An enhanced cutting force model and its application in tool breakage detection for end milling process using NURBS based neural-fuzzy system

An enhanced cutting force model of the end milling process was developed. Geometrical representation of the cut surface was proposed to describe interactions between the cut surface and tool deflections. From this consideration, the uncut chip thickness was calculated. The cutting force was then calculated iteratively at each time step by using the relationships between the cut surface and tool deflections. The simulated cutting forces were verified by comparing with the actual cutting forces obtained from experiments.; Tool breakage detection and estimation schemes using the cutting force model of end milling process are also presented. In the tool breakage detection scheme, the total difference in peak forces between the normal tool and broken tool was used. If the absolute value of total difference in peak forces was greater than the threshold value, then tool breakage was expected. The amount of tool breakage was estimated by the neural-fuzzy system with flexible membership functions based on NURBS (Non-Uniform Rational B-spline) curve, which was trained with simulated cutting force data for broken and normal tools. The simulated cutting force data for training the neural fuzzy systems was obtained from the proposed dynamic cutting force model. The tool breakage detection and estimation were performed by using actual cutting force data.