TRUMPF (United Kingdom)

Advancements in laser material processing, particularly in EV battery production, require innovative solutions. Dynamic beam control of fiber lasers has emerged as a promising technology to meet these needs. This contribution examines the challenges in EV battery production and the solutions provided by these lasers. Through dynamic beam control, fiber guided lasers enable precise and efficient welding of copper and aluminum components. Adjustable beam parameters such as intensity, shape, and size enhance precision, productivity, and material utilization. These capabilities of dynamic beam-controlled lasers drive innovation in manufacturing processes for the EV industry and beyond.

Predicting target material topography resulting from fibre laser cutting is challenging. We show that deep learning offers a data-driven capability for predicting the topography of 2mm thick laser machined stainless steel for different cutting speeds.

Using a specially designed all-fibre mode converter we generate and deliver so-called “petal” beam with high-power output. We observe that under partial obstruction, the petal beam can be reconstituted through propagation.