Diseño de sistemas de diagnóstico y pronóstico en aplicaciones electromecánicas

The use of a modern technological system requires a good engineering approach, optimized operations, and proper maintenance to keep the system in an optimal state. In maintenance, there are multiple strategies to determine the moment to trigger maintenance actions. Predictive maintenance is one of these strategies that have increasingly earned attention from industry and academy in the last decade. Predictive maintenance focuses on the organization of maintenance actions according to the actual health state of the system, aiming at giving a precise indication of when a maintenance intervention will be necessary. Predictive maintenance is normally implemented by means of specialized systems that incorporate one of several models to fulfil diagnostics and prognostics tasks. However, there are still multiple knowledge gaps in this topic that provide opportunities for research to carry out new research projects. The design of predictive maintenance systems, the selection of the optimal diagnosis or prognosis model, data uncertainty management are just a few examples of the research opportunities that can be addressed. In this project, participants are taking advantage of their previous experiences on the topic and their international contacts to create a multidisciplinary team that aims to address some of the above-mentioned research opportunities and position TEC as a reference in this research subject.

Desarrollar modelos de diagnóstico y/o pronóstico, aplicables a estrategias predictivas de acuerdo a requerimientos formalizados en aplicaciones electromecánicas.

Transformación digital