Jia Haili, Xiong Wu, Wang Aimin, Wu Long
Tianjin High-End Intelligent Machine Tool Engineering Research Center, Tianjin University of Technology and Education, Tianjin 300222, China.
School of Mechanical Engineering, Beijng Institute of Technology, Beijng 100081, China.
Materials (Basel). 2025 Aug 15;18(16):3836. doi: 10.3390/ma18163836.
The 7075-T7451 aluminum alloy, widely used in aerospace, aviation, and automotive fields for critical load-bearing components due to its excellent mechanical properties, suffers from residual stresses induced by thermo-mechanical coupling during milling, which deteriorate workpiece performance. This study explores how key milling parameters-spindle speed n, feed per tooth f, cutting depth a, and cutting width a-affect surface residual stress and cutting force via orthogonal experiments and finite element analysis (FEA). Results show a is critical for X-direction residual stresses, while f dominates Y-direction ones. Cutting force increases with f, a, and a but decreases with higher n. Multivariate regression-based prediction models for residual stress and cutting force were established, which effectively characterize parameter-response relationships with maximum prediction errors of 18.69% (residual stress) and 12.27% (cutting force), showing good engineering applicability. The findings provide theoretical and experimental foundations for multi-parameter optimization in aluminum alloy milling and residual stress/cutting force control, with satisfactory practical effectiveness.
7075-T7451铝合金因其优异的机械性能而广泛应用于航空航天、航空和汽车领域的关键承重部件，但在铣削过程中会因热机械耦合产生残余应力，从而降低工件性能。本研究通过正交试验和有限元分析（FEA），探讨了关键铣削参数——主轴转速n、每齿进给量f、切削深度a和切削宽度a——如何影响表面残余应力和切削力。结果表明，a对X方向残余应力至关重要，而f对Y方向残余应力起主导作用。切削力随f、a和a的增加而增大，但随n的增大而减小。建立了基于多元回归的残余应力和切削力预测模型，有效地表征了参数与响应之间的关系，最大预测误差分别为18.69%（残余应力）和12.27%（切削力），具有良好的工程适用性。研究结果为铝合金铣削中的多参数优化以及残余应力/切削力控制提供了理论和实验基础，具有令人满意的实际效果。
