Alsoufi Mohammad S
Department of Mechanical Engineering, College of Engineering and Architecture, Umm Al-Qura University, Makkah 21955, Saudi Arabia.
Materials (Basel). 2025 Jun 22;18(13):2952. doi: 10.3390/ma18132952.
This study proposes a dual-statistical and gradient-based framework to evaluate the machinability of five engineering alloys under CNC turning. Cutting force and surface deformation were measured across five machining zones. Finite difference-based gradients revealed spatial variations in material response. Stainless Steel 304 showed the highest cutting force (328 N), while Aluminum 6061 had the highest deformation (0.0164 mm). Carbon Steel 1020 exhibited the highest force-to-deformation efficiency (>97,000 N/mm). Arithmetic and harmonic means highlighted statistical sensitivities, while principal component analysis (PCA) identified clustering among materials and reduced dimensionality. A composite machinability score, integrating stiffness variation, efficiency gradients, and multivariate features, ranked Aluminum 6061 highest, followed by Brass C26000 and Bronze C51000. This methodology enables interpretable benchmarking and informed material selection in precision manufacturing.
本研究提出了一种基于双统计和梯度的框架，以评估五种工程合金在数控车削加工中的可加工性。在五个加工区域测量了切削力和表面变形。基于有限差分的梯度揭示了材料响应的空间变化。304不锈钢的切削力最高（328 N），而6061铝的变形最大（0.0164 mm）。1020碳钢表现出最高的力变形效率（>97,000 N/mm）。算术平均值和调和平均值突出了统计敏感性，而主成分分析（PCA）确定了材料之间的聚类并降低了维度。一个综合了刚度变化、效率梯度和多变量特征的复合可加工性得分，将6061铝排在首位，其次是C26000黄铜和C51000青铜。这种方法能够在精密制造中进行可解释的基准测试和明智的材料选择。
