2d barcode\/rfid-based maintenance management system. Automation in Construction, 37, 110\u2013121.","journal-title":"Automation in Construction"},{"key":"2002_CR77","doi-asserted-by":"publisher","first-page":"106193","DOI":"10.1016\/j.cie.2019.106193","volume":"139","author":"T Lins","year":"2020","unstructured":"Lins, T., & Oliveira, R. A. R. (2020). Cyber-physical production systems retrofitting in context of industry 4.0. Computers & Industrial Engineering, 139, 106193.","journal-title":"Computers & Industrial Engineering"},{"key":"2002_CR78","doi-asserted-by":"crossref","unstructured":"Liu, Y. Y., Hung, M. H., & Lin, Y. C., et al. (2018). A cloud-based pluggable manufacturing service scheme for smart factory. In 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) (pp.\u00a01040\u20131045). IEEE.","DOI":"10.1109\/COASE.2018.8560401"},{"key":"2002_CR79","doi-asserted-by":"crossref","unstructured":"Liyanage, J. P., & Badurdeen, F .(2010) . Strategies for integrating maintenance for sustainable manufacturing. In Engineering Asset Lifecycle Management (pp.\u00a0308\u2013315). Springer.","DOI":"10.1007\/978-0-85729-320-6_36"},{"key":"2002_CR80","doi-asserted-by":"crossref","unstructured":"Lubik, S., Lim, S., & Platts, K., et al .(2013) . Market-pull and technology-push in manufacturing start-ups in emerging industries. Journal of Manufacturing Technology Management.","DOI":"10.1108\/17410381311287463"},{"key":"2002_CR81","doi-asserted-by":"crossref","unstructured":"Luo, X. (2020). Research on communication technology of ship integrated monitoring system based on opc. In 2020 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS) (pp.\u00a0528\u2013531). IEEE.","DOI":"10.1109\/ICITBS49701.2020.00115"},{"key":"2002_CR82","doi-asserted-by":"crossref","unstructured":"Macchi, M., Roda, I., & Fumagalli, L. (2017). On the advancement of maintenance management towards smart maintenance in manufacturing. In IFIP International Conference on Advances in Production Management Systems (pp.\u00a0383\u2013390). Springer.","DOI":"10.1007\/978-3-319-66923-6_45"},{"key":"2002_CR83","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1016\/j.promfg.2020.02.057","volume":"42","author":"L Magad\u00e1n","year":"2020","unstructured":"Magad\u00e1n, L., Su\u00e1rez, F., Granda, J., et al. (2020). Low-cost real-time monitoring of electric motors for the industry 4.0. Procedia Manufacturing, 42, 393\u2013398.","journal-title":"Procedia Manufacturing"},{"key":"2002_CR84","unstructured":"M\u00e1rquez, A. C. (2007). The maintenance management framework: Models and methods for complex systems maintenance. Springer Science & Business Media."},{"issue":"3","key":"2002_CR85","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1016\/j.ifacol.2020.11.065","volume":"53","author":"MJ McNally","year":"2020","unstructured":"McNally, M. J., Chaplin, J. C., Martinez-Arellano, G., et al. (2020). Towards flexible, fault tolerant hardware service wrappers for the digital manufacturing on a shoestring project. IFAC-PapersOnLine, 53(3), 72\u201377.","journal-title":"IFAC-PapersOnLine"},{"key":"2002_CR86","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1016\/j.jmsy.2018.10.005","volume":"49","author":"S Mittal","year":"2018","unstructured":"Mittal, S., Khan, M. A., Romero, D., et al. (2018). A critical review of smart manufacturing & industry 4.0 maturity models: Implications for small and medium-sized enterprises (smes). Journal of Manufacturing Systems, 49, 194\u2013214.","journal-title":"Journal of Manufacturing Systems"},{"issue":"15","key":"2002_CR87","doi-asserted-by":"publisher","first-page":"4308","DOI":"10.3390\/s20154308","volume":"20","author":"P Moens","year":"2020","unstructured":"Moens, P., Bracke, V., Soete, C., et al. (2020). Scalable fleet monitoring and