Abstract
The study of the digital transformation of maintenance management in the context of industry and infrastructure is highly topical and interesting. In fact, maintenance is expected to be one of the business areas where this transformation is expected to be most significant. It is important to analyze why, and how, maintenance can benefit from this transformation: What are the new technologies and tools with the greatest potential impact on maintenance? How can this transformation process be accomplished? What is the impact of emerging asset management platforms and new intelligent maintenance Apps? Etc. Clearly, digital transformation is both an organizational challenge and a major technical challenge, needing a strategic planning process to guide it. To increase asset performance using 4.0 technologies, it is also necessary to face new technical problems and challenges: the non-ergodicity of data processes in many assets, the selection of the dimension of the number of data needed to explain their performance, the way to consider and interpret risks, the way to use such risk assessment for dynamic maintenance scheduling, etc. This document addresses each of these topics, providing the reader with keys to further explore each of them.
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References
Abualkibash, M., Elleithy, K. Cloud Computing. The Future of IT industry. Int.J.Distrib. Parallel Syst. 2012. Volume 3, No. 4, 1–12
Borgia, E.: The Internet of Things vision: Key features, applications and open issues. Comput. Commun. 54, 1–31 (2014)
Boschert, S., & Rosen, R. Digital twin-the simulation aspect. In Mechatronic Futures: Challenges and Solutions for Mechatronic Systems and Their Designers. 2016. https://doi.org/10.1007/978-3-319-32156-1_6
Chemweno, P., Pintelon, L., De Meyer, A.M., Muchiri, P.N., Van Horenbeek, A., Wakiru, J.: A Dynamic Risk Assessment Methodology for Maintenance Decision Support. Qual Reliab Eng Int 33, 551–564 (2017). https://doi.org/10.1002/qre.2040
https://www.clicdata.com/blog/what-are-bi-data-visualization-data-analytics/
Crespo, M.A.: Digital Maintenance Management. Guiding Digital Transformation in Maintenance. Springer, Cham (2022). ISBN 978-3-030-97659-0. https://doi.org/10.1007/978-3-030-97660-6
Crespo, M.A., Rosique, A.S., Moreu de León, P., Gómez Fernández, J.F., Diego, A.G., Fernández, E.C.: Exploiting EAMS, GIS and dispatching systems data for criticality analysis. In: Value Based and Intelligent Asset Management (2020). https://doi.org/10.1007/978-3-030-20704-5_7
Crespo, A., et al.: Criticality analysis for improving maintenance, felling and pruning cycles in power lines. IFAC-PapersOnLine (2018). https://doi.org/10.1016/j.ifacol.2018.08.262
Crespo, M.A., de la Fuente Carmona, A., Marcos, J.A., Navarro, J.: Designing CBM plans, based on predictive analytics and big data tools, for train wheel bearings. Comput. Ind. 122, 103292 (2020). ISSN 0166-3615, https://doi.org/10.1016/j.compind.2020.103292
Gartner’s Market guide for Asset Performance Management Software, dated 26th June 2019 (ID G00388410)
Hamdaqa, M., Tahvildari, L.: Cloud computing uncovered: a research landscape. Adv. Comput. (2012). https://doi.org/10.1016/B978-0-12-396535-6.00002-8
ISO/IEC JTC 1 Information technology. Big data Preliminary Report 2014. ISO/IEC (2015)
Kolevski, G., Gusev, M.: Analysis of cloud solutions for asset management. In: Gusev, M. (ed.) Conference: ICT Innovations 2010, Web Proceedings (2010). ISSN 1857-7288
Koutroumbas, K., Theodoridis, S.: Pattern Recognition, 4th edn. Burlington (2008). ISBN 978-1-59749-272-0. Retrieved 8 Jan 2018
Maciaszek, L.A., Skalniak, T., Biziel, G.: Architectural principles for service cloud applications. In: Shishkov, B. (ed.) BMSD 2014. LNIP, vol. 220, pp. 1–21. Springer, Cham (2020). https://doi.org/10.1007/978-3-319-20052-1_1
Martinez, H., Laukkanen, S., Mattila, J.: A new hybrid approach for augmented reality maintenance in scientific facilities. Int. J. Adv. Robot. Syst. 10, 1–10 (2013)
Metcalfe, D., Winter, S.: Operational Risk Management Software Market Size And Forecast 2018–2038. Verdentix (2018)
Mineraud, J., Mazhelis, O., Su, X., Tarkoma, S.: A gap analysis of internet-of-things platforms. Comput. Commun. 89–90, 5–16 (2016)
Pathria, R.K., Beale, P.D.: Statistical mechanics - computer simulations. In: Elsevier (ed.) Statistical Mechanics, 3rd edn. pp. 637–652. Academic Press, Cambridge (2011). https://doi.org/10.1016/B978-0-12-382188-1.00016-5
Perry, M.: Evaluating and Choosing an IoT Platform. O’Reilly Media, Inc., Sebastopol (2016)
Roda, I., Macchi, M.: A framework to embed asset management in production companies. Proc. Inst. Mech. Eng. Part O: J. Risk Reliab. (2018). https://doi.org/10.1177/1748006X17753501
Magdy, S.: The Curse of Dimensionality. IME Company. http://www.infme.com/curse-of-dimensionality-ml-big-data-ml-optimization-pca/
Palau, S.: Distributed collaborative prognostics. Ph.D. dissertation, University of Cambridge (2020)
Sola, R.A., Crespo, M.A.: Principles and Frameworks of Asset Management (2016)
Voulgaropoulos (2021). https://www.verdantix.com/blog/asset-investment-planning-what-is-it-and-how-is-it-useful)
Webel, S., Bockholt, U., Engelke, T., Gavish, N., Olbrich, M., Preusche, C.: An augmented reality training platform for assembly and maintenance skills. Robot. Auton. Syst. 61, 398–403 (2013)
Zhu, J., Ong, S.K., Nee, A.Y.C.: An authorable context-aware augmented reality system to assist the maintenance technicians. Int. J. Adv. Manuf. Technol. 66, 1699–1714 (2013)
Zio, E.: The future of risk assessment. Reliab. Eng. Syst. Saf. 177, 176–190 (2018). https://doi.org/10.1016/j.ress.2018.04.020
Acknowledgements
This paper has been written within the framework of the projects INMA “Asset Digitalization for INtelligent MAintenace” (Grant PY20 RE014 AICIA, founded by Junta de Andalucía PAIDI 2020, Andalucía FEDER 2014–2020) and Geminhi (Digital model for Intelligent Maintenance based on Hybrid prognostics models), (Grant US-1381456, founded by Junta de Andalucía, Andalucía FEDER 2014–2020).
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Crespo Márquez, A. (2023). Digital Transformation in Maintenance. In: Crespo Márquez, A., Gómez Fernández, J.F., González-Prida Díaz, V., Amadi-Echendu, J. (eds) 16th WCEAM Proceedings. WCEAM 2022. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-25448-2_7
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