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In this study, the microstructure of surface layers with varying roughness (Ra parameters) was analyzed using scanning electron microscopy (SEM) to optimize tribological properties in engineering design. SEM revealed key microstructural features – sharp and mild protrusions, pitting, microcracks and contaminants – that were not available in traditional profilometry. Reducing the Ra value improved surface uniformity by reducing irregularities and defect lengths, which had a positive effect on tribological properties and surface durability. However, defects were still present even at Ra < 1.25 μm, indicating the "Law of Microstructural Roughness," which emphasizes the inevitability of surface irregularities despite minimizing roughness. The integration of SEM results with profilometric methods enabled comprehensive identification and assessment of defects, combining microstructure with tribological properties. Results suggest that controlled roughness is key in combining materials and optimizing functional surfaces, particularly in the aerospace, biomedical and automotive industries, where reliability under demanding operating conditions is a priority.

To enhance the accuracy of fault diagnosis (FD) in motor rotor systems, this study introduces a novel method that leverages feature extraction (FE) combined with a CNN-BiGRU-Attention deep learning model. Initially, the time-domain features of the vibration signals are extracted using Variational Mode Decomposition (VMD), which also effectively denoises the data. Subsequently, the frequency-domain features of the vibration signals are extracted via Fast Fourier Transform (FFT). The aggregated features are then fed into the CNN-BiGRU-Attention model to perform fault classification. In this model, the Convolutional Neural Network (CNN) module extracts local spatial features, the Bidirectional Gated Recurrent Unit (BiGRU) module models the temporal dependencies, and the Attention mechanism enhances the focus on critical fault information, thereby improving the model's classification performance. Experimental results demonstrate that the proposed FD method achieves an accuracy of 99.58%. Compared to other commonly used models, the performance metrics of our model show significant advantages and superior performance.

Non-destructive stress measurement techniques are extremely important and are still being developed in engineering research and diagnostics of materials. They allow for a quick assessment of their condition without damaging the structure. Their development is crucial for the safety of structures and extending the life of materials. One of the new methods is the measurement of stress using the Barkhausen effect. The MagStress 5d device was used for the tests. In this work, stress measurements were performed using the MagStress 5D device during three-point bending of a steel flat bar. The results were verified using resistance strain gauges and numerical simulation was performed in the Abaqus program. The measurements indicate that the MagStress 5d device using the Barkhausen effect can serve as a complete alternative to traditional extensometers. The results provided by the introduced method showed very good agreement with the latter.

The optimization of process parameters plays a critical role in controlling temperature and velocity fields during centrifugal casting, which is essential for mitigating shrinkage porosity defects caused by uneven cooling in thick walled bearing alloy layers. In this study, two sequential numerical models were devel-oped using ProCAST software to simulate gravity filling and centrifugal solidification stages. The effects of key parameters, including inlet cross-sectional area and centrifugal rotational speed, on flow field characteristics were systematically analyzed. By using an orthogonal experimental design, we deter-mined the optimal parameters: a melt temperature of 440 °C for the Babbitt alloy, an initial temperature of 280 °C for the bearing blank, a filling inlet diameter of 16 mm, and a rotational speed of 340 r/min. Bearing alloy layers manufactured according to these optimized parameters exhibit no evident shrinkage or cracks on their surfaces. The high quality finished products meet the design requirements, thereby validating the accuracy of the numerical simulation.

Tree-like branched Al-Al₂Cu heterogeneous nanostructures with a high surface area ratio were successfully fabricated using magnetron sputtering of Al matrix and Cu nanoparticles, followed by in situ annealing. The method enables precise control over the composition and morphology of the nanosized columnar Al₂Cu phase grown on the substrate and embedded in the Al matrix. The formation of Al₂Cu begins at the initial locations of sputtered Cu nanoparticles. Further annealing promotes their coalescence and coarsening. Orientation relationships examined in several Al₂Cu particles revealed a semi-coherency with the Al matrix. The high surface area and tunable composition highlight the potential of these nanostructures for advanced battery anodes, with tailored geometry achieved through controlled processing conditions.