visualization for smart machine maintenance and industrial iot applications. Sensors, 20(15), 4308.","journal-title":"Sensors"},{"issue":"2","key":"2002_CR88","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1016\/j.cirp.2016.06.005","volume":"65","author":"L Monostori","year":"2016","unstructured":"Monostori, L., K\u00e1d\u00e1r, B., Bauernhansl, T., et al. (2016). Cyber-physical systems in manufacturing. Cirp Annals, 65(2), 621\u2013641.","journal-title":"Cirp Annals"},{"key":"2002_CR89","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1016\/j.jmsy.2018.05.008","volume":"47","author":"D Mourtzis","year":"2018","unstructured":"Mourtzis, D., & Vlachou, E. (2018). A cloud-based cyber-physical system for adaptive shop-floor scheduling and condition-based maintenance. Journal of Manufacturing Systems, 47, 179\u2013198.","journal-title":"Journal of Manufacturing Systems"},{"issue":"1","key":"2002_CR90","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1016\/j.ijpe.2010.04.039","volume":"131","author":"P Muchiri","year":"2011","unstructured":"Muchiri, P., Pintelon, L., Gelders, L., et al. (2011). Development of maintenance function performance measurement framework and indicators. International Journal of Production Economics, 131(1), 295\u2013302.","journal-title":"International Journal of Production Economics"},{"key":"2002_CR91","doi-asserted-by":"publisher","first-page":"450","DOI":"10.1016\/j.promfg.2020.02.050","volume":"42","author":"K Mykoniatis","year":"2020","unstructured":"Mykoniatis, K. (2020). A real-time condition monitoring and maintenance management system for low voltage industrial motors using internet-of-things. Procedia Manufacturing, 42, 450\u2013456.","journal-title":"Procedia Manufacturing"},{"issue":"1","key":"2002_CR92","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1002\/sys.21565","volume":"24","author":"H Nordal","year":"2021","unstructured":"Nordal, H., & El-Thalji, I. (2021). Modeling a predictive maintenance management architecture to meet industry 4.0 requirements: A case study. Systems Engineering, 24(1), 34\u201350.","journal-title":"Systems Engineering"},{"key":"2002_CR93","doi-asserted-by":"crossref","unstructured":"Nowlan, F. S., & Heap, H. F. (1978). Reliability-centered maintenance. United Air Lines Inc San Francisco Ca: Tech. rep.","DOI":"10.21236\/ADA066579"},{"key":"2002_CR94","first-page":"385","volume":"33","author":"A Oliveira","year":"2013","unstructured":"Oliveira, A., Araujo, R., & Jardine, A. (2013). A human centered view on e-maintenance. Chemical Engineering Transactions, 33, 385\u2013390.","journal-title":"Chemical Engineering Transactions"},{"issue":"1","key":"2002_CR95","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1007\/s10845-018-1433-8","volume":"31","author":"E Oztemel","year":"2020","unstructured":"Oztemel, E., & Gursev, S. (2020). Literature review of industry 4.0 and related technologies. Journal of Intelligent Manufacturing, 31(1), 127\u2013182.","journal-title":"Journal of Intelligent Manufacturing"},{"key":"2002_CR96","unstructured":"Parra, C., & Crespo, A. (2015). Ingenier\u00eda de mantenimiento y fiabilidad aplicada en la gesti\u00f3n de activos. desarrollo y aplicaci\u00f3n pr\u00e1ctica de un modelo de gesti\u00f3n del mantenimiento (mgm). Editado por INGEMAN, Escuela Superior de Ingenieros Industriales de la Universidad de Sevilla, Espa\u00f1a"},{"key":"2002_CR97","doi-asserted-by":"crossref","unstructured":"Parra, C., Gonz\u00e1lez-Prida, V., & Cand\u00f3n, E., et al .(2019) . Integration of asset management standard iso55000 with a maintenance management model. In World Congress on Engineering Asset Management (pp.