Research area

Maintenance, Reliability and Asset Management

In practice, engineering systems are not perfect. A perfect design is one that continues to function and achieves the system goal without failure for a preselected lifetime. This is a deterministic, idealistic, impractical and economically unfeasible vision. In order to maximize system performance and efficient use of resources, the area of Maintenance, ​​Reliability and Asset Management involves the disciplines related to the analysis and prediction of failures, as well as the optimization of performance throughout the cycle of life.

These disciplines include (i) monitoring and forecasting damage to equipment and structures; (ii) quantification of the performance of technological systems and their interaction with the human factor by integrating human reliability, neuro-psychophysiology, and pattern recognition techniques; (iii) optimization of equipment and fleet maintenance; (iv) modeling of failure mechanisms in degradation processes based on failure physics.


Viviana Meruane

Enrique López

Rodrigo Pascual

Postgraduate courses:

  • Deep Learning in Failure Diagnosis and Prognosis.
  • Signal Processing and Machine Learning in Predictive Maintenance.