Thirteen funded and partner-led initiatives across robotic welding, metal additive manufacturing, simulation, process optimization, monitoring, and traceability.
Integrating RobTrack with open-source ROS 2 and FIWARE middleware to create a standardized, brand-agnostic platform that optimizes process parameters while keeping human operators at the center of decision-making. A collaboration with Mechatronics Innovation Lab combining real-time monitoring, AI-driven optimization, and user-friendly interfaces.
Transforming on-site steel construction through federated AI-powered collaborative robotic welding. Building on RobTrack, FAROS networks multiple collaborative robots through a centralized intelligence platform for real-time welding parameter optimization, digital traceability, and a "welding-as-a-service" model for faster, more sustainable construction.
Deploying a field-ready collaborative robotic welding workflow for on-site inspection, diagnosis, and repair of crane rails in ports and heavy industry. Built on RobTrack, the system combines AI-driven parameter selection, depth-camera scanning, laser profilometry, adaptive tool-path generation, WAAM repair, SAFE-RP collision avoidance, and DPP-based digital traceability to extend asset life while reducing manual rework and shutdown time.
Developing robust and sustainable rare earth element-free permanent magnets using novel AlNiCo and high-entropy alloy compositions through additive manufacturing. The project combines open-source modeling and machine-learning-guided high-throughput screening for applications in wind turbines, ship propulsion, heat pumps, and automotive systems.
Integrating high-performance computing into numerical simulation and physics-based AI workflows for welding and additive manufacturing. The project uses experimentally determined boundary conditions from RobTrack process data to support WAAM, LMD, and traditional welding across energy, aerospace, and automotive applications.
AIRISE-funded work advancing RobTrack with AI-driven model predictive control for real-time, location-specific parameter adjustment during deposition. The project combines laser linear profilometry with machine-learning workflows for screening, monitoring, qualification, and certification of welding and additive manufacturing processes.
A material innovation platform for fast-track alloy development and on-demand production. The project combines accelerated alloy design, powder synthesis and atomization, AM parameter establishment, and validated component production against industrial requirements.
Developing a robotized x-ray sensor-based, non-contact hardness measurement system for weld beads. The system supports greener manufacturing by replacing classical weld characterization routines with faster robotized and digitalized inspection workflows.
A traveling cell that pairs the RobTrack control stack with collaborative arms to demonstrate autonomous parameter tuning in minutes. The platform brings adaptive control, real-time analytics, and mobile workcell deployment into a practical demonstration format.
EU-funded work developing a physics-informed AI software framework for metallic additive manufacturing. The system optimizes material-specific build conditions for DED and PBF processes, automates design-of-experiment workflows, and supports precise parameter selection across energy, aerospace, automotive, and manufacturing sectors.
Redesigning and producing aircraft brackets using metal 3D printing through the AMable programme. The project validated the process chain from powder selection and build strategy to post-treatment and surface finishing, delivering lighter parts with reduced material waste while meeting aerospace quality requirements.
Demonstrating metal 3D printing for lighter, high-performance aircraft components with aerospace-grade quality. The project established a complete value chain from design and digital simulation through production, finishing, and quality control, validating advanced aluminium alloy manufacturing while reducing material use.
Introducing laser powder bed fusion for complex, lightweight aero-structures. The project redesigned stainless-steel aircraft components to use less raw material and reduce weight while maintaining performance, building in-house expertise in design, simulation, and process engineering toward near "buy-to-fly" material ratios.