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Revealing the relationship among the machining parameters, surface topography, and functionality-related properties of the machined surface is crucial for obtaining micro-milling surfaces with good functional performance. In the present study, slot micro-milling Ti6Al4V was conducted to investigate the effect of machining parameters on the 3D surface topography, with an emphasis on surface defects, the 3D surface texture parameters, and functionality-related properties of the machined surface. The results show that the 3D surface topography of the machined surface presents obvious anisotropy in slot micro-milling Ti6Al4V. The 2D surface profile shows the non-uniformity along the slot width direction in slot micro-milling Ti6Al4V. The surface defects with different machining parameters are various, such as deep and large feed marks of single cutting, narrow and small feed marks of single cutting, feed marks of multi-cutting, scratch marks, scratch pit, surface tearing, tear pit, back-cutting marks, and metal debris. With the consideration of cutting processing efficiency and surface roughness Sa, it is suggested to adopt the high spindle speed and large depth of cut. At the same time, feed per tooth that is near the minimum cutting thickness is recommended to obtain the minimum surface roughness with the balance of chip thickness accumulation effect and chip removal or surface formation. Moreover, the functionality-related properties of the machined surface, e.g. friction or abrasion contact behaviors, load-bearing capacity, fluid retention properties, fatigue performance, and the machining parameter effect were evaluated with surface texture parameters, such as amplitude parameters, spatial parameters, hybrid parameters, and functional or volume parameters. Our findings are of great significance for shedding light on the relationship between the surface formation mechanism, surface topography, and functionality-related properties of machined surfaces in micro-milling Ti6Al4V. [ABSTRACT FROM AUTHOR]

Thin-walled micro parts are widely used in many fields, such as aviation, aerospace, precision engineering, and even micro-molds. Compared with other micro-fabrication technology, micro-milling can be considered as one of the most efficient 3D fabrication techniques. However, due to the vulnerable stiffness of thin-walled micro parts and micro tools, regenerative chatter is prone to occur during the micro-milling process. Severe chatter can lead to large fluctuations in cutting forces, resulting in deterioration of surface roughness/integrity and decreasing in tool life. Therefore, an in-process chatter detection strategy based on the feature extraction of micro-milling forces is proposed in this paper. Micro-milling force signals are measured and processed by advanced algorithms developed. After variational mode decomposition (VMD) for each group of cutting forces, the optimal intrinsic mode function (IMF) is adopted based on the Laplacian score (LS). The multi-scale permutation entropy (MSPE) values of the optimal IMF of each group are calculated, wherein the scale factor s , the embedding dimension m , and the delay time t are obtained by the genetic algorithm (GA). The obtained MSPE values are used as input vectors to train the support vector machine (SVM) classifier, which is used to monitor the stability states of the micro-milling processes. The effectiveness of the proposed strategy is compared with the other classic chatter detection methods and indicators in the micro-milling experiments of thin-walled parts. The results show that the method resulted from the strategy can extract cutting force features effectively and in-process detect chatters accurately in micro-milling thin-walled parts processes. [ABSTRACT FROM AUTHOR]

The effect of titanium-alloying on microstructure and mechanical properties of Fe35Ni35Cr20Mn10 high-entropy alloy (HEA) was studied. The microstructure was characterized by X-ray diffraction, scanning electron microscopy and transmission electron microscopy. The mechanical properties were examined by tensile and hardness tests. After the homogenization treatment at 1000 °C for 12 h, a great amount of thick/thin η flakes are observed to form at the grain boundaries, regularly intersect-arraying with specific directions that form η-locks. It is found that both the thick and thin η-Ni 3 Ti flakes are well coherent with face-centered cubic (FCC) matrix. Ti-alloying makes the homogenized Fe35Ni35Cr20Mn10 HEA possess high yield strength (331 MPa) and excellent ductility (47.2% in elongation), exhibiting a better strength-ductility. The remarkable rise in yield strength is from fine grain strengthening, dislocation hardening and second phase strengthening that are induced by Ti alloying. The refinement of grains induced by Ti alloying, the formation of a number of clear dislocation cells in FCC matrix and many stacking faults in FCC matrix and inside η flakes during the tensile deformation, and especially the coordinated deformation between η flakes and matrix, are thought to be responsible for the excellent ductility. The excellent strength-ductility in homogenized (Fe35Ni35Cr20Mn10) 95.3 Ti 4.7 HEA is, more importantly, due to the formation of regular intersect-arraying of η flakes (η-locks) with specific directions. The thick/thin η flakes are all along keeping the coherent relationship with FCC matrix during the total tensile deformation and hence can coordinately deform with the matrix. • Thick/thin η flakes are regularly intersect-arraying that form η-locks. • The thick/thin η flakes in η-locks are well coherent with FCC matrix. • The prepared HEA exhibits an excellent strength-ductility. • The η flakes keep the coherent relationship with FCC matrix during tensile deformation. • It is found that η flakes can coordinately deform with the matrix. [ABSTRACT FROM AUTHOR]