Search Results (55)

Burrs are a significant machining defect affecting the quality of precision parts, and tool eccentricity may substantially influence milling burrs. Using AISI 304 stainless steel as the workpiece material, a three-dimensional thermo-mechanical coupled model for slot milling was constructed based on an explicit dynamics model. Combining the Johnson–Cook (J-C) constitutive model with the J-C shear failure criterion, simulations were conducted to obtain burr dimensions, cutting temperature distributions, and cutting force waveforms under different tool eccentricity directions and magnitudes. Results: As the eccentricity increases, the temperature of the top burr rises, and both the width of the top burr and the thickness of the exit side burr significantly increase. Under simulated conditions, the width of the top burr in down milling side increased by up to 70%. The burr dimensions under different eccentricity directions can differ by approximately 40%. Groove milling experiments revealed similar burr shapes between experimental and simulated results. Furthermore, the simulated cutting force waveforms aligned with those in the literature, indicating the reliability of the simulation outcomes. Based on these findings, it can be concluded that tool eccentricity significantly affects the dimensions of top burrs and exit side burrs. The width of top burrs and the thickness of exit side burrs are positively correlated with the tool eccentricity distance, while exit bottom burrs remain unaffected by eccentricity. These research results provide valuable reference for burr suppression in practical machining operations. Full article

Background: To evaluate the fracture resistance of 3D-printed 3-unit fixed dental prostheses (FDPs) made from tetragonal zirconia polycrystal (3Y-TZP). Methods: Based on a maxillary typodont model with a missing first molar and neighboring teeth with full crown preparations, FDPs differing in wall thickness (d = 0.6 mm / d = 0.8 mm / d = 1.0 mm) were designed. For all test groups, 12 samples were fabricated from 3Y-TZP by either 3D-printing or milling. For 3D-printing, pontic designs were modified by basal slots to enable regular firing times. After luting on CoCr dies, samples underwent artificial aging. Loads tilted by 30° were applied on the mesio-buccal cusp of the pontic, and fracture resistance F_u was assessed. Welch ANOVA and Dunnett-T3 tests were used for statistical evaluation. Results: Significant differences in F_u were identified (Welch ANOVA, p < 0.001). For milled FDPs, fracture originated from connector areas, and F_u increased with increasing wall thickness (d = 0.6 mm: 1536 ± 131 N, d = 0.8 mm: 2226 ± 145 N, d = 1.0 mm: 2686 ± 127 N, significant differences but for the comparison d = 0.8 mm vs. d = 1.0 mm). For 3D-printed FDPs, the loaded cusp fractured, and F_u did not change with FDP wall thicknesses (p > 0.779, F_u = 1110 ± 26 N for all PZ FDPs). Milled FDPs showed significantly higher F_u when compared to 3D-printed FDPs with identical wall thickness. Conclusions: Although 3D-printed zirconia FDPs still show lower fracture resistance values than their milled counterparts, all tested FDP configurations clearly exceed the clinical reference thresholds and can therefore be recommended for clinical use. Full article

Jet electrochemical milling (JECM) offers significant advantages for fabricating fine grooves and slits in thin-walled, low-rigidity, and heat-sensitive metallic materials, such as amorphous alloys, owing to its operational flexibility, lack of material constraints, and superior surface quality. Nevertheless, conventional JECM techniques for groove machining encounter limitations including excessive overcut, restricted ability to produce microstructures with high depth-to-width ratios, and reduced machining accuracy. To address these issues, this study proposes an innovative approach termed the periodically thinning jet electrochemical milling (PT-JECM) method. This method involves initially generating a shallow microgroove through a single pass using the original nozzle diameter, followed by successive milling passes with progressively smaller nozzle diameters based on the preformed groove. Comparative analysis with traditional JECM methods reveals that this strategy significantly improves the etching factor from 1.896 to 4.318, corresponding to a 128% enhancement. Furthermore, it markedly decreases the slot width increase from 275 μm to 1 μm and improves the aspect ratio from 0.51 to 0.83, representing a 63% increase, enabling the precision machining of large aspect ratio holes and slot structures. Full article

