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Silicon nitride (Si 3 N 4 ) is a high demanded structural ceramic with exceptional mechanical, thermal and chemical properties. Poor surface integrity and limited material removal rate due to high tool wear and cutting forces are the main problems of grinding this material. A novel laser-assisted grinding process is developed to overcome the current technological constraints in the grinding of Si 3 N 4 . Ultra-short pulsed laser radiations are efficiently applied to create ablation, controlled thermal damages and enhance the material removal rate in the grinding process. Two different laser structures have been produced on gas-pressure-sintered Si 3 N 4 with various laser scan speeds and laser line spans. The high performance of the developed process is shown by experimental results. A substantial reduction in tangential and normal grinding forces and a slightly improved surface roughness have been achieved. The analysis of the surface integrity has shown a damage-free ground surface via laser assistance, where the pattern type of structures had a significant influence on the process results.

Super abrasive diamond grinding wheels are the most promising tools for the precision machining of advanced ceramics and carbide materials. However, the efficiency of conventional conditioning of these tools is limited owing to high dressing tool wear, long process time, low form flexibility, and induced damage to the abrasive grains. Wire electrical discharge machining (WEDM) is an alternative method for conditioning of superabrasive grinding wheels with electrically conductive bonding materials. In this study, cylindrical plunge grinding of an alumina ceramic with a resin-bonded diamond grinding wheel is investigated. The assigned type of resin bond contains copper particles and is accordingly electrically conductive for wire electrical discharge conditioning (WEDC). Conventional (mechanical) and WEDC methods are used for generating the same profile on two similar diamond grinding wheels. As a result, the specific grinding energy was reduced up to 26% and 29% during rough and finish plunge grinding, respectively. Reduced specific grinding energy and forces, along with more effective grain protrusion and sharpness by using WEDC for profiling of grinding wheels, have contributed positively to the ground surface conditions despite the relatively rougher wheel surface topography in comparison to the conventional profiling. The more considerable reduction in the mean roughness depth (Rz) than in the arithmetical mean roughness value (Ra) (11% smaller Rz values in WEDC versus mechanical conditioning) verifies that the workpiece surface underwent less surface degradation in case of WEDC because of smaller grinding forces. Furthermore, the profile wear behavior of the workpiece ground with the WED conditioned grinding wheel was superior to the conventionally conditioned one.

This work investigates the penetration behavior of SiC particles into Digital Light Processing (DLP)-printed thermoset substrates under low-pressure cold-spray conditions, aiming to enhance surface hardness and wear resistance. A coupled simulation framework was established in which particle acceleration was obtained from CFD using ANSYS Fluent, and high-speed impact and embedding were modeled through ANSYS Explicit Dynamics. Two particle diameters (25 μm and 60 μm) were examined across inlet pressures from 2 to 5 bar to evaluate both the continuous influence of pressure and the two-level effect of particle size. Mesh convergence was achieved at a resolution of d[sub.p]/20, ensuring numerical stability and computational efficiency. The results showed a strong dependence of penetration depth on pressure and particle size: for 25 μm particles, penetration increased from 0.76 d[sub.p] at 2 bar to 1.53 d[sub.p] at 5 bar, while 60 μm particles exhibited deeper absolute embedding due to their significantly higher kinetic energy. Response-surface analysis further revealed nonlinear pressure effects and a predominantly linear size-dependent shift. Experimental validation at 3 bar confirmed a penetration depth of approximately 1 d[sub.p], demonstrating good agreement between simulation and physical observation. Overall, the validated workflow provides quantitative insight into particle–substrate interaction in thermoset polymers and offers a practical basis for controlled particle embedding as a surface-strengthening strategy in additive manufacturing.

