Three-dimensional printing, or additive manufacturing, represents one of the fastest growing branches of the industry, and fused deposition modeling (FDM) is one of most frequently used technologies. Three-dimensional printing does not provide high-quality surfaces, so finishing is required, and milling is one of the best methods for improving surface quality. The combination of 3D printing and traditional manufacturing technologies is known as hybrid manufacturing. In order to improve quality and determine optimal machining parameters, researchers increasingly use artificial intelligence methods. In the context of manufacturing technologies, both multiple regression analysis (MRA) and artificial neural networks (ANNs) have proven to be highly reliable in predicting and optimizing machining processes. This study focuses on the use of MRA and an ANN to analyze the influence of machining parameters such as feed rate, depth of cut, and spindle speed on the surface roughness of a 3D-printed part in a milling process. The study compares the measured results with the outcomes obtained through MRA and the ANN to assess their effectiveness in predicting and optimizing surface roughness. The results show that higher accuracy was obtained from the ANN method.

In modern material processing industries, the constant need for increased efficiency and precision drives ongoing research aimed at optimizing technological parameters. The presented study aims to analyze excessive wear and chipping of gun drills during the deep drilling process of 24CrMoV5-5 steel. The experiment was conducted on a horizontal deep drilling machine, model T30-2-500 (TBT Tiefbohrtechnik GmbH+Co), under real production conditions. The investigation included the performance analysis of both factory-reground and subsequently reground drills, with the number of tests enabling a detailed comparison across different process regimes. The process parameters were systematically varied in three phases, with a focus on increasing the coolant pressure from 50 to 60 bar, while other conditions, such as spindle speed and feed rate, remained constant. The results indicate that increasing coolant pressure allows for more efficient cooling, stabilization of temperature fluctuations in the cutting zone, and improved chip evacuation, directly leading to reduced chipping and more uniform tool wear. Consequently, this extends the service life of the drills and preserves the high precision of the machined surface. The obtained results provide valuable guidelines for optimizing deep drilling parameters, highlighting the importance of properly adjusted cooling conditions in industrial machining. Future research will focus on integrating additional processes, including variations in cutting speed, the application of different cooling techniques, and the implementation of intelligent tool condition monitoring systems, aiming to achieve an optimal balance between process efficiency and tool longevity.

This paper investigates the influence of layer height, one of the key parameters in Fused Deposition Modeling (FDM) 3D printing, on the surface roughness of parts manufactured using PETG (Polyethylene Terephthalate Glycol) material. Specimens were printed with different layer heights (0.1 mm, 0.2 mm, and 0.3 mm) under identical printing conditions to evaluate how this parameter affects surface quality. Surface roughness (Ra) was measured using a profilometer, and the results indicate that increased layer height leads to higher surface roughness values, resulting in a rougher surface finish. The findings highlight the importance of selecting an appropriate layer height to achieve the desired surface quality, particularly in applications where aesthetics or functional surface characteristics are critical. This study contributes to the optimization of PETG 3D printing processes in contexts where surface finish is of particular importance.

This paper presents an experimental procedure for the automatic detection and quantitative evaluation of surface wear on drills used in deep hole drilling processes. The analysis was based on images of the cutting edge captured by an industrial camera under controlled conditions, with a particular focus on the curved edge segment, which is especially prone to wear. A custom image processing algorithm was developed within the MATLAB programming environment, employing a multi-stage approach—preprocessing, surface condition classification, and distance analysis of worn zones from the curved edge—to calculate VB_mean as an indicator of wear severity. The algorithm successfully distinguishes between healthy regions, grinding marks, mechanical damage, and active wear, significantly reducing the risk of misinterpretation. Quantitative analysis performed on a dataset of 50 samples demonstrated repeatability of the results and potential for further industrial application. The observed wear patterns may serve as a basis for optimizing process parameters and implementing predictive maintenance strategies. The proposed methodology represents a step toward automated tool condition monitoring under demanding machining conditions, with the potential for integration into broader technical diagnostics systems

The paper presents a numerical analysis, using the finite element method, for the case of static and dynamic loading of the upper carriage of the remote-controlled combat station, due to the recoil force generated by the operation of the integrated automatic grenade launcher 30mm M93. The paper describes the problem of integrating the BGA 30mm M93 automatic grenade launcher onto the combat platform, and based on the dimensions of the automatic launcher, modeling of the automatic launcher stand with cradle was carried out. As a result of the weapon dynamics equations and internal ballistics calculations, the pressure force of the gunpowder gases and the recoil force of the automatic grenade launcher were calculated. The paper also presents the results of the dynamic analysis of the finite element model of the upper gun carriage loaded with the obtained impulse recoil force for different elevation angles of the weapon.