The polyamide PA6 composites reinforced with carbon fibres (CF) are widely studied due to their properties and their high strength to weight ratio. Good adhesion between a filler and a matrix is es-sential for enhancing properties of a resulting composite. This study investigates the effect of the short CF content and the used CF treatment on mechanical properties of the PA6-CF composites. The composites were subjected to tensile, flexural, compression, hardness and Charpy tests as well as dynamical mechanical analysis. An atomic force microscopy was employed to investigate topography of the CF and the composites. Initially, the properties of the composites were improved through the oxidation of the CF in HNO₃. Subsequently, to further enhance these properties, the oxidized CF were grafted with nano-SiO₂. The CF content in the tested composites varied from 10 wt% to 60 wt%. The most significant improvement of the tested properties was observed at the CF content of 40 wt%.

The present work was aimed at studying the effect of a “Slab/Sheet” thickness ratio (SSTR) on the microstructure and mechanical properties of API 5L X70 steel sheets intended for heavy-wall oil/gas pipelines. The 25 mm-thick and 40 mm-thick steel sheets were rolled from the cast slabs of different thicknesses (250 mm and 300 mm) and their mechanical properties were compared. The sheets were subjected to thermo-mechanical controlled processing followed by accelerating cooling, resulting in the structure of quasi-polygonal/acicular ferrite with minor amounts of granular pearlite and martensite-austenite constituents. Increasing the cast slab thickness significantly improved the ductility and low-temperature impact toughness of steel sheets regardless of their thickness. Specifically, a total elongation increased by 3-6 points (up to 26-28 %); an absorbed impact energy (tested at –20 °C) – in 1.5-1.8 times (up to 300-370 J); the DWTT shear area (at –20 °C) – in 1.6-2.1 times (up to 81-91.7 %). The properties advancement under SSTR increase was associated with an additional refinement of ferrite grains and better homogenization of cast structure under deeper hot deformation.

In order to solve the problem of heterogeneous deformation in the rolling process of 10Ni5CrMoV heavy plate, the effects of uniform temperature rolling (UTR) and graded temperature rolling (GTR) on the microstructure and deformation uniformity of 10Ni5CrMoV steel were studied by means of numerical simulation and verification experiment, and the strengthening mechanism of high permeability rolling process on the rolling deformation of 10Ni5CrMoV heavy steel was clarified. The results show that compared with the uniform temperature rolling process(UTR), different gradient temperature rolling processes (GTR) make the deformation area gradually expand to the core, and the deformation of the core increases significantly. The reduction rate of the first pass gradient temperature rolling processes (FGTR) is about 2.3% higher than that of uniform temperature rolling, and that of continuous gradient temperature rolling (CGTR) is about 5.3% higher than that of uniform temperature rolling. At the same time, the microstructure difference of the core surface is reduced, which is conducive to improving the uniformity of microstructure and properties. At the same time, the microstructure of the core in the rolled is uniformly refined, and the effect is significant.

Fused silica is a key material for high-precision applications such as micro-optics and microfluidics. One route to improving direct laser writing (DLW) of fused silica is the use of shorter laser wavelengths, which enable tighter focusing and enhanced absorption. In this study, the influence of process parameters on surface quality and material removal during DLW using a deep ultraviolet (DUV) ultrafast laser (257 nm, 1 ps) was investigated. A full-factorial design of the experiment was used to identify conditions that optimise both surface quality and ablation efficiency. Surface roughness as low as Sa ≈ 200 nm and material removal rates up to 0.048 mm³∙min-1 were achieved. Conditions that led to surface degradation were also identified. Finally, the optimised parameters were applied to fabricate a microfluidic demonstrator. These results confirm that DUV ultrafast DLW is a powerful technique for fabricating high-fidelity features in fused silica with exceptional precision and quality that can be used for micro-optics or microfluidics devices.

Monitoring and diagnostics of cutting tools are crucial for ensuring production efficiency and product quality in the machining industry. This study uses acoustic emission (AE) to non-invasively detect damage and monitor tool condition in real time. Experiments assessed cutting inserts in a milling head, both used and new. Results showed AE effectively diagnoses tool wear, with significant differences in signals from worn and new inserts. Fast Fourier Transform (FFT) analysis determined the frequency range of signals during machining, confirming AE's usefulness. Microscope verification supported the AE findings on tool wear. This research highlights AE's potential in non-destructive diagnostics, enhancing production efficiency and product quality

