To investigate the formation mechanism of the white layer on the machined surface during high-speed milling of nickel-based superalloy GH4169, several cutting parameters were selected for milling experiments. Energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), and electron backscattered diffraction (EBSD) were employed to characterize element distribution, phase transformation, and microstructure changes in the machined surface of the superalloy and then reveal the formation mechanism of the white layer on the machined surface. The results show that the white layer appears on the machined surface of GH4169, which is dense and has no obvious structural features. The total amount of elements in the white layer remains unchanged, but the distribution of elements such as C, N, O, Fe, and Ni changes due to phase change. The formation mechanism of the white layer is due to the dynamic recovery and dynamic recrystallization caused by the heat–force coupling effect, which leads to the grain refinement of the material and thus forms the white layer. This investigation can provide theoretical support to improve the service life of the parts in actual machining.

Inconel 718 has excellent thermal and chemical properties and is widely used in the manufacture of aerospace parts; however, there are some problems in the machining of Inconel 718, such as a large milling force, serious tool wear, and poor surface quality. In this research, a type of longitudinal–torsional ultrasonic milling (LTUM) tool is designed based on theoretical computations and FEM simulation analysis. To verify the design rationality of the developed LTUM tool, milling experiments are performed. It is verified that the LTUM tool can realize an elliptical vibration path at the tool tip. The resonance frequency of the tool is 21.32 kHz, the longitudinal amplitude is 6.8 µm, and the torsional amplitude is 1.4 µm. In the milling of Inconel 718, the experimental data of LTUM are compared with those of conventional milling (CM). The comparative experiments show that the LTUM tool can effectively lessen the milling force and tool wear in the milling of Inconel 718, improve the surface quality, inhibit the generation of burrs, and improve the chip breaking ability. The application potential of the LTUM tool in high-performance milling of Inconel 718 parts is proven.

Nodular cast iron QT700-2 is extensively used in automobile engine crankshaft parts due to its prime mechanical properties. The journal of a crankshaft is a curved surface, and traditional wheel grinding easily causes grinding burn and surface and subsurface damage. Shape adaptive grinding (SAG) is a flexible grinding technology, which has the advantages of low grinding force and temperature, and good grinding quality. It is suitable for machining curved surface parts with complex shapes. Therefore, the SAG surface integrity of nodular cast iron QT700-2 was experimentally investigated. The influence of grinding parameters on grinding force, material removal rate, grinding temperature, and surface integrity was studied, and the machining performance of SAG tools was evaluated. It was concluded that the grain size in SAG is the most important factor affecting the grinding force, material removal rate, and surface roughness; the influence of SAG grinding is very weak, mainly removing the workpiece material. Then, the influence law of SAG technology on the surface integrity of nodular cast iron QT700-2 was summarized, and the optimal grinding parameters were obtained, providing a reference for the curved surface grinding of nodular cast iron QT700-2 in the future.

This paper proposes an enhanced numerical integration technique for predicting milling stability. The underlying milling dynamics model incorporates regenerative chatter effects, formulated as a system of linear time-delay differential equations. The computational methodology begins by dividing the tool engagement period into the free vibration and forced vibration intervals, followed by uniform discretization of the forced vibration interval. A numerical integration method is primarily carried out using Simpson’s and Hermite’s rules. Thus, a discrete dynamic mapping that correlates the system’s current state with its previous state is constructed. Based on this, the milling stability is ultimately determined by applying Floquet theory. Furthermore, the mean squared error metric is introduced to quantify the prediction accuracy of stability lobe diagrams. Through comprehensive comparative analyses, the predicted efficiency and accuracy of the proposed method are systematically benchmarked against the conventional approaches. The simulated and experimental results demonstrate that the proposed method achieves high computational efficiency alongside good accuracy, and its engineering practicality is rigorously validated through milling experiments.

Hard machining, as one of the sustainable manufacturing technologies, tends to introduce highly coupled thermomechanical loads into the machined surface layer, which causes materials to suffer from severe plastic deformation underneath and, thus, the alteration of the mechanical properties. In this paper, a systemic investigation was performed on the correlation of processing parameters, plastic deformation, and mechanical properties of machined surface layer for hardened H13 steel, where the cutting parameters and tool micro-geometry are varied. The plastic deformation layer was composed of an amorphous structure and plastically deformed grain. Compared to cutting parameters, edge micro-geometry significantly influences the depth of the plastic deformation layer. The automated ball indentation (ABI) technique was utilized to evaluate the mechanical properties of the machined surface layers. Finally, the relationship between processing parameters, depth of plastic deformation, and mechanical properties was revealed. The experimental findings provide a solid foundation for processing parameter selection to improve the functional performance of manufactured components.