Physics-based simulation and reliability modeling for multi-objective optimization of advanced cutting tools in machining titanium alloys.

摘要

Titanium alloys are widely used in various industries due to their superior characteristics such as high strength-to-weight ratio, toughness, corrosion resistance and bio-compatibility. Ti-6Al-4V is the most commonly used titanium alloy and considered as difficult-to-cut because of its low thermal conductivity, high chemical reactivity with cutting tool materials at elevated temperatures, and low modulus of elasticity. Therefore, rapid tool wear and poor surface quality are the issues in machining of this alloy. Hence, selecting appropriate cutting conditions (cutting speed, uncut chip thickness, depth of cut, etc.), tool materials, coatings, and geometry are essential not only to increase productivity and decrease the costs, but also to obtain a desirable surface integrity.;Initially, a modified constitutive model was proposed for Ti-6Al-4V which is able to predict the behavior under high strains and temperatures. Since workpiece experiences high strain, strain rate at elevated temperatures during machining, it is important to develop a material model that captures material behavior at these conditions. Using this material model, two dimensional finite element simulations were designed to predict machining forces and serrated chip geometry and results were validated with experiments. This verified material model was used in three dimensional finite element simulations to predict tool wear, temperature, stress and strain distributions. Effects of different cutting tool materials, coatings (TiAlN and cBN), geometry and machining process parameters were investigated. A reliability model for different types of cutting tools is created with experimental and physics-based data. Furthermore, using genetic algorithms, a multi-objective optimization problem was designed and solved to find the optimal process parameters (cutting speed and feed) and cutting tool selection in order to maximize reliability and machining efficiency. Finally, validation experiments were conducted to measure tool wear on uncoated and TiAlN coated inserts under the optimum cutting conditions with expected reliability rating. The results indicate that there is an adequate agreement and the discrepancy may be related to model uncertainty and stochastic nature of the tool wear.