Externally toothed components have a very crucial and essential role in all areas of production and manufacturing because they function as away of transmitting motion, energy, and power in all indus-trial applications, such asmodes of transportation, aviation, aerospace, equipment, and operating machines like lathes and milling. All machines have a gear box. Therefore, it is receiving increasing attention. This research presents a new multi-stage rotary ballizing technology for producing toothed parts in one stroke. This process has been investigated experimentally. The parameters that were ex-amined experimentally was at the optimal conditions for single stage ballizing were: die rotation speed of 315 rpm; Axial feed rate, 0.13, mm/rev; The interference (cross in-feed) between the balls and the tubular specimen of 5.5 and 6.5 mm is formed by three stages of ball forming of graduated outer diameters and fixed on a single mandrel; Initial tube thickness is 7 and 8 mm. The effect of these parameters on the forming load, filling ratio and quality of the formed part was studied. The finding sindicated that the seideal variables influence the forming load, tooth filling proportion, and product quality. Experimental results proved the success of this novel technique to form toothed tubular components

This study focuses on addressing the challenges faced by individuals with physical disabilities, particu-larly lower body impairments, by developing a stump socket using Reverse Engineering (RE), 3D Printing, and QFD. The integration of these three methods is something new in product design devel-opment, especially prosthetic products. The research adopted a three-step methodology: 3D scanning the stump, obtaining precise measurements, and fabricating a stump socket using fused deposition modeling (FDM) technology. QFD will produce technical requirements (TR) derived from consumer needs and brainstorming with prosthetists. TR will be the basis for developing the socket design in the 3D Scanning phase. The scanning process utilized Polycam, and the 3D models were refined with Meshmixer. The socket was fabricated using PLA+ material to ensure cost efficiency and customiza-bility. Experimental results demonstrated the accuracy and feasibility of the designed prosthetic sock-et, with a layer thickness of 0.2 mm and printing temperatures up to 215°C. The study highlights the potential of RE and 3D Printing to address the unique anthropometric variations of Indonesian users, overcome the limitations of conventional crutches, and reduce production costs compared to imported prostheses. This approach demonstrates a scalable and innovative solution to improve accessibility and quality of life for individuals with physical disabilities while contributing to economic inclusivity.

Additive technologies are becoming a common part of not only prototype production, but also piece or small series production. However, the choice of technology and material plays a key role in the applicability of the manufactured parts. The most widespread type of additive technology is FFF technology, which consists of applying a fused plastic string in single layers. The resulting mechanical properties of parts produced using this technology depend not only on the material and structure selected, but also on the process parameters used in the printing process itself. This study deals with the production of filament from PLA, which is the primary material. The advantage is its environmental degradability after the end of the life cycle of PLA products. However, the resulting properties of the printed parts may depend on the way the filament is prepared and in particular on the melt temperature during filament extrusion. This study investigates the effect of the produced filaments on the quality of printed parts. It has been shown that the filament production technology has a significant effect on the quality of printed parts.

longitudinal externally splined parts have garnered increasing attention due to their critical role in power transmission across various industrial applications. This study explores the use of the internally rotating ballizing technique for manufacturing these components. The process was analyzed both experimentally and numerically through a mathematical model. The experimental investigation focused on key process parameters, including die rotational speed (50, 63, 80, 100, 125, 160, 200, 250, and 315 rpm), axial feed rate (0.13, 0.15, 0.18, and 0.21 mm/rev), interference between the balls and the tubular sample (cross in-feed: 2.5, 3.5, 4.5 and 5.5 mm), and initial tube thickness (4, 5, 6 and 7 mm). The study assessed the influence of these variables on the forming load and the quality of the produced longitudinal externally splined sleeves. A numerical model was developed to predict forming loads, and the findings indicated that these parameters significantly affect both (forming load and filling ratio). The optimal values for these variables were identified, and the numerical results showed a strong correlation with experimental findings. Keywords: Externally Splined Sleeves, rotary Ballizing Process, Numerical method, Experimental Study and forming load.

As part of my research work, in its practical part, I deal with the selection of suitable 3D printing pa-rameters for parts of a robotic kit, as well as the selection of a 3D printer and the determination of a set of experimental measurements and testing in order to obtain the necessary data to determine a suitable filament material for 3D printing of a part of a robotic kit and setting the appropriate 3D printing parameters to obtain the desired mechanical properties of the parts while maintaining the economic benefits of 3D printing. The main aspects for choosing a filament material are printability in primary and secondary school conditions, easy printing (beginner level), minimal postprocessing, adequate mechanical properties – these are obtained by experimental measurement and correspon-ding destructive tests on a real part from the VEX GO and IQ kit.

