Artificial Intelligence in Production: "AI for Laser Technology" conference

The second "AI for Laser Technology" conference will take place on September 28 and 29, 2021. Researchers, plant engineers, software developers and machine builders discuss the current status of the application of artificial intelligence in laser material processing online. The Fraunhofer Institute for Laser Technology ILT opens its laboratories for virtual tours.

The first conference "AI for Laser Technology" took place two years ago and dealt with areas of application for artificial intelligence (AI) in manufacturing. Many ideas have now arrived in industries.

This year's event discusses current trends. A 100 percent quality control is important for users. Here, AI opens up the possibility of monitoring the quality in-situ for each individual part with high precision and quickly identifying possible production disruptions. For this purpose, in-line process diagnostics have been developed on the manufacturer's side in recent years. Thanks to modern computing technology, AI ​​is able to process the amounts of data generated in real-time. "At this year's 'AI for Laser Technology' conference we want to look at and discuss precisely these trends and the state of the art", says Peter Abels from Fraunhofer ILT in Aachen about the aim of the conference.

AI learns to capture complex data and to use it for process control

AI in manufacturing aims to record and process data with the regulation to an autonomous process. With human help, AI ​​first learns to recognize complex data in structures. The process begins with the evaluation of (image)data. Deviations from the norm can thus be identified in good time.

"We were able to significantly improve the results in metallic 3D printing with AI", says co-organizer Knaak, who will demonstrate the process using an example. To detect defects, the component surface in each layer was photographed with a high-resolution HDR camera in a system for the Laser Powder Bed Fusion (LPBF) process in order to make possible warpage of the component measurable during the process and to check roughness on the surface. With the help of AI, laser parameters can also be changed in a targeted manner in the process in order to react dynamically to changes in the process status.

Therefore, the lectures at this year's “AI for Laser Technology” conference will focus on the acquisition and processing of data from production processes such as laser welding. The focus is on end-to-end process and quality control. In addition, AI-based control processes and the development of AI software in various applications are discussed. To optimizing errors, AI also reduces complexity in order to make processes less dependent on the intuition of individual experts.

Contact: Peter Abels, Fraunhofer Institute for Laser Technology ILT peter.abels@ilt.fraunhofer.de