Transforming Programme WP13 - E – Resource and Energy efficiency and renewables

Advance4i aims to respond to 2 major problems:

(i) Low digitalization of the Portuguese industrial fabric and the need to substantially improve the sustainability of its processes and

(ii) Maintenance as a factor in the resilience and competitiveness of a sustainable industry.

Digitalization opens up new opportunities to achieve the optimum compromise between these two factors by intelligently exploiting data from the shop floor. Through advanced Machine Learning (ML) algorithms, it is possible to predict and anticipate the occurrence of equipment failures and suggest configuration changes to minimize maintenance costs, spare parts inventory and production stoppages.

This approach, called Predictive Maintenance, represents state-of-the-art maintenance approaches. However, it requires effective digitization of the shopfloor, through the implementation of IoT platforms capable of bringing together digital data and the implementation of ML models for predictive maintenance.

The use of ML, particularly deep learning, in predictive maintenance has shown positive results, successfully predicting the RUL (Remaining Useful Life) of production machines. This makes it possible to anticipate maintenance actions and prevent failures that could interrupt production.