Additive manufacturing (AM) is rapidly developing with emerging technology of wire arc additive manufacturing (WAAM) process due to its ability to manufacture large components and high deposition rate. However, WAAM faces mechanical properties problems like porosity, distortion, and strength due to the large heat affected zone (HAZ) from commonly used heat sources such as metal inert gas (MIG) and tungsten inert gas (TIG). Utilization of micro plasma as the heat source should reduce this problem since it has a smaller heat source diameter. Therefore, this study investigates the thermal distribution of micro plasma wire arc additive manufacturing (MPWAAM) by developing a finite element method (FEM) model. This paper focuses on the fabrication of single-layer multitrack deposition and tool path planning of multi-layer multitrack depositions by MPWAAM process. The melt pool size and peak temperature are mainly governed by heat input per unit travel speed of the worktable, with current and voltage being the significant factors. Besides, tool path planning strategy influences the properties and quality of the final product, where parallel tool path design with longer interlayer cooling time minimized part distortion and residual stresses.

In this study, binary zinc-based alloys (Zn–1Mg, Zn–1Li, Zn–2Mn, wt.%) were synthesized by performing mechanical alloying (MA) of elemental powders, followed by consolidation using spark plasma sintering (SPS). The processing parameters were optimized to obtain homogeneous powders with controlled particle size. X-ray diffraction and SEM analyses confirmed the presence of secondary intermetallic phases (Mg2Zn11, Zn13Mn, ZnLi2 phases) formed during milling, which were preserved after SPS. Microstructural examination revealed a fine-grained microstructure with residual oxide networks originating from powder surfaces. Mechanical testing demonstrated significant strengthening effects after Mg and Li additions, with Zn–1Mg alloy reaching the highest hardness (128 HV1) and compressive strength (526.7 MPa), attributed to uniformly distributed Mg2Zn11 precipitates. However, this strengthening was accompanied by reduced ductility. Zn–1Li exhibited the most balanced combination of strength and plasticity, while Zn–2Mn provided only a limited improvement over pure zinc. These results confirm that mechanical alloying combined with SPS is a promising route for developing biodegradable Zn-based biomaterials with enhanced properties.

This paper proposes a solution not previously used in the forging industry, which aims to reduce the proportion of arduous human labour. The concept of a prototype robotic station for hot forging includes a system that allows the selection of batch material with its heating, the execution of the process of lu-brication of forging tools and the forging itself, synchronised with the feeding and removal of material using full automation, in accordance with the idea of Industry 4.0. At the same time, by increasing the repeatability of the entire forging process and changing some of its key parameters, it will be possible to influence the durability of the tools used during its implementation. In order to verify the impact of such a modified technological process on forging tool life, computer simulations of forging were performed, where the currently applied technology using hand forging was compared with a conceptual automated process.

The high-entropy alloy with the composition Al0.8FeCoNiCrCu0.5Si0.2 was produced through a pro-cess in-volving a vacuum arc melting method. Comprehensive characterization was performed through techniques such as XRD, SEM, and TEM. The findings revealed that the alloy primarily con-sists of Fe-Cr and Al-Ni phases, displaying predominantly two body-centered cubic structures. The alloy exhibited a characteristic dendritic cast structure. The alloy predominantly has high-angle grain boundaries accounting for 96.1%. Its grains demonstrate minimal internal strain and reduced lattice anomalies. The alloy showcased resistance with a corrosion current density of 1.4×10-7 A/cm2 and a corrosion potential of 0.28047 V. Post-corrosion examinations emphasized regions abundant in Al and Cu as the primary degradation sites. The addition of Si has further improved the alloy's resistance to corrosion. In terms of abrasion durability, the alloy exhibit-ed a wear scar length of only 1.42 mm, substantially less than the 1.88 mm found in 45# steel, highlighting its enhanced resistance to wear. This wear resistance is attributed to its inherent BCC1 and BCC2 phase structures and the hardness it derives from its unique composition. Owing to its superior traits, this high-entropy alloy presents promising potential for applications, including coatings, and advanced automotive components.

