Collaborative Projects

This project represents the second phase of an industrial research initiative focused on applying Artificial Intelligence and Big Data techniques to optimize manufacturing processes within the consortium formed by CEFA, MRA, and ALGONTEC. The first phase, approved under the AEI 22b call, was successfully executed and laid the groundwork for this continuation.

This project aims to implement a scalable artificial intelligence system based on real-time process data analysis to improve quality, production efficiency, and predictive maintenance in a robotic welding cell for automotive components. The system is designed with an open and flexible data architecture that will allow the future integration of new IoT devices, such as cameras to evaluate the degradation of welding consumables.

The main objective of this project is to develop a monitoring system for machining processes in ferrous and non-ferrous materials, with the goal of reusing waste generated in the form of metal shavings and transforming them into new value-added materials. The initiative is structured in two phases: the first carried out under the AEI 2022b call, and the second—covered in this report—focused on validation and practical application of the developed technologies.

In its second phase, this project advances research into flexible additive manufacturing technologies through the combined use of robotics, intelligent systems, computer vision, artificial intelligence, and digital twin applications for sustainable materials. The integration of these technologies will optimize additive manufacturing processes, driving greater efficiency, sustainability, and zero-defect production, with a significantly reduced environmental impact.

This project focuses on implementing a pilot manufacturing system at the Zatec plant, designed for the automation and optimization of plastic injection processes. The system covers two key areas: automated assembly of O-rings onto injected plastic parts and conditioning of hygroscopic parts, including optimized packaging that contributes to reducing the carbon footprint.

The YMPACTO project aims to develop an AI-based internal communication system designed to enhance sustainability in resource use, organizational transparency, and stakeholder engagement across the industrial value chain. The initiative is based on the premise that each individual and organization can generate a positive impact in three dimensions: responsible resource use, the research and application of innovative technologies such as generative AI, and the unified management of critical systems to benefit workers.

This project continues the ECOMOB “Connecting Mobility Ecosystem” initiative, approved under the AEI 2022 call (file AEI-010500-2022b-311). The first phase, successfully completed in April 2023, focused on knowledge dissemination and transfer regarding different digital enablers in the automotive sector, with special emphasis on the role of the six regional automotive and mobility clusters that make up the consortium.