In 5-axis machining, the existing tool's axisvectoroptimization methods are limited since they only consider the global collision between the tool and the workpiece while aiming at the ball-nosed cutter. A multi...
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In 5-axis machining, the existing tool's axisvectoroptimization methods are limited since they only consider the global collision between the tool and the workpiece while aiming at the ball-nosed cutter. A multi-factor vectoroptimization method for the face milling cutter shaft is proposed to solve this problem. This method comprehensively considers machining global collision, cutting force, the angular displacement of a rotating shaft, and angular speed. An improved global collision detection method of cutter axisvector based on the NURBS surface principle is developed, and a global collision detection algorithm is employed to determine the cutter machining global collision. The relationship model between the end-milling cutter axisvector and cutting force variation is established to optimize the cutting force. In addition, an optimization model of angular displacement and velocity of the machine tool's rotating axis is proposed based on Dijkstra optimal path algorithm. The CAM software simulation and experimental validation are conducted using a large propeller with a complex surface. The tool's axisvectoroptimization algorithm is applied to the propeller results. Comparing the tool's axisvectoroptimization results to those obtained without optimization, it is discovered that the surface workpiece's machining quality has significantly increased.
In five-axis machining, nonlinear errors arise due to deviations between the interpolated cutter contact point (CCP) and the tool cutting edge profile, which negatively impacts machining accuracy and surface quality. ...
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In five-axis machining, nonlinear errors arise due to deviations between the interpolated cutter contact point (CCP) and the tool cutting edge profile, which negatively impacts machining accuracy and surface quality. To address this challenge, a real-time optimization method for both tool position and toolaxisvector is proposed, based on the interpolated CCP. First, a cutting profile surface calculation is introduced, enabling the determination of the shortest distance between the interpolated CCP and the cutting profile. This allows precise compensation of CCP errors caused by overcutting or undercutting, improving machining accuracy. Additionally, a hybrid interpolation method combining linear interpolation and quaternion spherical linear interpolation (SLERP) is employed to ensure smooth transitions in toolaxis orientation. This approach maintains computational efficiency while providing stability in regions with large angular variations. Experimental results show that the proposed method significantly reduces CCP errors and surface roughness, enhancing machining precision and surface quality. The approach demonstrates high efficiency and reliability in machining complex surfaces, offering a robust solution for high-precision applications in five-axis machining.
Two rotating axes of the five-axis machine tools complicate the kinematics, which increases the difficulty of trajectory planning of five-axis CNC machining. In the process of machining a free-form surface with a ball...
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Two rotating axes of the five-axis machine tools complicate the kinematics, which increases the difficulty of trajectory planning of five-axis CNC machining. In the process of machining a free-form surface with a ball-end cutter, the tool is required to follow the tool tip path of the surface and the restriction of tool orientation is only constrained within a certain range. This paper proposes a planning algorithm based on differential vectoroptimization for generating a smooth trajectory of each axis for five-axis machining. Firstly, the kinematic model of the five-axis CNC machine tool and the Jacobian matrix are built. Secondly, the optimization objectives combined with the smoothness optimization requirements and the limits of the toolaxisvector are established. Then, the trajectory of the moving axis is generated by integrating the optimized differential vector. At last, a waveform surface machining process is simulated in the VERICUT software with the trajectory generated by the proposed optimization method. To prove the feasibility and superiority of the method, the real part machining experiment is conducted in an A-C type five-axis CNC machine. The experiments verify the smoothness and optimal of the proposed path planning method.
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