Optimizing the parameters for force, temperature, and metal removal rate: a multi-feature fusion model for titanium alloy milling

Abstract

In the processing of titanium alloy, the milling parameters determine the process temperature and force. Increasing the milling temperature and force can affect the quality of the titanium alloy produced. In this study, we developed a multi-feature fusion model for high-quality titanium alloy workpieces. In the milling experiments with different milling parameters, an infrared thermal imager and a three-dimensional dynamometer were used to collect the time-domain signals for temperature near the tip of the milling cutter and the milling force. Based on the experimental data, a multi-feature fusion model was established with the milling temperature, milling force, and metal removal rate as the targeted variables, and the milling parameters as the optimized parameters. Based on the particle swarm optimization algorithm, the optimal milling parameters within the test parameters were resolved using the multi-feature fusion model. The results show that: within the milling parameter range of the experimental design, the optimal solutions for the milling parameters are: milling speed of 22.14 m/min; feed speed of 8.25 mm/min; milling depth of 1.36 mm. The multi-feature fusion model resulted in lower milling temperature and force, and provides theoretical guidance for scientifically designing the parameters for the milling process.