In this work, a new approach to high-speed multi-coordinate milling was developed. The new approach is based on a new model of trochoidal machining; this is, in turn, based on the theoretical thickness of a chip and its ratio to the cutting edge’s radius, allowing us to establish the vibroacoustic indicators of cutting efficiency. The new model can be used for the real-time assessment of prevailing cutting mechanisms and chip formation. A set of new indicators and parameters for trochoidal high-speed milling (HSM), which can be used to calculate tool paths during technological preparation of slotting, was determined and verified. The size effect in the multi-coordinate HSM of slots on cast iron was identified based on the dependency of vibroacoustic signals on the cutting tooth’s geometry, HSM’a operational machining modes, theoretical chip thicknesses, the sizes of the cut chips, and the quality/roughness of the surface being machined. Based on the analysis of vibroacoustic signals, a set of the most important indicators for monitoring HSM and determining cutting and crack-formation mechanisms during chip deformation was derived. Based on the new model, recommendations for monitoring HSM and for assigning the tool path relative to the workpiece during production preparation were developed and validated. Full article

Technological advances have expanded the use of single-crystal in microscale applications—particularly in infrared optics, electronics, and aerospace. Conducting research on the surface quality of micro-milling processes for single-crystal superalloys has become a key factor in expanding their applications. In this paper, the nickel-based single-crystal superalloy DD5 is selected as the test object, and the finite element analysis software ABAQUS 2022 version is used to conduct a simulation study on its micro-scale milling process with reasonable milling parameters. A three-factor five-level L₂₅(5³) slot milling orthogonal experiment is conducted to investigate the effects of milling speed, milling depth, and feed rate on its milling force and surface quality, respectively. The results show that the milling depth has the greatest impact on the milling force during the micro-milling process, while the milling speed has the greatest influence on the surface quality. Finally, based on the experimental data, the optimal parameter combination for micro-milling nickel-based single-crystal superalloy DD5 parts is found—when the milling speed is 1318.8 mm/s; the milling depth is 12 µm; the feed rate is 20 µm/s; and the surface roughness value is at its minimum, indicating the best surface quality—which has certain guiding significance for practical machining. Full article

To address the challenges of complex cutting force formation and low prediction accuracy in discrete-edge end mills, this study proposes a precise cutting force modeling method based on an effective chip slot function. An effective chip slot function is established to quantitatively characterize the dynamic variation of cutting edge engagement along different axial positions. Based on the instantaneous uncut chip thickness theory by Altintas, a high-precision cutting force model suitable for discrete-edge tools is developed. Experimental results show that the proposed model achieves an average prediction error of 4.82%, with a maximum error below 10%, demonstrating its high accuracy and practical applicability. Comparative experiments with conventional continuous-edge end mills under identical machining conditions indicate that the discrete-edge tool can reduce cutting forces (F_x by 7.2%, F_y by 3.2%), significantly suppress cutting vibrations (fluctuation coefficients reduced by 13.5% and 21.9%, respectively), and lower surface roughness to approximately one-sixth of that produced by conventional tools. The results confirm that discrete-edge end mills exhibit notable advantages in machining stability, cutting force control, and surface quality, providing a solid theoretical foundation for the design and process optimization of high-performance cutting tools. Full article

Nickel-based superalloy Hastelloy C276 is widely used in high-performance industries due to its strength, corrosion resistance, and thermal stability. However, these same properties pose substantial challenges in machining, resulting in high tool wear, surface defects, and dimensional inaccuracies. This study investigates methods to enhance machining performance and surface quality by evaluating the tribological behavior of TiSiN/TiAlN-coated carbide inserts under six cooling and lubrication conditions: dry, MQL with coconut oil, Cryo-LN₂, Cryo-LCO₂, MQL–Cryo-LN₂, and MQL–Cryo-LCO₂. Open-slot finishing was performed at constant cutting parameters, and key indicators such as cutting zone temperature, tool wear, surface roughness, chip morphology, and microhardness were analyzed. The hybrid MQL–Cryo-LN₂ approach significantly outperformed other methods, reducing cutting zone temperature, tool wear, and surface roughness by 116.4%, 94.34%, and 76.11%, respectively, compared to dry machining. SEM and EDS analyses confirmed abrasive, oxidative, and adhesive wear as the dominant mechanisms. The MQL–Cryo-LN₂ strategy also lowered microhardness, in contrast to a 39.7% increase observed under dry conditions. These findings highlight the superior performance of hybrid MQL–Cryo-LN₂ in improving machinability, offering a promising solution for precision-driven applications. Full article

