As part of the AI-SLAM project, the Fraunhofer Institute for Laser Technology (ILT) is working with Canadian partners on an AI-supported laser cladding process for wear parts in the mining industry. The aim is to optimize the coating of components such as excavator teeth and drill bits by automatically monitoring and adjusting the process parameters. Artificial intelligence is to be used to make the process more efficient and reduce the need for experienced machine operators.
AI-SLAM, an acronym for “Artificial Intelligence Enhancement of Process Sensing for Adaptive Laser Additive Manufacturing”, aims to combine laser material deposition (LMD) with machine learning. The OpenARMS software from BCT uses control and data processing systems that record geometries in real time, compensate for process deviations and carry out optimizations. The AI automatically adjusts the welding parameters to ensure a uniform coating. This is done using the mIOS platform from Canadian company Braintoy, which enables software integration with various sensor data.
For the mining industry, which has to repair and coat millions of wear parts every year, the AI-supported process brings decisive advantages.
Project manager Max Zimmermann: “We qualify the LMD processes in order to be able to say whether it is a good or a bad coating. The main task is to visualize and digitalize our expertise.”
In addition to increasing efficiency through AI monitoring, a real-time process is being developed that enables proactive error prevention.
Amit Varma, co-founder of Braintoy Inc. in Calgary, Canada: “We also want to work with other partners in the future, because we don’t want to keep our R&D results to ourselves.”
This should not only reduce operating costs, but also facilitate access to LMD technology for less experienced users.
AI-SLAM will be presented at the upcoming Formnext 2024, where potential partners from industry are invited to learn about the current status and future possibilities of the project.
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