Collaborative Projects

The Greenlake AI project aims to transform industrial maintenance and energy management through the integration of Artificial Intelligence (AI), IoT, Big Data, Machine Learning, and cognitive models. This initiative proposes a paradigm shift from reactive and preventive models towards predictive and cognitive maintenance, enabling industrial companies to be more efficient, sustainable, and proactive in managing their facilities.

This project seeks to develop a new sustainable, plant-based material to replace conventional plastics used in automotive interior components. The initiative responds to growing regulatory, social, and environmental pressures on the automotive sector to reduce the use of petroleum-derived plastics, advancing toward more environmentally friendly solutions aligned with the principles of the circular economy.

The “Aditech” project focuses on researching and developing solutions that allow the reuse of industrial plastic waste, particularly from the automotive sector, as raw material for advanced additive manufacturing processes. This strategic initiative aims to reduce environmental impact and improve production efficiency by integrating complex waste into emerging technologies such as robotic 3D printing.

The VoltIA project focuses on industrial research into an AI-based technology designed to determine the State of Health (SoH) of electric vehicle batteries during fast-charging processes. Its development addresses one of the key challenges of sustainable mobility: optimizing battery range and extending battery lifespan, both essential elements in the transition toward more efficient and decarbonized transportation.

The LOGIHUMAN project—Intelligent Automation and Flexible Traceability in Internal Logistics Processes—is led by the Aragón Automotive Cluster (CAAR) together with Algontec, CEFA, Moontech, Aquiles Solutions, Vitum, and the Digital Cluster of Catalonia. Its goal is to investigate new technological solutions that drive intelligent automation and advanced traceability in internal logistics processes within industrial environments. The initiative addresses current limitations in integrating physical and digital flows, as well as capturing and recording events related to production and quality, particularly in scenarios where human intervention remains necessary.