Cutting tool wear estimation for turning

The experimental investigation on cutting tool wear and a model for tool wear estimation is reported in this paper. The changes in the values of cutting forces, vibrations and acoustic emissions with cutting tool wear are recoded and analyzed. On the basis of experimental results a model is developed for tool wear estimation in turning operations using Adaptive Neuro fuzzy Inference system (ANFIS). Acoustic emission (Ring down count), vibrations (acceleration) and cutting forces along with time have been used to formulate model. This model is capable of estimating the wear rate of the cutting tool. The wear estimation results obtained by the model are compared with the practical results and are presented. The model performed quite satisfactory results with the actual and predicted tool wear values. The model can also be used for estimating tool wear on-line but the accuracy of the model depends upon the proper training and section of data points.