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© The University of Sheffield

Tim Rooker

Project Title: Applications of in-process inspection and machine learning for the intelligent monitoring of machine tools.

Academic Supervisor: Dr Nikolaos Dervilis

AMRC Supervisor: Dr Jon Stammers

Industrial Sponsor: Metrology software products ltd.

Tim’s current research, in collaboration with the Advanced Manufacturing Research Centre and metrology software products ltd., concerns the drift of geometric performance in machine tools throughout their operable life and between calibration cycles. He is exploring the use of machine learning paradigms to build intelligent monitoring models for this purpose. Potential benefits from this research include reduced frequency calibration cycles for higher manufacturing productivity, as well as an insight into the relationships between health parameters, which collectively determine the geometric error characteristics of the finished workpiece.

Publications:

Publications:
  • T Rooker, N Dervilis, J Stammers, K Worden, metrology software products ltd.  Machine tool health monitoring with geometric performance data. 12th BSSM International Conference on Advances in Experimental Mechanics.  August 2017.