17-4 PH stainless steel alloy has been widely used in the field of defence industry such as weapon equipment, aerospace, nuclear energy, and so on because of its high strength, high toughness, high temperature resistance, and corrosion resistance. In order to meet the flexible manufacturing requirements of multi-variety small batch complex structure products with lower cost and higher efficiency, selective laser-melted 17-4PH stainless steel alloy has become the focus of research in the field of rapid alloy manufacturing in recent years. In this article, the density characteristics and the distribution characteristics of holes and spheroidization phenomena of 17-4 PH pre-alloyed powder subjected to multidimensional temperature conduction under selective laser melting are studied, and the mechanism of defect generation under temperature conduction is proposed. Finally, the optimal selection of the combination of different process parameters was carried out by orthogonal test, and it was found that the comprehensive mechanical behaviour of the 17-4 PH stainless steel alloy after being formed exceeded the ASTM A564 standard (the yield strength is 1,132 MPa, the tensile strength is 1,323 MPa, and the elongation is 16.6%).

Deep and narrow groove structures are widely used in aviation, aerospace, weapons, and other industries, and play a very important role. In order to solve the problems of machining tool deformation, machining flying edge, burr in traditional Computerized Numerical Control (CNC) milling for deep and narrow grooves, and the problems of serious motor loss and low machining efficiency in non-contact electrical discharge machining (EDM), electrochemical mask machining through the mask treatment of the non-processed part mask processing, and with no loss of the processing cathode tool, was suggested as an efficient way to solve these problems. Considering that the corrosion removal of the anodic workpiece is mainly subject to the multi-physical field coupling action between the electric field, the flow field, and the temperature field, it is necessary to construct a multi-physical field coupling model of electrochemical mask machining and combine this with the numerical simulation analysis to realize the distribution state of the multi-physical field, so as to realize the optimization guidance of the overall processing process.

As the aero-engine blade surface is a typical representative of a free-form surface, its sampling and reconstruction accuracy directly determines the evaluation and correction of subsequent processing technology. In this study, based on a case study of a small engine rotor blade, the blade surface (including concave and convex variations) was divided into thick rectangular meshes based on the idea of mesh subdivision, and the rectangular meshes were refined into primary triangular meshes by Delaunay triangulation. Second, the local Gaussian curvature of the vertices of each primary refined triangle mesh was estimated by combining the Moreton-Sequin method. Then, according to the curvature change in the two connected sampling points on the edge of each primary refined triangle, the adaptive sampling point interpolation along with the curvature change on the boundary of the original triangulation triangle and the densified sampling point distribution, which satisfies the idealized triangulation requirement, were further realized. This approach happens through continuous iteration by introducing a curvature relaxation factor and a greedy algorithm. This method can be used to adaptively adjust the distribution and number of sampling points according to the change in the geometric characteristics of the free-form surface and the curvature distribution of each part. The comparison between this method and the mainstream equidistant sampling method in the blind sampling method and the recent mainstream adaptive sampling method, which uses biquartic B-spline curves, demonstrates that the method proposed in this study can accurately and efficiently represent the complex special-shaped free-form surface in blade free-form surfaces with the fewest sampling points while achieving the highest sampling efficiency and the highest model reconstruction precision. Graphical Abstract

To address the problems of serious tool loss and the easy deformation of aero-rotor blade profiles in NC milling technology, electrochemical machining can realize the processing of complex, specially structured products with advanced materials such as nickel alloy Inconel®718 by means of a non-contact electrochemical etching process. In this paper, by analysing the electrochemical reaction state of Inconel®718 alloy in vertical electrolytic processing, the electrolyte side flow of aero-blade electrochemical machining technology is innovatively transplanted to the traditional vertical single-axis feed machining tool, and the corresponding optimized flow channel structure that combines the characteristics of positive flow mode and side flow mode are proposed. Then, the verification test shows that the vertical machining of aero-blade with the characteristics of positive flow and side flow of electrolyte has high machining quality, and its surface error is in the range of 0.02–0.12 mm (the average surface error can reach 0.07 mm), the corresponding surface roughness is 1.16 µm. Therefore, the research foundation and technical potential are laid for the vertical electrochemical machining of the aero-rotor blades.

In order to solve the problem of high cost and long cycle in the process of traditional subtractive material manufacturing of a complex‐shaped mould, the technology of FDM rapid prototyping is used in combination with the global service idea of cloud manufacturing, where the information of various kinds of heterogeneous‐forming process data produced in the process of FDM rapid prototyping is analysed. Meanwhile, the transfer and transformation relation of each forming process data information in the rapid manufacturing process with the digital model as the core is clarified, so that the FDM rapid manufacturing process is integrated into one, thus forming a digital and intelligent manufacturing system for a complex‐shaped mould based on the cloud manufacturing big data management. This paper takes the investment casting mould of a spur gear as an example. Through research on the forming mechanism of jet wire, the factors affecting forming quality and efficiency is analysed from three stages: the pretreatment of the 3D model, the rapid prototyping, and the postprocessing of the forming parts. The relationship between the forming parameters and the craft quality is thus established, and the optimization schemes at each stage of this process are put forward through the study on the forming mechanism of jet wire. Through a rapid prototyping test, it is shown that the spur face gear master mould based on this technology can be quickly manufactured with a critical surface accuracy within a range of 0.036 mm–0.181 mm and a surface roughness within the range of 0.007–0.01 μm by only 1/3 the processing cycle of traditional subtractive material manufacturing. It lays a solid foundation for rapid intelligent manufacturing of products with a complex‐shaped structure.