High flexibility of the micro-milling process compared to nontraditional methods has led to its growing application in manufacturing complex micro-parts with tight tolerances and high accuracies. However, difficulties such as tool deflection, size effect, and tool wear limit the application of micro-milling. In this regard, the role of laser-assisted machining (LAM) is highlighted to prevent mentioned issues through reduction of machining forces and providing the possibility for using higher feeds. Ti6Al4V as a hard-to-machine material is chosen as the workpiece material. Unlike traditional LAM, Ti6Al4V parts were structured using a picosecond laser before micro-milling. The influence of laser structuring at different structure densities on the reduction of machining forces was analyzed at two feeds of 10 and 50 µm/tooth at a constant cutting speed of 35 m/min. A remarkable reduction in cutting forces was observed at both feeds. Additionally, the role of structure density in cutting force reduction is highlighted.

A picosecond laser is utilized for microstructuring of a metal-bonded cBN grinding wheel. Two types of structure, both with 15% reduction of the wheel surface area, but with different patterns are produced. The effect of structuring on surface roughness and grinding forces in the cylindrical plunge grinding of 100Cr6 is studied. Reducing the abrasive layer area (15% reduction of the wheel surface area) causes the reduction of grinding forces up to 60%, while the roughness values increase up to 30%. The concentrated structuring approach led to better structure persistence of the wheel structure in comparison with the uniformly distributed structure. Furthermore, temperature measurement demonstrated that microstructuring leads to reduced wheel and workpiece contact zone temperatures.

In this study, an additive manufacturing process based on digital light processing was employed for a quick, flexible, and economical fabrication of resin bonded SiC grinding tools. The grinding wheel has been fabricated using laboratory manufacturing processes that utilize ultraviolet-curable resins and conventional abrasives. Also, desirable geometries and features like integrated coolant holes, which are difficult or even almost impossible to manufacture by conventional processes, are easily achievable. Grinding experiments were carried out by different process parameters, and with two different grinding wheels, i.e., with and without cooling channels with different concentrations (25 wt.% and 50 wt.% grains) to evaluate the grinding efficiency of the produced tools. Grinding forces, tool wear, tool loading, and ground surface quality were measured and analyzed. The wear rates of the grinding wheels with cooling channels were generally less than those without cooling channels, particularly in the deep grinding processes with large contact areas. Grinding tests on a hardened steel have shown that the integration of cooling lubricant channels almost prevents the wheel loading. In addition, by increasing the cutting speed (from 15 to 30 m/s) and decreasing the feed rate (from 10 to 2 m/min), the grinding wheel wear was significantly reduced. Furthermore, surface grinding of aluminum resulted in surface roughness values (Ra) in the range of 1 μm to 2.5 μm, while a Ra of about 0.2 μm was achieved by grinding hardened steel (100Cr6) with the same grinding conditions. Using the higher SiC-grain concentration (50 wt.%), it was determined that the surface roughness was 50% finer. Additionally the tool wear was significantly reduced (up to 30 times depending on the process parameters). The wear characteristics of the grinding wheel were analyzed through a novel image processing system. Significant correlations were found between the wear flat of grains and the increase in grinding forces due to the tool wear.

Polyether ether ketone (PEEK) and its composites are widely used in the biomedical industry due to their superior properties. The presence of glass and carbon reinforcing particles will improve the strength of the polymers while affecting their machinability. The cutting speed, dressing speed ratio, and different reinforcing fibers were defined as input parameters. Grinding forces, specific grinding energy, surface roughness, the surface topography of the workpiece, and wheel loading ratio were selected as output parameters of this research. Surface roughness is strongly affected by heat generation in the grinding zone. The experiments showed that pure polymer, GFRP (glass fiber–reinforced plastic), and CFRP (carbon fiber–reinforced plastic) induce maximum wheel loading ratio, respectively. The maximum wheel loading was calculated as 31% for pure polymer, and the main mechanism is melting. The highest cutting forces were measured when grinding pure polymer, followed by carbon, and glass fiber composites. The grinding forces were also affected by wheel loading ratio. Normal and tangential grinding forces increased up to 67% and 57%, respectively, by severe cutting conditions. The minimum specific grinding energy of PEEK and its composites was around 2.5 J/mm 3 . Additionally, increasing the cutting speed to v c = 15 m/s (despite lower inducing cutting forces) and decreasing the dressing speed ratio to q d = −0.3 surprisingly caused a rise in the roughness of the ground surfaces (for all three materials) due to a higher heat generation in the contact zone.

