Scientists use AI to predict the reusability of waste lubricant oil and prevent potential losses
Despite regeneration success rates of over 80% in Portugal, some waste oils coagulate, resulting in equipment downtime and subsequent product disposal.
A research team from the Faculty of Sciences and Technology of the University of Coimbra (FCTUC) is developing process analytical technology and artificial intelligence (AI) techniques that can predict if a waste lubricant oil (WLO) can be reused before the start of the regeneration process. In Portugal, the regeneration rate for waste oils is over 80%, but some oils have coagulation problems during the process which, if not detected, will lead to a shutdown and the subsequent loss of all potentially regenerable oil.
Marco Reis, Professor at the Department of Chemical Engineering (DEQ) and researcher at CERES - Chemical Engineering and Renewable Resources for Sustainability, who is also the project coordinator, explains: "We are developing an AI-based tool that will allow us to predict the regeneration potential of these oils quickly. He adds: "Waste lubricant oils (WLOs) are essential for the operation of many types of machinery used intensively in industry and society. Their regeneration is, therefore, crucial to maximise the efficient use of natural resources and minimise environmental impact.
This research is being carried out in collaboration with Sogilub - Sociedade de Gestão Integrada de Óleos Lubrificantes Usados, Lda, as part of the project Intelligent Computation and Analytics for the Regeneration of Oils (ICARO), and also involves the participation of professors Licínio Ferreira, Margarida Quina and Pedro Faia, and researchers Tiago Rato, Rúben Gariso and Sofia Braz.