The article describes a pilot experiment of mechanical testing of 3D printed vertebrae with an inserted screw. The main goal of this work was to verify the design of a measurement methodology for experimentally determining the mechanical properties of vertebrae produced using 3D printing and also for determining the load-bearing capacity of a screw when it is drilled into a vertebra. The work describes the construction of a special fixture with which it is possible to clamp test samples for tensile testing. The stud screws were pulled out of a real or printed vertebra using a tearing machine. Testing was performed on porcine and 3D printed vertebrae. CT images of porcine spines obtained by a computed tomography scanner were used to create the printed vertebrae. This work verified the mechanical properties of printed and real vertebrae. In connection with this work, suitable printed materials and the necessary parameters of 3D printed samples will be sought so that they correspond to the necessary mechanical properties and can replace human vertebrae. It will then be possible to conduct laboratory investigations to obtain better results in spinal stabilization. The experiments verified the measurement methodology, compared the measured values between real and printed vertebrae, and also determined the next direction of research.

Determining the productivity and quality of precision AWJ machining requires routine and careful inspection of nozzle condition. The degradation of the inner bore of the nozzle adversely impacts the mixing efficiency and uniformity of the water jet, thereby affecting its cutting performance. In this study, new nozzle was designed and manufactured using additive manufacturing and were made of 316 L stainless steel. The new nozzle consists of two combined parts with the peculiarity of being easy to install using a screw thread. The wear behavior of the new nozzle was examined using an accelerat-ed wear test. An accelerated wear test was conducted on the hard abrasive silicon carbide (SiC) and compared to garnet, the abrasive commonly used in the AWJ industry. The aim of the test was to de-termine the wear pattern of the nozzle. The cumulative mass loss and nozzle diameter increase for different abrasives were measured. The geometric change in the nozzle is made visible through de-structive examination. The findings indicated that the type of abrasives significantly affects nozzle wear. As the hardness of the abrasive increases, the diameter of the nozzle enlarges, resulting in accel-erated nozzle wear. The mass loss factor of SiC abrasives is three times higher than that of garnet abrasives. This research allows practitioners to monitor the nozzle wear behaviour during the AWJ process. The results obtained were used to estimate the nozzle life based on the observed wear history.

Titanium alloy Ti6Al4V fabricated using Selective Laser Melting (SLM) has gained significant attention in biomedical and aerospace applications due to its superior mechanical properties and design flexibility. However, its machining characteristics, particularly in milling, remain challenging due to the material's hardness and thermal conductivity. This study investigates the milling performance of SLM-manufactured Ti6Al4V by optimizing surface roughness using the Taguchi method. An L9 orthogonal array was employed, considering spindle speed, feed rate, and depth of cut as control factors. Surface roughness measurements were analyzed using Signal-to-Noise (S/N) ratios, and Analysis of Variance (ANOVA). Results indicate that spindle speed significantly affects surface roughness, contributing over 83.67% of the total variation. The optimized milling parameters resulted in a notable improvement in surface quality, highlighting the effectiveness of the Taguchi method in achieving better machinability for additively manufactured titanium alloys. This study offers useful insights to improve the milling process of SLM-made Ti6Al4V, helping boost performance in industrial use.

This work aims at the description of the degradation of the intake and exhaust valve of the combus-tion engine during operation. For the experiments, new valves from Ford Fiesta were used, as well as the used ones with known mileage. In order to simulate the valve long-term operation and to esti-mate the temperature of the valve during the use, the new valves were annealed at 700 – 900 °C for 1000 h (corresponding to the mileage of 70,000 km with average speed of 70 km/h) and the grain size was compared with the used valves. It was found that this model experiment can easily predict the operation temperatures of the exhaust valves, which were made of the heat-resistant austenitic steel. However, the metallography procedure for the determination of the grain size fails in the case of the martensitic steel valves.

Cast iron with nodular graphite is one of the most important structural materials that exhibit really good mechanical properties already in the as-cast condition. Nowadays, cast iron with nodular graphite is used in many areas of the manufacturing industry, the most widespread being in the engineering and automotive industries. The applicability of this material for construction purposes is mainly due to its mechanical properties, which are close to those of steel, but the production cost of cast iron is lower. This experiment was aimed at optimizing the production of ductile iron castings in the casting pits so that the foundry could produce ductile iron castings in the casting pits. Therefore, the optimization of the moulding compound database material was carried out in numerical simulation and at the same time, the heat transfer measurement of the foundry sand mould was carried out.

This article explores the significance of microtexturing on cutting tools for improved tribological performance and reduced friction in machining operations. Drawing inspiration from biomimetic structures, the study focuses on laser surface microtexturing and evaluates its impact on cutting forces and tool wear. Experiments involve microtextures of dots with a specific emphasis on a fiber laser-processed pattern. While long-term tests reveal the formation of negative protrusions on the textured tools, reduced variability in cutting forces suggests potential benefits for stable machining processes and increased tool longevity. The findings underscore the intricate relationship between microtexturing patterns and tool performance, offering insights into the broader implications for energy-efficient machining.