\u00a0189\u2013200). Springer.","DOI":"10.1007\/978-3-030-64228-0_17"},{"issue":"1\u20134","key":"2002_CR98","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1007\/s00170-009-2482-0","volume":"50","author":"Y Peng","year":"2010","unstructured":"Peng, Y., Dong, M., & Zuo, M. J. (2010). Current status of machine prognostics in condition-based maintenance: A review. The International Journal of Advanced Manufacturing Technology, 50(1\u20134), 297\u2013313.","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"key":"2002_CR99","doi-asserted-by":"crossref","unstructured":"Pignatelli, E., Scaffa, L., & Pignatelli, G., et al. (2015). An approach to the development of an advanced solution for smart monitoring applications. In 2015 IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC). IEEE (pp.\u00a0638\u2013643)","DOI":"10.1109\/EEEIC.2015.7165239"},{"issue":"31","key":"2002_CR100","doi-asserted-by":"publisher","first-page":"133","DOI":"10.3182\/20121122-2-ES-4026.00021","volume":"45","author":"P Pistofidis","year":"2012","unstructured":"Pistofidis, P., & Emmanouilidis, C. (2012). Developing advanced context aware tools for mobile maintenance. IFAC Proceedings Volumes, 45(31), 133\u2013138.","journal-title":"IFAC Proceedings Volumes"},{"issue":"2","key":"2002_CR101","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1080\/0951192X.2020.1718762","volume":"33","author":"BA Prathima","year":"2020","unstructured":"Prathima, B. A., Sudha, P. N., & Suresh, P. M. (2020). Shop floor to cloud connect for live monitoring the production data of cnc machines. International Journal of Computer Integrated Manufacturing, 33(2), 142\u2013158.","journal-title":"International Journal of Computer Integrated Manufacturing"},{"key":"2002_CR102","doi-asserted-by":"crossref","unstructured":"Priller, P., Aldrian, A., & Ebner, T. (2014). Case study: From legacy to connectivity migrating industrial devices into the world of smart services. In Proceedings of the 2014 IEEE emerging technology and factory automation (ETFA) (pp.\u00a01\u20138). IEEE.","DOI":"10.1109\/ETFA.2014.7005136"},{"issue":"3","key":"2002_CR103","doi-asserted-by":"publisher","first-page":"e2731","DOI":"10.1002\/jnm.2731","volume":"34","author":"EB Priyanka","year":"2021","unstructured":"Priyanka, E. B., Maheswari, C., & Thangavel, S. (2021). A smart-integrated iot module for intelligent transportation in oil industry. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 34(3), e2731.","journal-title":"International Journal of Numerical Modelling: Electronic Networks, Devices and Fields"},{"key":"2002_CR104","doi-asserted-by":"crossref","unstructured":"Prudenzi, A., Fioravanti, A., & Ciancetta, F. (2019a). Smart distributed energy monitoring for industrial applications. In 2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4. 0 &IoT) (pp.\u00a0274\u2013278). IEEE.","DOI":"10.1109\/METROI4.2019.8792861"},{"key":"2002_CR105","doi-asserted-by":"crossref","unstructured":"Prudenzi, A., Fioravanti, A., & Pierannunzi, F., et al. (2019b). Distributed power quality monitoring in customer\u2019s electrical distribution system. In 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC\/I &CPS Europe) (pp.\u00a01\u20135). IEEE.","DOI":"10.1109\/EEEIC.2019.8783784"},{"key":"2002_CR106","doi-asserted-by":"crossref","unstructured":"Ramani, B. V., Amith, C., & Oommen, J. M., et al. (2016). Predictive analysis for industrial maintenance automation and optimization using a smart sensor network. In 2016 International Conference on Next Generation Intelligent Systems (ICNGIS) (pp.\u00a01\u20135). IEEE.","DOI":"10.1109\/ICNGIS.2016.7854004"},{"key":"2002_CR107","doi-asserted-by":"crossref","unstructured":"Ranjbar, E., Sedehi, R. G., & Rashidi, M., et al . (2019) . Design of an iot-based system for smart maintenance of medical equipment. In 2019 3rd International Conference on Internet of Things and Applications (IoT) (pp.