Professor Paz’s research is focused on energy conversion processes and electric machinery. Particularly on diagnosis of electric machinery, electric power quality and power generation. He believes it is critical to harmonize automation with efficient energy conversion processes in order to improve the sustainability of environmental friendly production processes. Prof. Paz studies and develops novel techniques to diagnose electrical machines for predictive and preventive maintenance. He focuses on the development of systematic methods that are implemented in the form of stochastic expert systems. The premise being that existing approaches erroneously assume that specific symptoms appear automatically in the presence of specific faults, which leads to credible predictions in only 1/3 of the faults and the remaining 2/3 to false positives that cause unnecessary interruption to productions lines. Prof. Paz’s has recently proposed a new form of diagnostics tool that combines stochastic and probabilistic methods with multi-parametric non-invasive analysis of electric motors, which accurately predict its state and identifies its short, medium and long-term probability of failure.
Currently Funded Research