The increasing demand for precision-engineered machined components across diverse sectors highlights the importance of optimizing machining procedures. The improvement of milling strategies is significant in the production of flat surfaces and slots of different sizes. The choice between milling techniques can significantly impact the final product quality and production efficiency. This study provides a detailed examination of the relative effectiveness of plunge milling (axial feed) versus face milling (radial feed) techniques, concentrating on critical performance metrics such as cutting force and surface roughness. In our systematic approach, we varied key milling parameters (feed per tooth, depth of cut, and cutting speed). We conducted a series of experiments to quantify the resulting cutting forces and surface finish quality employed under different conditions. The analysis reveals notable performance differences between the two milling methods at various parameter settings. Through statistical and graphical analysis, we clarify the relationships between milling parameters and the resultant outputs, offering a deeper understanding of the factors influencing machining efficiency. The results reveal significant differences between plunge milling and face milling, with plunge milling exhibiting lower cutting forces, while face milling demonstrated superior surface quality. The insights granted from this research have implications for optimizing milling operations. Full article

It is well understood that burr size and shape, as well as surface quality attributes like surface roughness in milling parts, vary according to several factors. These include cutting tool orientation, cutting profile, cutting parameters, tool shape and size, coating, and the interaction between the workpiece and the cutting tool. Therefore, burr size cannot be formulated simply as a function of direct parameters. This study proposes an ensemble learning regression model to accurately predict burr size and surface roughness during the slot milling of aluminum alloy (AA) 6061. The model was trained using cutting parameters as inputs and evaluated with performance metrics such as mean absolute error (MAE), mean squared error (MSE), and the coefficient of determination (R²). The model demonstrated strong generalization capability when tested on unseen data. Specifically, it achieved an R² of 0.97 for surface roughness (Ra) and R² values of 0.93 (B5, B8), 0.92 (B2), 0.86 (B1), and 0.65 (B4) for various burr types. These results validate the model’s effectiveness despite the nonlinear and complex nature of burr formation. Additionally, feature importance analysis via the F-test indicated that feed per tooth and depth of cut were the most influential parameters across several burr types and surface roughness outcomes. This work represents a novel and accurate approach for predicting key surface quality indicators, with significant implications for process optimization and cost reduction in precision machining. Full article

The aim of the work was to investigate the influence of the machining parameters on the surface roughness and tool wear during slot milling of a polyurethane block (PUB). In the experiment, the influence of the cutting speed, the feed per tooth and the depth of cut on the roughness Ra and Rz of the milling slot surface and wear of the end mill was analyzed. A three-axis CNC milling machine Emco Concept Mill 55 was used to perform the study. After the machining, the values of parameters Ra and Rz were measured using the Hommel Tester T500 induction profilometer. Three polyurethane materials of different densities were considered: the Labelite 45, the Prolab 65 and the LAB 1000. The wear of the end mill was also examined for each of the tested materials by a workshop microscope. In conclusion, it was indicated how and to what extent the variation in the machining parameters affects the surface geometrical structure of a polyurethane plate. Moreover, the research results for the tested materials were compared with each other. Full article

Difficult-to-cut titanium matrix composites (TMCs) are widely used in the aerospace, automotive, and defense sectors due to their excellent physical properties. Electrochemical mill grinding (ECMG) can achieve the processing effects of electrochemical milling and electrochemical grinding using the same tool, which has the potential to complete the rough and finish machining of TMCs in succession. However, in the rough machining stage, the bottom of the slot becomes concave due to the inevitable stray corrosion, leading to poor flatness, which increases the machining allowance for subsequent finish machining. In this paper, a bottom outlet hole layout of an abrasive tool with a diameter of 6 mm is proposed. Dynamic simulations demonstrate that the electrolyte flow rate in both side regions of the slot is significantly increased by the bottom outlet holes. The experimental results confirm that, compared with the tool without bottom outlet holes, a 61.2% reduction in the bottom flatness can be achieved when using the newly proposed tool during rough machining. After the finish machining, a slot with a width of 8 mm and a depth of 4.8 mm was obtained on the TMCs, which had a flat bottom and sidewall surface with good surface quality. Full article

