Intelligent design and database development of micro-texture ball-end milling cutters

There is an urgent need for the selection of micro-texture parameters and cutting parameters, as well as the rapid design of texture cutting tools, in response to the micro-texture ball-end milling technology. Therefore, this paper takes micro-texture ball-end milling cutter as the research object, sets up a milling test platform, and analyzes the influence of micro-texture parameters and cutting parameter changes on the cutting performance of the cutter. The results show that the main factors affecting the milling force, tool wear and surface roughness are cutting depth, cutting distance from the edge and feed, cutting speed, respectively. Then, the stepwise regression model was used as the objective function to call the genetic algorithm for multi-objective parameter optimization. The optimization results were v = 116.24 (m/min), a_p = 0.20 (mm), f = 0.05 (mm/r), D = 56.34 (μm), L = 158.08 (μm), L₁ = 120 (μm), the F: 202.43 N; VB: 16.65 μm; Ra: 240.35 μm. Finally, a C/S mode micro-texture ball-end milling titanium alloy data system is established based on the SQLite database in the Python programming environment. The system realizes information query and management, micro-texture distribution design, milling performance prediction, parameter optimization, system maintenance and help. The system can provide better data support for micro-texture ball-end milling technology.