Understanding the laser ablation mechanism is highly essential to find the effect of different laser parameters on the quality of the laser ablation. A mathematical model was developed in the current investigation to calculate the material removal rate and ablation depth. Laser cuts were created on the workpiece with different laser scan speeds from 1 to 10 mm s −1 by an ultrashort pulse laser with a wavelength of about 1000 nm. The calculated depths of laser cuts were validated via practical experiments. The variation of the laser power intensity on the workpiece’s surface during laser radiation was also calculated. The mathematical model has determined the laser-material interaction mechanism for different laser intensities. The practical sublimation temperature and ablated material temperature during laser processing are other data that the model calculates. The results show that in laser power intensities ( I L ) higher than 1.5 × 10 9 W cm −2 , the laser-material interaction is multiphoton ionisation with no effects of thermal reaction, while in lower values of I L , there are effects of thermal damages and HAZ adjacent to the laser cut. The angle of incidence is an essential factor in altering incident I L on the surface of the workpiece during laser processing, which changes with increasing depth of the laser cut.

Alumina is an advanced ceramic that is frequently used in high-performance applications. Grinding of alumina is usually associated with micro-cracks and deteriorated surface quality. Ultrasonic-assisted grinding has been introduced in several applications as a promising method to overcome these constraints. In order to get a deeper knowledge of the characteristics of material removal mechanisms in alumina during grinding with ultrasonic stimulation of the workpiece, single-grain scratch tests were performed and the theoretical and experimental kinematics of grain-workpiece engagement were investigated. It was shown that in the real contact conditions, interrupted contact conditions happen, which is analogous to the theoretical model. The measured workpiece resonance frequency and mode shape were very close to the design conditions. The investigations show that the superposition of ultrasonic vibration into the grinding process increases the material removal of each grain. This result fully correlates with the presented theoretical analysis. Additionally, it was found that the impact action of ultrasonic-assisted grinding induces chipping around the produced scratch.

Microdrilling of titanium alloys suffers from rapid tool wear that degrades surface quality and dimensional accuracy, while industrial datasets are often too small for conventional data-hungry models. This work proposes a general, AI-driven modelling framework for tool wear prediction under severe data scarcity, which is validated using a titanium microdrilling case study. The study focuses on maximum flank-wear prediction (VBmax) using 18 experimental observations (VBmax = 4–13 µm). Three regression models—support vector regression (SVR), random forest (RF), and extreme gradient boosting (XGBoost)—were benchmarked under multiple validation protocols, with leave-one-out cross-validation (LOOCV) used as the primary assessment due to the limited sample size. To improve reliability and transparency, feature selection was performed using SHapley Additive exPlanations (SHAP), yielding a compact, interpretable feature subset dominated by thrust-force descriptors. Robustness was further evaluated using hyperparameter tuning and a conservative, leakage-controlled (“fold-safe”) augmentation strategy applied strictly within training folds. After tuning and fold-safe augmentation, XGBoost achieved the best LOOCV performance (R2 = 0.89, MSE = 0.70 µm2, MAPE = 7.62%). External validation on two additional tools under identical cutting conditions using a frozen model configuration showed bounded prediction errors under geometry and coating shifts. Overall, the results indicate that combining systematic benchmarking, SHAP-guided explainable feature selection, and leakage-controlled augmentation can enable accurate and interpretable VBmax prediction in the investigated titanium microdrilling case study, while broader validation across additional tools and cutting conditions is required to confirm generalization.