The current study aims to evaluate the performance of the ultrasonic vibration-assisted milling (USVAM) process when machining two different materials with high deviations in mechanical properties, specifically 7075 aluminium alloy and Ti-6Al-4V titanium alloy. Additionally, this study seeks to develop an AI-based model to predict the process performance based on experimental data for the different workpiece characteristics. In this regard, an ultrasonic vibratory setup was designed to provide vibration oscillations at 28 kHz frequency and 8 µm amplitude in the cutting feed direction for the two characterised materials of 7075 aluminium alloy (150 BHN) and Ti-6Al-4V titanium alloy (350 BHN) workpieces. A series of slotting experiments were conducted using both conventional milling (CM) and USVAM techniques. The axial cutting force and machined slot surface roughness were evaluated for each method. Subsequently, Support Vector Regression (SVR) and artificial neural network (ANN) models were built, tested and compared. AI-based models were developed to analyse the experimental results and predict the process performance for both workpieces. The experiments demonstrated a significant reduction in cutting force by up to 30% and an improvement in surface roughness by approximately four times when using USVAM compared to CM for both materials. Validated by the experimental findings, the ANN model accurately and better predicted the performance metrics with RMSE = 0.11 µm and 0.12 N for Al surface roughness and cutting force. Regarding Ti, surface roughness and cutting force were predicted with RMSE of 0.12 µm and 0.14 N, respectively. The results indicate that USVAM significantly enhances milling performance in terms of a reduced cutting force and improved surface roughness for both 7075 aluminium alloy and Ti-6Al-4V titanium alloy. The ANN model proved to be an effective tool for predicting the outcomes of the USVAM process, offering valuable insights for optimising milling operations across different materials. Full article

In the die and mold industry, tempered JIS SKD11 steel is selected to manufacture cold-forming dies that require an optimum balance of toughness, strength, and wear resistance. Therefore, the machinability of tempered JIS SKD11 in the milling machining process is challenging. The use of eco-friendly machining settings is intended to diminish tool wear and enhance the quality of the machined surface as well as the accuracy of the machined components. Adapting to the aforementioned factors for cold-forming dies is a pivotal issue. In this study, the machinability of tempered JIS SKD11 steel was analyzed under dry, MQL, cryogenic cooling with liquid nitrogen (LN₂), and liquid carbon dioxide (LCO₂) machining settings during open slot milling operations with varying input parameters, including cutting speeds and cutting feeds. An in-depth evaluation of output responses, including tool wear, surface roughness, cutting temperature in the cutting zone, and microhardness of the machined surface, was also conducted. The findings unveiled that the flank wear of the cutters and surface roughness of the machined surfaces obtained minimum values of 0.22 mm and 0.197 µm, respectively, during open slot milling operations at a cutting speed of 100 m/min and a cutting feed of 204 mm/min under cryogenic cooling with liquid carbon dioxide (LCO₂). The findings from this study suggest that employing cryogenic cooling with LCO₂ could serve as a viable substitute for dry, MQL, and cryogenic cooling with LN₂ methods to enhance the machinability of hardened JIS SKD11 steel. Full article

Cooling–lubricating processes have a big impact on cutting force, tool wear, and the quality of the machined surface, especially for hard-to-machine superalloys, so the choice of the right cooling–lubricating method is of great importance. Nickel-based superalloys are among the most difficult materials to machine due to their high hot strength, work hardening, and extremely low thermal conductivity. Previous research has shown that flood cooling results in the least tool wear and cutting force among different cooling–lubricating methods. Thus, the effects of the flood oil concentration (3%; 6%; 9%; 12%; and 15%) on the above-mentioned factors were investigated during the slot milling of the GTD-111 nickel-based superalloy. The cutting force was measured during machining with a Kistler three-component dynamometer, and then after cutting the tool wear and the surface roughness on the bottom surface of the milled slots were measured with a confocal microscope and tactile roughness tester. The results show that at a 12% oil concentration, the tool load and tool wear are the lowest; even at an oil concentration of 15%, a slight increase is observed in both factors. Essentially, a higher oil concentration reduces friction between the tool and the workpiece contact surface, resulting in reduced tool wear and cutting force. Furthermore, due to less friction, the heat generation in the cutting zone is also reduced, resulting in a lower heat load on the tool, which increases tool life. It is interesting to note that the 6% oil concentration had the highest cutting force and tool wear, and strong vibration was heard during machining, which is also reflected in the force signal. The change in oil concentration did not effect the surface roughness. Full article

While a gambler may occasionally win, continuous gambling inevitably results in a net loss to the casino. This study experimentally demonstrates the profitability of a particularly deceptive casino game: a two-armed antique Mills Futurity slot machine. The main findings clearly show that both non-random and random two-arm strategies, predetermined by the player and repeated without interruption, are always profitable for the casino, despite two coins being refunded for every two consecutive losses by the gambler. We theoretically explore the cyclical nature of slot machine strategies and speculate on the impact of the frequency of switching strategies on casino returns. Our results not only assist casino owners in developing and improving casino designs, but also guide gamblers to participate more cautiously in gambling. Full article