• An In-Person-Only Event
  • Technical Conference:  07 – 12 May 2023
  • The CLEO Hub: 09 – 11 May 2023

Artificial Intelligence in Material Processing

Organizers

Andreas Michalowski, University of Stuttgart, Germany

Beat Neuenschwander, Berner Fachhochschule, Switzerland

 

Machine Learning is increasingly proving to be a very powerful approach for supporting a wide variety of technologies. In many cases, the appropriate adaptation of established machine learning methods to new fields of application already represents a major technological advance. In the field of laser material processing, there are numerous interesting approaches to using machine learning in a supportive manner. Applications are for example in control and feedback control systems, process monitoring and optimization. The topical review offers the opportunity to discuss current scientific results, allows to demonstrate successful applications and to identify further research needs.

 

Invited Speakers

Satoshi Hasegawa, Utsunomiya University, Japan
Laser processing with adaptive optics based on convolutional neural network

Benjamin Mills, University of Southampton, UK
Modelling and Optimisation of Femtosecond Laser Machining via Deep Learning

Aiko Narazaki, National Institute of Advanced Industrial Science and Technology (AIST), Japan
Data-driven ultrashort pulse laser processing based on novel in-process monitoring and AI high-speed optimization

Maja Rudolph, Bosch Center of Artificial Intelligence (BCAI), USA
Hybrid Modeling Design Patterns – A Modular Approach for Solving Modeling Challenges Combining First Principles and Data

Joachim Schwarz, Precitec GmbH & Co KG, Switzerland
Artificial intelligence in industrial laser material processing

Shuntaro Tani, University of Tokyo, Japan
Neural-network-based ultrashort laser ablation simulator for micro-machining