This paper comprehensively reviews friction stir welding (FSW) as applied to copper and its alloys. FSW is a solid-state joining process that offers significant advantages over traditional fusion welding methods, particularly for materials like copper that are difficult to weld conventionally due to their high thermal conductivity and oxidation issues. Over time, the FSW process has been developed for different industries. Copper structures joined through FSW are utilized for nuclear waste storage, electrical connectors, chemical and petrochemical storage, refrigeration systems, heat exchangers, and the aerospace industry. This covers recent advancements in FSW technology, the geometry of the tools used, the process parameters, and the microstructural characteristics and mechanical properties of the joints. It examines the shapes, sizes, and materials of the tools used for welding copper and its alloys, along with process parameters such as rotational speed and traverse speed, and their influence on the quality of the joints. Additionally, the paper presents syntheses of previously published results, highlighting the values of parameters that indicate the quality of the welds, including grain size, microhardness, mechanical strength, and elongation. The challenges and potential solutions in applying FSW to copper are also discussed, providing a starting point for future research and industrial applications.

Nowadays, FDM technology permits obtaining functional prototypes or even end parts. The process parameters, such as layer thickness, building orientation, fill density, type of support, etc., have great influence on the quality, functionality and behavior of the obtained parts during their lifetime. In this paper, we present a study concerning the possibilities of obtaining certain values for clearance in revolute joints of non-assembly mechanisms manufactured by FDM 3D Printing. To ensure the functioning of the assembly, one must know the relationship between the imposed and measured clearances by taking into account the significant input data. One way is to use the automat learning method with an artificial neuronal network (ANN). The data necessary for the training, testing, and validation of ANN were experimentally obtained, using a complete L 27 Taguchi experimental plan. A total of 27 samples were printed with different values of the following parameters: the infill density, the imposed clearance between the shaft and the hole, and the layer thickness. ANN architecture corresponds to the Hecht–Kolmogorov theorem. Genetic algorithms (GA) were used for the optimization of the output. The Neural Network Toolbox from MATLAB was used for training the network and a hybrid tool genetic algorithm artificial neural network (GA-ANN) was used to minimize the value of the absolute relative clearance (arc). The minimum value of the absolute relative clearance established by GA-ANN was 0.0385788. This value was validated experimentally, with a relative difference of 4%. We also introduced a rational function to approximate the correlation between the input and output parameters. This function fulfills some frontier conditions resulted from practice. In addition, the function may be used to establish the designed clearance in order to obtain an imposed one.

Copper and its alloys have specific properties - electrical and thermal conductivity, ductility, mechanical strength, corrosion resistance - which make it a material used in various industrial applications. However, these materials are difficult to weld by conventional processes due to their high thermal conductivity and high rate of oxidation at temperatures close to melting. To be able to join copper-based materials, friction stir welding seems to be a promising possibility. The quality of the assembly obtained strongly depends on the parameters of the process chosen to generate a temperature close to the optimum value. So, to find these parameters, it is necessary to carry out experimental test campaigns which are generally very expensive in terms of time and equipment. An alternative will be to use the numerical simulations of the FSW process to find the optimal parameters. Numerical simulation contributes also to a better understanding of the influence of input parameters on the phenomena in the process and the connections made. To develop a numerical model, it is necessary to use a constitutive equation that defines the behavior of the material throughout the process. The most commonly constitutive equation used for FSW modeling is Johnson-Cook. The paper describes the strategy of identifying the constants of the material, respectively the method of inverse identification of the parameters. The constants of the thermo-mechanical behavior (both elastic and plastic) are identified by coupling the finite element method with Abaqus and Matlab software. This strategy tries to minimize the quadratic deviation between the response of the model and the experimental tests. Tensile tests were carried out on quasi-pure copper CU-DHP samples, at temperatures of 22°C, and 500°C, for speeds of 3 mm/min and 30 mm/min, respectively. The validation of the model thus identified was carried out on tensile tests at a temperature of 300°C, by comparing the curves obtained with the Johnson-Cook model and those obtained experimentally.

The radial cold rolling process is widely used in industry due to the advantages of chip removing processing. In this study, circular complex profiles were formed by cold-rolling with radial feed, using a patented device with two roller-tools. By achieving several numerical simulations of the radial rolling process, the study aimed to establish the influence that the maximum set force and the diameter of the workpiece have on the productivity of the process and the quality of the formed trapezoidal and metric grooves. The numerical simulations were performed with ABAQUS/Explicit software and by using a previously validated finite element model. The penetration curve of the roller-tools in the material was introduced in the simulation as an analytical function and was determined based on experimental researches. To express the dependency of the penetration curve coefficients on other rolling conditions, a multivariable analysis using a design of experiments technique was performed. The parameters that result from numerical simulations and were analyzed in this study are the profile forming time, the maximum radial force, the distribution of the equivalent strains in the axial section of the profiles, and the profile dimensions. The conclusions that were drawn from the analysis of the results regarding the influence of the set maximum force and the workpiece diameter on the analyzed parameters of the numerical simulations, together with the definition of efficient process criteria, allowed also the identification of the optimal conditions of the rolling process.

Single Point Incremental Forming (SPIF) has emerged as a flexible and cost-effective technique for producing complex sheet metal parts. However, its industrial application is often limited by issues related to surface quality. This study examines the impact of tool geometry on the surface integrity of the AA6061-T6 aluminum alloy. The research novelty lies in the innovative eccentric tool with a variable radius (ETVR), which we compare to two conventional hemispherical tools with radii of 5 mm and 10 mm. Truncated cones were formed under the same process conditions, and their quality was assessed by measuring surface roughness and microhardness along the cone’s generatrix in both the rolling direction and the transverse direction. Additionally, microchip analysis and visual inspections were conducted. The results reveal distinct differences in the surface morphology, evolution of roughness, and distribution of microhardness among the three tools. The SS5 tool produced the highest level of hardening but also resulted in significant surface deterioration. In contrast, the SS10 tool generated smoother surfaces with moderate hardening, while the ETVR tool struck a balance between surface uniformity and enhanced hardness. Statistical analyses, using t-tests, confirmed the significance of these findings. This study offers new insights into tool design for SPIF, highlighting the trade-offs between surface quality and material strengthening.