Lasers have revolutionized manufacturing, playing a crucial role in cutting, drilling, marking, welding, and 3D printing. However, laser-based manufacturing is undergoing a fundamental change through the introduction of autonomous monitoring, control, and correction processes, all of which are central to the Manufacturing 4.0 and Smart Factory paradigms. The key ingredient in this transformation is deep learning, which has the potential to help create lasers that can make independent decisions in real time. Laser companies are rapidly investing in this pivotal technology, and 2023 saw the first AI-supported laser welding products come to market.

In this webinar, Ben Mills will discuss the application of deep learning to the field of laser-based manufacturing, with applications including laser parameter optimization, predicting the outcome of laser machining, indirect imaging of the sample from plasma and acoustic information, identification of errors during machining, coherent beam combination, and identification of optimal strategies for machining bespoke structures.

What You Will Learn:
• An understanding of the exponential progress in deep learning
• An understanding of deep learning as an engineering tool for finding solutions to intractable problems
• Examples of how to quickly apply state-of-art deep learning to your research and development activities

Who Should Attend:
• PhD students looking to use deep learning to automate their laser experiments
• Academics wanting to understand how to lead their research activity toward deep learning
• Industry leaders wanting to understand the wider landscape of deep learning and lasers

About the Presenter: Ben Mills from Optoelectronics Research Center, University of Southampton

Dr. Ben Mills is a Principal Research Fellow at the University of Southampton and world-leader in the application of deep learning for laser materials processing. He has over 150 papers, 20 invited talks, and £11 million in grant income in this area, and has recent awards of "The Top 100 in Photonics" and the AILU "Innovation Award".