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Research on tool axis vector optimization when face milling complex surfaces

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Abstract

In 5-axis machining, the existing tool’s axis vector optimization 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 vector optimization 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 axis vector 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 axis vector 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 axis vector optimization algorithm is applied to the propeller results. Comparing the tool’s axis vector optimization results to those obtained without optimization, it is discovered that the surface workpiece’s machining quality has significantly increased.

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Data availability

The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

This research is greatly supported by the National Natural Science Foundation of China (No. 51975019).

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Authors and Affiliations

  1. Institute of Advanced Manufacturing and Intelligent Technology, Beijing University of Technology, Beijing, 100124, China

    Pengrui Zhao & Zhixiong Li

  2. Beijing Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing, 100124, China

    Pengrui Zhao & Zirui Cao

  3. Mechanical Industry Key Laboratory of Heavy Machine Tool Digital Design and Testing, Beijing University of Technology, Beijing, 100124, China

    Zhifeng Liu, Zhixiong Li & Zirui Cao

  4. Key Laboratory of CNC Equipment Reliability, Ministry of Education, School of Mechanical and Aerospace Engineering, Jilin University, Changchun, 130015, China

    Zhifeng Liu

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  1. Pengrui Zhao
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  4. Zirui Cao
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Pengrui Zhao and Zirui Cao. The first draft of the manuscript was written by Pengrui Zhao, Zhifeng Liu, and Zhixiong Li, and all authors commented on previous versions of the manuscript. Zhixiong Li is responsible for the performance of data. All authors read and approved the final manuscript.

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Correspondence to Zhifeng Liu.

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Zhao, P., Liu, Z., Li, Z. et al. Research on tool axis vector optimization when face milling complex surfaces. Int J Adv Manuf Technol 128, 5081–5099 (2023). https://doi.org/10.1007/s00170-023-12031-7

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  • DOI: https://doi.org/10.1007/s00170-023-12031-7

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