Three different and very small amounts of alumina (0.2, 0.3 and 0.5 wt. %) in two sizes (approx. 25 and 100 nm) were used to enhance the wear characteristics of ZA-27 alloy-based nanocomposites. Production was realised through mechanical alloying in pre-processing and compocasting processes. Wear tests were under lubricated sliding conditions on a block-on-disc tribometer, at two sliding speeds (0.25 and 1 m/s), two normal loads (40 and 100 N) and a sliding distance of 1000 m. Experimental results were analysed by applying the response surface methodology (RSM) and a suitable mathematical model for the wear rate of tested nanocomposites was developed. Appropriate wear maps were constructed and the wear mechanism is discussed in this paper. The accuracy of the prediction was evaluated with the use of an artificial neural network (ANN). The architecture of the used ANN was 4-5-1 and the obtained overall regression coefficient was 0.98729. The comparison of the predicting methods showed that ANN is more efficient in predicting wear.

The nickel (Ni) coatings without and with embedded (5–7 vol. %) cubic boron nitride (c-BN) nanoparticles (10 nm in diameter) were deposited on carbon steel substrate by an electroless plating process. Coatings were tested in as-deposited and heat-treated (heating at 300 °C for 6 h) conditions. Coating structure characterisation was performed, as well as hardness and roughness measurements. Friction properties were tested in dry and in water (seawater) lubricated contact conditions, with bronze as a counter-body material. Both static and kinetic coefficients of friction were measured for two different surface texture preparations (initial and working). The first surface texture simulated the running-in condition, and the second surface texture represented the steady-state conditions. The enhancement of the abrasive and erosive wear resistance of heat-treated electroless Ni coatings with embedded c-BN nanoparticles was already proved in our previous studies. This study aims to investigate those influences on friction properties of electroless Ni coatings in different sliding conditions. The results show that the coefficients of friction did not differ too much between the coatings and that the surface roughness and presence of seawater had a much stronger influence.

Despite the surge in plasma nitriding research, few reviews thoroughly examine how surface decarburization—occurring both before and during the treatment—affects AISI 4140 and similar steel grades. This review addresses that shortfall by providing an investigation into the decarburization process and its consequences. It compiles essential findings from prior studies, demonstrating instances of decarburization in both plasma-free and plasma-containing environments. Furthermore, this analysis explores strategies to prevent decarburization and assesses its significant impact on the steel’s microstructure, hardness, corrosion resistance, and wear properties in surface and near-surface regions. Moreover, this study proposes directions for future research, emphasizing the necessity for a more detailed understanding of the decarburization mechanisms and their influence on the properties of plasma-nitrided steels.

In the paper are presents new solutions regarding milling strategies who increase the efficiency of machine tools with numerical control. To the modern machine tool solutions, new assisted programming methods have been joined to achieve better processing time and the accuracy of processed surfaces. Was underline the ability to manufacturing a special part, dedicate for aerospace area, using a modern milling strategy: adaptive milling strategy. Technological solutions who were presented, modality how was used the existed infrastructure: CNC milling centre in three axis, are the personal results of the authors, results that could be implement for different technological applications.

Complex parts require specific processing. Computer aided manufacturing solutions make their mark and optimize the manufacturing process. Different CAM software’s have different philosophy with different capabilities. TEBIS CAM software brings more facilities and opportunities to manufacturing a complex part. In the paper was presented this capability on real part. It was made the comparison between two different milling strategies: one classical milling strategy-Contour parallel strategy, versus adaptive milling strategy. Was presented the way how was implement the TEBIS CAM software and the results of manufacturing. The time of manufacturing was significantly reduced with 43% using the adaptive milling strategy and the surface accuracy was improved.

The paper present solutions to optimize the NC program. Using the original NC program, keep the technology with the same cutting tools, the results give us less time of manufacturing with more protection to collisions. The use of new softer with real capabilities solution to manage and optimize the CNC technologies.