The ZA-27 alloy belongs to the group of zinc– aluminium alloys, which are well known for their high strength and wear resistance, good dimensional stability, and relatively low cost compared to other materials with similar technical and operational characteristics. Composites such as ZA-27+Al₂O₃+SiC are increasingly applied in technical and tribo-mechanical systems. These alloys have found wide application in mechanical engineering and transportation, particularly in the automotive industry for brake components, engine parts, and steering systems, as well as in aerospace applications and machine tools, where elements are exposed to increased friction and wear. By combining ZA-27 with reinforcements such as Al₂O₃ (aluminium oxide) and SiC (silicon carbide), composites with exceptional properties are obtained. Al₂O₃ is used as a reinforcement in composites due to its high hardness and wear resistance. This material significantly improves the mechanical properties of the composite, such as strength, impact resistance, and abrasion resistance. SiC is an extremely hard substance with high heat and wear resistance. When combined with ZA-27, SiC contributes to the composite’s thermal stability and provides additional mechanical durability. Numerous studies and research papers highlight the advantages of these alloys in practical applications compared to many other materials. The focus of this study is not on comparing ZA-27 alloys with other materials, but rather on examining the ZA-27 alloy with reinforcements, specifically how SiC- and Al₂O₃- based reinforcements influence the coefficient of friction and penetration force during experiments. The tribological properties of materials are influenced by several factors, including applied load, sliding speed, lubrication conditions and type of lubricant, as well as the surrounding environment in which the experiment is conducted. In the case of composites with reinforcements, the percentage of reinforcement also plays a key role. However, an increased reinforcement content does not necessarily guarantee improved properties; instead, the characteristics also depend on the fabrication method and the degree of homogeneity achieved. A more uniform microstructure ensures consistent performance across the entire surface. Research findings have shown a significant reduction in the coefficient of friction for reinforced materials compared to the base alloy. Optimal results were obtained under a load of 20 N (load range: 20–80 N) and a sliding speed of 1 m/s (speed range: 1–2 m/s), where minimal wear and the lowest coefficient of friction were recorded. Notably, the best results were achieved with a 5% reinforcement content, with variations tested between 1% and 5%. The fabrication method also significantly affects the properties of such composites. These materials are most commonly produced by either sintering or compo-casting. Increasing the sintering temperature has been found to reduce wear and improve friction resistance, highlighting the potential for application of these materials in demanding industrial environments. The results confirm that high-temperature sintering substantially enhances the tribological properties of the material. These findings may be of great importance for the development of new materials in engineering and manufacturing, where wear resistance is critical. Several studies hypothesize that the addition of SiC and graphite enhances the wear resistance of composites under dry sliding conditions, since these solid particles can reduce friction and wear compared to unreinforced ZA27 alloy. Experimental results confirm that composites reinforced with SiC and graphite exhibit significantly reduced wear compared to the base ZA27 alloy, thereby supporting the hypothesis regarding improved tribological properties. This analysis highlights the potential of ZA27/SiC/Graphite composites for industrial applications in environments where wear resistance is critical. Another important finding is that composites containing graphite demonstrated much better results than those without, as graphite acted as a solid lubricant. In addition to dry sliding tests, investigations including lubrication with oil at the contact interface have also been carried out. These results confirm the positive influence of nano-graphite on the tribological performance of ZA27 alloys under lubricated conditions, opening new opportunities for industrial applications. Furthermore, results have shown that the strength and hardness of aluminium alloys increase with the addition of Al₂O₃, while the wear rate decreases. This emphasizes the role of Al₂O₃ as a reinforcement in aluminium-based composites, which may be highly relevant for the development of more efficient braking systems in the automotive industry.