Shape Memory Alloy Machining Evaluation throughCutting Force Sensor Monitoring

In this paper, sensor monitoring and advanced signal processing are applied for process optimisation in the machining of nickel-titanium (NiTi) alloys. Two Labs are involved in the joint research work: Machining Technology Laboratory at the Fraunhofer Institute for Machine Tools and Forming Technology (IWU), Chemnitz, Germany, and Laboratory for Advanced Production Technology (LAPT) at the Dept. of Materials and Production Engineering, University of Naples Federico II, Italy. The joint research activities comprise the detection, conditioning, processing, feature extraction, and pattern recognition of cutting force sensor signals obtained during turning tests on NiTi with variable cutting parameters generating different process conditions in order to achieve the process acceptability identification through a supervised expert knowledge based neural network approach.