Professor Supervisor of Master's Candidates
The Prognostic/ Predictive Health Monitoring (PHM) of milling cutters is key issue in the field of machine tool manufacturing. As the "teeth" of CNC machine tools, their health status directly affects the machining efficiency and the quality of products.
It has become a hot topic in both academic research and industries, which propose to employ big data and deep learning technology to realize high reliable tool fault diagnosis and predictive maintenance. However, the lack of high-quality yet life-cycle data has become the bottleneck restricting academic research and engineering promotion.
Supported by the Major Scientific and Technological Innovation Project of Shandong Province "R&D and application demonstration of key technologies for new adaptive production systems in the field of machine tool manufacturing", the research team cooperated with Qilu Institute of Technology to jointly setup a multi-sensor based data colloection platform on the machining tools. The purpose is to bulid a multi-dimensional data set which covers multi-working conditions for the full life cycle of milling cutters. The data set would be publicly released once the collection and testing are completed.