Methanol, a type of alcohol, with gasoline, a conventional fossil fuel used in internal combustion engines. This blending process is often done to create an alternative fuel that may have certain advantages over using gasoline alone. The combination of methanol and gasoline can offer benefits such as improved combustion efficiency, reduced emissions, and potentially lower overall fuel costs. Methanol has a high-octane rating, which can enhance the combustion characteristics of the fuel mixture. This can lead to more efficient and cleaner combustion in internal combustion engines. Conducting this research is essential to explore potential improvements in fuel efficiency, emission reduction, and overall system performance, which are critical for advancing sustainable energy solutions. The tests were done using a mobile generator Briggs and Stratton ProMax 3500A. The tested fuels were 10 %, 20 % and 50 % blends of methanol in gasoline. The electrical output of the generator was roughly the same for all fuels even at higher load, however consumption increased significantly. The mixtures had a negative effect on the stability of engine operation and engine emissions had a negative effect at most of the measurement points. In some cases, like the concentration of formaldehyde by weight, gasoline fuel mixtures showed a decrease in mass concentration at lower engine loads and an increase at higher loads compared to the reference fuel.

The topic of this paper is the application of machine learning and neural networks in engineering, specifically in the prediction of the lifetime of bearings operating in different conditions. In addition, the basics of machine learning are introduced, giving an idea of the importance of input data quality for model training. It also presents the elements of neural network training to be used in other projects. The article is supplemented by a source code examples written using only the Python language, and some other popular libraries, like the NumPy, Matplotlib, Tensorflow, Keras, and Scikit-learn. The main advantage of the libraries used is that they are freely available and widely used, bringing variety of sophisticated tools for gen-eral use.

The given paper deals with the defects propagation in car tires for passenger vehicles under dynamic loading. The occurrence of defects has the significant influence on the lifetime and quality of the tire, especially during its operation as a part of the vehicle. The given defects are closely connected with a safety in road traffic. The aim of the study was to carry out a non-destructive analysis of the car tire for the purpose to analyze the defects propagation as well as to introduce the defects classification and their location along with the whole course of rupture as a result of increasing speed, loading and the number of hours or kilometers driven. During the analysis, we used a non-destructive method for detecting defects using a non-destructive analyzer that works on the principle of shearography. The experimental measurement was carried out for 12 car tires. The measurement results are displayed from the non-destructive analyzer in the form of protocols from measurement and video display. The evaluation of the results of the measurement for the propagation of defects is displayed graphically. In relation to the tire casing, the analysis of the defects propagation can help design engineers to solve critical issues by choosing the right material, modifying dimensions of individual components or even by redesigning the overall construction of the tire casing and thus to increase the safety from the as-pect of vehicle operation.

The article is focused on the investigation of the impact of the implementation of mechanization into the welding workplace, for the production of cylinders from austenitic X5CrNi18 10 chromium nickel steel. The welds are assembled into a production line for the processing of puff pastry. In addition to the technical improvement of the process and the verification of the sufficient quality of the welds, calculations were used to prove that after the implementation of the change, there was a significant reduction in the production time. By introducing a higher level of mechanization and necessary technological changes, the production time was reduced by up to half, compared with the original technological procedure, including an increase in quality parameters and it led to a reduction in the production costs of the welding workplace. A significant consequence of the proposed change was connected with its impact on workplace safety.

Polymers and their surface modifications are the subject of intensive research due to their wide industrial applications in the fields of food packaging, biomedicine and electronics. The most widely used polymer films include polyethylene (PE), polyethylene terephthalate (PET) and polypropylene (PP), whose surface and mechanical properties can be optimized through physicochemical modifications. Diffuse coplanar surface barrier discharge (DCSBD) represents an effective method for modifying the surface properties of polymers without significantly affecting their structural properties. This study focuses on analyzing the effect of DCSBD plasma discharge on the mechanical behavior of PE, PET and PP films by means of dynamic mechanical analysis (DMA). Experimental samples were exposed to DCSBD plasma discharge and subsequently subjected to DMA over a wide temperature range. The measurement results showed significant changes in the storage modulus (E′), loss modulus (E′′) and loss angle (tan δ), while a decrease in material stiffness and a shift in glass transition temperatures (Tg) were identified.