4.6 Article

Optimization of tool axis vector for mirror milling of thin-walled parts based on kinematic constraints

Journal

Publisher

SPRINGER LONDON LTD
DOI: 10.1007/s00170-022-10494-8

Keywords

Mirror milling; Kinematic constraints; Machining path; Tool axis vector

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This paper discusses the importance and steps of tool axis vector optimization in mirror milling of thin-walled parts. By planning the machining path and optimizing the tool axis vector based on kinematic constraints, the quality and efficiency of the machining process can be greatly improved. The feasibility of the proposed optimization model is verified through simulation and experimentation.
In mirror milling of thin-walled parts, the machining path and change in tool axis vector will affect the surface quality of the workpiece and machining efficiency. Reasonable planning of the tool axis vector can avoid the occurrence of overcutting and undercutting and prevent a collision between the tool and the workpiece and damage of the spindle. At the same time, the rapid change in tool axis vector will also affect the machining quality, so optimization of the tool axis vector is very important in mirror milling. In this paper, the optimization of the tool axis vector for titanium alloy skin processing is divided into two steps. The first optimization is carried out on the basis of the planning of the machining path. First, the machining path is obtained according to constraints of mirror milling, and the iterative algorithm of the tool position is used. The tool location point is obtained, and then the tool location point is projected onto the parameter plane to optimize the tool axis vector. The second optimization is to optimize the tool axis vector based on kinematic constraints. The rotation axis of the machine tool needs to meet the constraints of the maximum angular velocity, the maximum angular acceleration, and the maximum angular jerk. First, the optimal feed rate of the mirror milling machine tool is obtained. The tool axis vector is optimized for optimization goals with minimum motion fluctuation stop and minimum adjacent machining time. Subsequently, the optimized machining path and the tool axis vector were simulated and tested. Finally, the simulation and experimental results were determined by an analysis that proved the feasibility of the optimized model proposed in this paper. At the same time, the results of the experimental measurements also showed that the optimized machining path had been greatly improved in terms of quality and efficiency.

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