Success Stories Concerning the Implementation of Predictive Maintenance Through the Use of Industry 4.0 Technologies in Colombian Companies
DOI:
https://doi.org/10.26439/ciis2020.5508Keywords:
Industry 4.0, technologies 4.0, predictive maintenance, energy efficiency, sustainable process, maintenance managementAbstract
With the arrival of new technologies, maintenance has taken substantial steps in recent decades, leaving aside the manual collection of data. More efficient and reliable automated and computerized systems, predictive inspection techniques and real-time remo te-controlled systems have been adopted. This has allowed companies to develop specific maintenance plans based on the analysis of the collected data flow, generating benefits in terms of time and cost. This article will present the results obtained by two top Colombian companies in the implementation of Industry 4.0 technologies in predictive maintenance processes. An analysis of their conditions of success and the way this methodology promoted their recognition and prestige in their respective industry sectors was performed. The entire research process was carried out using virtual tools and scenarios given the current situation with COVID-19.
Downloads
References
Alsyouf, I. (2007). The Role of Maintenance in Improving Companies’ Productivity and Profitability. International Journal of Production Economics, 105, 70-78. https://doi.org/10.1016/j.ijpe.2004.06.057
Asociación Nacional de Empresarios de Colombia. (2019). Informe de la encuesta de transformación digital 2019. http://www.andi.com.co/Uploads/ANALISIS%20%20ENCUESTA%20DE%20TRANSFORMACI%C3%93N%20DIGITAL%202019%20-%20ANDI.pdf
Asociación Nacional de Empresarios de Colombia e iNNpulsa. (2018). Cierre de brechas de innovación y tecnología. https://www.innpulsacolombia.com/es/cierre-de-brechas-de-innovacion-y-tecnologia
Dueñas Ramírez, L. M., y Villegas López, G. A. (2020). Technological Advances in Computer Science that Define Maintenance Concerns in Industry 4.0 in Colombia. Journal of Physics: Conference Series, 1513, 12010. https://doi.org/10.1088/1742-6596/1513/1/012010
Fuentes, D. (29 de mayo del 2020). Mantenimiento centrado en confiabilidad Grupo Avidesa MacPollo. (C. A. Castaño Restrepo, entrevistador).
Guba, E. G., y Lincoln, Y. S. (1982). Epistemological and Methodological Bases of Naturalistic Inquiry. ECTJ, 30(4), 233-252.
Hernán-García, M., Lineros-González, C., y Ruiz-Azarola, A. (2020). Cómo adaptar una investigación cualitativa a contextos de confinamiento. Gaceta Sanitaria. https://doi.org/https://doi.org/10.1016/j.gaceta.2020.06.007
Jiménez Arango, C. A. (15 de mayo del 2020). Entrevista Departamento Mantenimiento y Sistemas de Refrigeración EAFIT. (S. Castiblanco Tique, entrevistador).
Kobbacy, K., y Prabhakar Murty, D. (2006). Springer Series in Reliability Engineering. Springer. https://doi.org/10.1007/978-1-4471-4588-2
Lee, J., Lapira, E., Bagheri, B., y Kao, H. (2013). Recent Advances and Trends in Predictive Manufacturing Systems in Big Data Environment. Manufacturing Letters, 1(1), 38-41. https://doi.org/https://doi.org/10.1016/j.mfglet.2013.09.005
Montero Jimenez, J., Schwartz, S., Vingerhoeds, R., Grabot, B., y Salaün, M. (2020). Towards Multi-model Approaches to Predictive Maintenance: A Systematic Literature Survey on Diagnostics and Prognostics. Journal of Manufacturing Systems, 56, 539-557. https://doi.org/10.1016/j.jmsy.2020.07.008
Morse, J. M., y Field, P. A. (1995). Qualitative Research Methods for Health Professionals. Sage Publications, Inc.
Morse, J. M., Hupcey, J. E., Penrod, J., y Mitcham, C. (2002). Integrating Concepts for the Development of Qualitatively-Derived Theory. Research and Theory for Nursing Practice, 16(1), 5-18.
Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2.a ed.). Sage Publications, Inc.
Russmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Engel, P., y Harnisch, M. (2015). Industry 4.0: The future of productivity and growth in manufacturing industries. Boston Consulting Group, 9(1), 54-89.
Sahal, R., Breslin, J. G., y Ali, M. I. (2020). Big Data and Stream Processing Platforms for Industry 4.0 Requirements Mapping for a Predictive Maintenance Use Case. Journal of Manufacturing Systems, 54, 138-151. https://doi.org/https://doi.org/10.1016/j.jmsy.2019.11.004
Selcuk, S. (2017). Predictive Maintenance, its Implementation and Latest Trends. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 231(9),1670-1679. https://doi.org/10.1177/0954405415601640
Strauss, A., y Corbin, J. (2004). Bases de la investigación cualitativa. Técnicas y procedimientos para desarrollar la teoría fundamentada. En A. Strauss y J. Corbin, Bases de la investigación cualitativa. Técnicas y procedimientos para desarrollar la teoría fundamentada. Universidad de Antioquia.
