A Dual-Mean Statistical and Multivariate Framework for Machinability Evaluation in CNC Turning: Gradient and Stiffness Analysis Across Five Materials

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.