\u00a01\u201312). IEEE.","DOI":"10.1109\/IICITA.2019.8808841"},{"key":"2002_CR108","unstructured":"Richter, C., Fessel, K., & Kattefeld, A. (2019). Intelligent iot maintenance using lorawan. Smart SysTech 2019; European Conference on Smart Objects (pp. 1\u20135). VDE: Systems and Technologies."},{"key":"2002_CR109","doi-asserted-by":"publisher","first-page":"103531","DOI":"10.1016\/j.compind.2021.103531","volume":"133","author":"I Roda","year":"2021","unstructured":"Roda, I., & Macchi, M. (2021). Maintenance concepts evolution: A comparative review towards advanced maintenance conceptualization. Computers in Industry, 133, 103531.","journal-title":"Computers in Industry"},{"key":"2002_CR110","doi-asserted-by":"crossref","unstructured":"Romero, N., Medrano, R., & Garces, K., et al. (2021). Xrepo 2.0: A big data information system for education in prognostics and health management. International Journal of Prognostics and Health Management 12(1)","DOI":"10.36001\/ijphm.2021.v12i1.1412"},{"key":"2002_CR111","first-page":"238","volume":"4","author":"EM Rubio","year":"2018","unstructured":"Rubio, E. M., Dion\u00edsio, R. P., & Torres, P. M. B. (2018). Predictive maintenance of induction motors in the context of industry 4.0. International Journal, 4, 238.","journal-title":"International Journal"},{"key":"2002_CR112","unstructured":"Sadiki, S., Ramadany, M., & Faccio, M., et al. (2018). Implementation of a remote monitoring system for condition-based maintenance using wireless sensor network: Case study. Journal of Theoretical & Applied Information Technology 96(15)"},{"key":"2002_CR113","volume-title":"The coding manual for qualitative researchers","author":"J Salda\u00f1a","year":"2016","unstructured":"Salda\u00f1a, J. (2016). The coding manual for qualitative researchers. SAGE."},{"key":"2002_CR114","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1016\/j.procir.2019.03.052","volume":"81","author":"M Schneider","year":"2019","unstructured":"Schneider, M., Lucke, D., & Adolf, T. (2019). A cyber-physical failure management system for smart factories. Procedia CIRP, 81, 300\u2013305.","journal-title":"Procedia CIRP"},{"key":"2002_CR115","doi-asserted-by":"crossref","unstructured":"Scholtz, B., Kapeso, M., & Van\u00a0Belle, J. P (2018). An internet of things (iot) model for optimising downtime management: a smart lighting case study. In IFIP International Internet of Things Conference (pp.89\u2013104). Springer.","DOI":"10.1007\/978-3-030-15651-0_9"},{"key":"2002_CR116","doi-asserted-by":"crossref","unstructured":"Sepehri, A., Chu, Z., & Ren, G., et al. (2018). Condition monitoring of industrial machines using cloud communication. In 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) (pp.\u00a01318\u20131323). IEEE.","DOI":"10.1109\/IEMCON.2018.8614909"},{"key":"2002_CR117","doi-asserted-by":"crossref","unstructured":"Sezer, E., Romero, D., & Guedea, F., et al. (2018). An industry 4.0-enabled low cost predictive maintenance approach for smes. In 2018 IEEE International Conference on Engineering, Technology and Innovation (ICE\/ITMC) (pp.\u00a01\u20138). IEEE.","DOI":"10.1109\/ICE.2018.8436307"},{"key":"2002_CR118","doi-asserted-by":"crossref","unstructured":"Shapsough, S., Takrouri, M., & Dhaouadi, R., et al. (2020). An iot-based remote iv tracing system for analysis of city-wide solar power facilities. Sustainable Cities and Society, 57.","DOI":"10.1016\/j.scs.2020.102041"},{"issue":"17","key":"2002_CR119","doi-asserted-by":"publisher","first-page":"3781","DOI":"10.3390\/s19173781","volume":"19","author":"M Short","year":"2019","unstructured":"Short, M., & Twiddle, J. (2019). An industrial digitalization platform for condition monitoring and predictive maintenance of pumping equipment. Sensors, 19(17), 