Research on multi-objective optimization design for high-precision turning-milling machine tool bed based on taguchi method -FEA
Year: 2025
Type: article
Abstract: As a high-precision machining equipment, the turning-milling machine tool requires its bed structure the primary load-bearing component to exhibit excellent dynamic and static characteristics that significantly influence machining accuracy and efficiency. To ensure machining precision, this paper proposes a multi-objective collaborative optimization design methodology integrating Finite Element Analysis(FEA) and Taguchi Method. This approach employs FEA technology to obtain the static and dynamic characteristics of the machine tool bed(MTB) structure, followed by multi-objective collaborative optimization using Taguchi Method to achieve comprehensive performance enhancement. Compared with the traditional research methods for optimizing machine tool beds, the FEA technology can handle more complex geometric shapes and boundary conditions, improve the accuracy and reliability of data, and enhance the optimization efficiency through the Taguchi method, achieving multi-objective joint optimization. Comparative analysis demonstrates that the optimized structure achieves 5.14% reduction in maximum deformation, 1.75% decrease in mass, and 1.04% improvement in fourth-order natural frequency. The results validate the effectiveness of this design methodology in achieving efficient MTB optimization for turning-milling machine tools, simultaneously enhancing dynamic-static performance while realizing lightweight design. This research provides valuable references for advancing precision improvement and green manufacturing research in turning-milling machine tools.
Source: Scientific Reports
Authors: Hongyi Wu, Haozhen Li, Xuanyi Wang, Junshou Yang, Runze Jiang, Xiaolei Deng, Jianchen Wang
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W4412659660
