Cutting Tool Geometry Suggestions Based on a Fuzzy Logic Model

This work is about a fuzzy logic model in order to suggest an initial cutting tool geometry for each work-tool material combination. The Takagi-Sugeno-Kang model was used to design the fuzzy system that was trained with suggested empirical cutting tool geometry values. The system inputs are the specific cutting energy of the work material and the ratio of the quadratic bending strength over modulus of elasticity of the cutting tool material. The outputs are: the normal rake angle (γn), the normal clearance angle (αn) and the cutting edge inclination angle (λs). The outputs evaluation is based on a macro-level optimization of cutting tool geometry proposed in the literature; in this methodology the tool geometry is characterized by a geometric entity number that is calculated in terms of the cutting tool angles and its optimal value depends of the work-tool paired materials.