3781.","journal-title":"Sensors"},{"issue":"21","key":"2002_CR120","doi-asserted-by":"publisher","first-page":"5356","DOI":"10.1016\/j.jsv.2014.05.011","volume":"333","author":"S Singh","year":"2014","unstructured":"Singh, S., K\u00f6pke, U. G., Howard, C. Q., et al. (2014). Analyses of contact forces and vibration response for a defective rolling element bearing using an explicit dynamics finite element model. Journal of Sound and Vibration, 333(21), 5356\u20135377.","journal-title":"Journal of Sound and Vibration"},{"key":"2002_CR121","doi-asserted-by":"crossref","unstructured":"Strau\u00df, P., Schmitz, M., & W\u00f6stmann, R., et al. (2018). Enabling of predictive maintenance in the brownfield through low-cost sensors, an iiot-architecture and machine learning. In 2018 IEEE International Conference on Big Data (Big Data) (pp.\u00a01474\u20131483). IEEE.","DOI":"10.1109\/BigData.2018.8622076"},{"issue":"3","key":"2002_CR122","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1016\/j.ifacol.2020.11.050","volume":"53","author":"M Surico","year":"2020","unstructured":"Surico, M., Ricatto, R., Merlo, A., et al. (2020). Programs project approach to maintenance management. IFAC-PapersOnLine, 53(3), 313\u2013318.","journal-title":"IFAC-PapersOnLine"},{"key":"2002_CR123","doi-asserted-by":"crossref","unstructured":"Talmoudi, S., Kanada, T., & Hirata, Y. (2019). An iot-based failure prediction solution using machine sound data. In 2019 IEEE\/SICE International Symposium on System Integration (SII) (pp.\u00a0227\u2013232). IEEE.","DOI":"10.1109\/SII.2019.8700357"},{"key":"2002_CR124","doi-asserted-by":"crossref","unstructured":"Tedeschi, S., Emmanouilidis, C., & Farnsworth, M., et al. (2017). New threats for old manufacturing problems: Secure iot-enabled monitoring of legacy production machinery. In IFIP International Conference on Advances in Production Management Systems (pp.\u00a0391\u2013398). Springer.","DOI":"10.1007\/978-3-319-66923-6_46"},{"key":"2002_CR125","first-page":"45","volume":"17","author":"E Uhlmann","year":"2017","unstructured":"Uhlmann, E., Laghmouchi, A., Geisert, C., et al. (2017). Smart wireless sensor network and configuration of algorithms for condition monitoring applications. Journal of Machine Engineering, 17, 45\u201355.","journal-title":"Journal of Machine Engineering"},{"key":"2002_CR126","doi-asserted-by":"crossref","unstructured":"Vieira, G. G., Varela, M. L., & Putnik, G. D., et al. (2018). Intelligent platform for supervision and production activity control in real time. In Advances in Manufacturing (pp.\u00a0151\u2013159). Springer.","DOI":"10.1007\/978-3-319-68619-6_15"},{"key":"2002_CR127","doi-asserted-by":"crossref","unstructured":"Villar-Fidalgo, L., Crespo\u00a0M\u00e1rquez, A., & Gonz\u00e1lez-Prida, V., et al. (2018). Cyber physical systems implementation for asset management improvement: A framework for the transition. Safety and Reliability\u2013Safe Societies in a Changing World: Proceedings of ESREL 2018, June 17\u201321, 2018, Trondheim, Norway","DOI":"10.1201\/9781351174664-383"},{"key":"2002_CR128","unstructured":"Vogl, G. W., Weiss, B. A., & Donmez, M. A . (2015) . A sensor-based method for diagnostics of machine tool linear axes. In: Proceedings of the Annual Conference of the Prognostics and Health Management Society. In Prognostics and Health Management Society. Conference, NIH Public Access"},{"issue":"2","key":"2002_CR129","doi-asserted-by":"publisher","first-page":"869","DOI":"10.1109\/COMST.2020.2970550","volume":"22","author":"X Wang","year":"2020","unstructured":"Wang, X., Han, Y., Leung, V. C., et al. (2020). Convergence of edge computing and deep learning: A comprehensive survey. IEEE Communications Surveys & Tutorials, 22(2), 869\u2013904.","journal-title":"IEEE Communications Surveys & Tutorials"},{"key":"2002_CR130","volume-title":"System Analysis, Design, and Development","author":"CS Wasson","year":"2006","unstructured":"Wasson, C. S. (2006). System Analysis, Design, and Development. John Wiley & Sons Inc."