Maintenet: AI based condition monitoring for assets of the electric power distribution networks
Maintenet, a project bringing the power of prediction into the electric distribution network and critical assets, led by Mipu Energy Data in Italy, it will provide solutions in the predictive maintenance area of experimentation.
Who will help implement the AI solution?
Mipu Energy Data offers a comprehensive portfolio of services, technologies and trainings based on our competences related to Energy Efficiency, Predictive Maintenance and Reliability and on our know-how in Predictive Modelling, extensively employing Artificial Intelligence models to perform data analysis. In particular, Mipu is active in provision of consulting services and trainings for Energy Managers, consultants and corporates, helping to reach energy efficiency goals, to cut waste and save money. Our experienced team carries out energy audits to analyse consumption and elaborate energy models of prediction and control. In addition to that, Mipu provides consulting services, software and hardware solution to digitize industrial, manufacturing environments, facilities and infrastructures, where assets are augmented with wireless connectivity and sensors, connected to a system that can visualize the entire process, control, and make decisions on its own. In particular, predictive maintenance is a method of preventing asset failure by analysing operating and maintenance data to identify patterns and predict issues before they happen. The expertise developed in the industrial field has enabled us to move forward in the field of digital innovation integrating services that apply Machine Learning and Artificial Intelligence to industrial processes. The know-how related to the application field is fundamental for the development of solutions able to provide a comprehensive response to the needs of digitization and optimization of operations.
What is the AI solution the project plans to implement?
Leveraging on our mix of engineering and data science knowledge, we proposed the integration of MAINTENET solution in the AI on demand platform, obtaining I-NERGY Technology Transfer Programme funding. The project aims at developing Artificial Intelligence models to constantly monitor the health status of assets within the distribution network. Machine Learning is effective in modelling the behaviour of assets abiding underlying physical laws. In particular, it is possible to precisely model the relationship between assets input and output variables, so that when the observations significantly differ from the algorithm’s prediction, we have an indication of an anomaly bound to occur.