Laser Beam Welding
Laser Beam Welding Group
Research with laser focus
Laser beam welding is a key tool for manufacturing e-vehicles and accelerating the adoption of lightweight structures and recycled materials.
Our work spans the entire research and innovation cycle, encompassing fundamental research (TRL 3/4), applied research (TRL 4/5), and technology development (TRL 6/7).
The focus lies on advancing the current understanding of laser-to-material interaction and developing innovative welding strategies for processing similar and dissimilar materials.
Additionally, we aim to create intelligent decision-making systems for autonomously selecting welding process parameters with real-time feedback control, achieving precision within a few milliseconds.
Discover our specialised research degrees in this dynamic field.
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Key capabilities
Our work focuses on improving the current understanding of laser-to-material interaction, developing new welding strategies to process similar and dissimilar materials, and delivering intelligent decision-making systems for autonomous selection of the welding process parameters and real-time (within a few milliseconds) feedback control.
We are addressing several grand challenges related to laser beam welding such as:
- Improve the current understanding of laser-to-material interaction for better processability of challenging materials such as aluminium (including recycled aluminium) and copper
- Explore novel welding strategies, such as laser beam shaping and assisted ultrasonic vibrations, to control grain structure and phase formation for enhanced functionality
- Develop intelligent decision-making systems for autonomous selection of the welding process parameters for real-time (within a few milliseconds) feedback control
- Link state-of-the-art machine learning methods and multi-physical simulations for addressing the broader challenge of incorporating the physical knowledge of the welding process into statistical learning rules.
Our expertise is in:
- Characterisation of laser weldments using state-of-the-art testing equipment
- Advanced multi-physical simulation for early validation
- Intelligent laser welding systems enabled by digital twins and state-of-the-art sensors
- Process scale-up from concept validation to certification of full-scale prototype
Key research findings include (1) the elucidation of laser beam shaping on the microstructure properties of similar and dissimilar materials; (2) the development of a real-time control system for high process capability.
The breadth of industry applications includes electric-vehicle manufacturing and lightweight structures for automotive and aerospace.
Improve understanding of laser-to-material interaction
Advanced physics-based models provide information about fluid flow and metal mixing, all of which are difficult to measure directly via experiments. We complement lab experimentation with physics-based models to advance our understanding of the laser-to-material interaction and the underlying physics of the welding process (i.e., beam wobbling and beam shaping). The synergy between experimental characterisation and physical-driven modelling will accelerate the new technology development and the deployment of novel applications of laser beam welding to process both similar and dissimilar material structures.
Explore novel strategies to weld similar and dissimilar materials
Strategic introduction of novel materials (virgin and recycled) requires the fundamental development of novel welding strategies, such as laser beam shaping, beam oscillation/wobbling and temporal power modulation, to control grain structure and phases’ formation for enhanced product functionality and performance. Complex inter-relationships between joint design, process selection and sustainable product development are being formulated to allow processing novel mixed-material combinations (i.e., steel, aluminium, copper, titanium), optimisation of functionally designed components and processing of recycled materials.
Integrate Industry 4.0 tools for autonomous laser beam welding
Stringent requirements from the growing e-mobility sector, and the fact that large arrays of welds are required to produce each finished assembly, are necessitating novel methodologies and technologies to uplift current laser welding solutions to make them Industry 4.0-compatible. We are addressing the broader challenge of incorporating the physical knowledge of the welding process into statistical learning rules, transforming our capacity to monitor and control the laser welding systems through the use of high-fidelity physics-based models and predictive tools such as ML/AI.
Develop novel process monitoring and control systems
The quality of laser weldments is assessed by measuring multiple features: (1) surface features – such as, melt pool width, concavity, convexity; and, (2) sub-surface features – such as, weld depth, interface width, weld pores and cracks. State-of-the-art has achieved some level of success for monitoring and control only of a single-feature, i.e., weld penetration depth. Our research focus is on in-process monitoring and real-time closed-loop control of multiple features with novel applications of ML/AI-based methods with best-in-class sensors.
Success stories
Research that generates impact
Explore the solutions that we create and the impact that we generate in response to societal, industrial and environmental challenges.