},{"key":"2002_CR131","unstructured":"Weiss, B. A., Vogl, G., & Helu, M., et al. (2015) . Measurement science for prognostics and health management for smart manufacturing systems: key findings from a roadmapping workshop. In Proceedings of the Annual Conference of the Prognostics and Health Management Society. Prognostics and Health Management Society. Conference, NIH public Access."},{"issue":"12","key":"2002_CR132","doi-asserted-by":"publisher","first-page":"2407","DOI":"10.3390\/app9122407","volume":"9","author":"H Wiemer","year":"2019","unstructured":"Wiemer, H., Drowatzky, L., & Ihlenfeldt, S. (2019). Data mining methodology for engineering applications (dmme)\u2014A holistic extension to the crisp-dm model. Applied Sciences, 9(12), 2407.","journal-title":"Applied Sciences"},{"key":"2002_CR133","unstructured":"Wirth, R., & Hipp, J. (2000). Crisp-dm: Towards a standard process model for data mining. In Proceedings of the 4th International Conference on the Practical Applications of Knowledge Discovery and Data Mining. Springer."},{"key":"2002_CR134","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1016\/j.measurement.2019.02.079","volume":"139","author":"LT Yiu","year":"2019","unstructured":"Yiu, L. T., Cholette, M. E., & Peter, W. T. (2019). A multi-sensor approach to remaining useful life estimation for a slurry pump. Measurement, 139, 140\u2013151.","journal-title":"Measurement"},{"key":"2002_CR135","doi-asserted-by":"crossref","unstructured":"Yu, N., Chen, H., & Song, X., et al . (2014) . Research on iec 61968 based message design for intelligent operation and maintenance center. In: 2014 China International Conference on Electricity Distribution (CICED), IEEE, pp 1331\u20131337","DOI":"10.1109\/CICED.2014.6991923"},{"key":"2002_CR136","doi-asserted-by":"publisher","first-page":"626","DOI":"10.1016\/j.jclepro.2016.07.123","volume":"142","author":"Y Zhang","year":"2017","unstructured":"Zhang, Y., Ren, S., Liu, Y., et al. (2017). A big data analytics architecture for cleaner manufacturing and maintenance processes of complex products. Journal of cleaner production, 142, 626\u2013641.","journal-title":"Journal of cleaner production"},{"issue":"3","key":"2002_CR137","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.ifacol.2020.11.010","volume":"53","author":"AJ Ziegelaar","year":"2020","unstructured":"Ziegelaar, A. J., Travaglione, B. C., & Hodkiewicz, M. R. (2020). Sensing system for low cost condition monitoring of remote assets. IFAC-PapersOnLine, 53(3), 60\u201365.","journal-title":"IFAC-PapersOnLine"}],"container-title":["Journal of Intelligent Manufacturing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-022-02002-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10845-022-02002-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-022-02002-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,4]],"date-time":"2023-01-04T21:05:58Z","timestamp":1672866358000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10845-022-02002-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,29]]},"references-count":137,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1]]}},"alternative-id":["2002"],"URL":"https:\/\/doi.org\/10.1007\/s10845-022-02002-2","relation":{},"ISSN":["0956-5515","1572-8145"],"issn-type":[{"value":"0956-5515","type":"print"},{"value":"1572-8145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,29]]},"assertion":[{"value":"21 January 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 July 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 August 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}