Analysis and Definition of Strategies and Scenarios for the Development of Industrial Maintenance Systems Oriented Towards Energy Efficiency and Environmental Friendliness in the City of Cuenca

This multidisciplinary project focuses on the conceptualization, design, development, and validation of strategies for industrial maintenance systems that prioritize energy efficiency and environmental impact in Cuenca. The methodology is structured in phases, beginning with conceptualization, where techniques for failure severity analysis using data mining and statistical analysis of waste oils are evaluated. This includes researcher training and the development of algorithms based on machine learning techniques (such as neural networks, Support Vector Machines, and decision trees) for failure assessment. The second phase involves the detailed design and computational implementation of these intelligent and statistical models, including preliminary testing and the execution of experimental protocols for the physicochemical analysis of collected used oils. Finally, a rigorous validation of the results is performed by comparing the predictive performance of the developed algorithms against other proposals, and feasible scenarios for waste oil purification systems are defined, culminating in the dissemination of technical and scientific findings.<br/><br/><b>Goal</b>: <br/>To analyze and define scenarios and strategies for developing industrial maintenance systems oriented towards energy efficiency and environmental friendliness within the city of Cuenca.<br/><br/><b>Research lines</b>: <br/>Industrial maintenance