AI-based optimization, condition monitoring and control of high performance machining systems.

Important results from the project

The project objectives were: (i) Seco Tools facility characterization for readiness and incorporation of the developed solutions into the machine tools platform, (ii) AI-techniques enhancement to adapt the existing production routines to enhance their performance and efficiency and increase level of automation, (iii) Testing and validation of the enhanced AI techniques in industrial facility, (iv) Employing the collected data during task (iii) to test the proposed concept for improving cutting data recommendations . All stated objectives of the project were achieved.

Expected long term effects

(i) The AI real-time tool condition monitoring system has been successfully tested in Seco Tools facilities. (ii) An application for the purchase of the necessary equipment and software for the implementation of the AI real-time tool condition monitoring system has been formed. (iii). A solution was proposed to create a cloud data warehouse common to NRC and Seco Tools that will unify and make more effective cooperation in the future. (iv). The possibility of improving the cutting data recommendation based on the tool condition monitoring system was successfully tested.

Approach and implementation

The project consisted of two parts: preparatory and practical. As part of the preparatory part, the holders for the sensors were manufactured at Seco and the necessary software was prepared. The practical part was Dr. Hassan´s visit to Seco, which consisted of his work on installing the tool condition monitoring system at Seco, as well as training and education of Seco personal how to use the tool condition monitoring system. The practical part of the project also included an introduction to Seco core business and meetings with various Seco departments.