Search Results (455)

This study presents a simulation-assisted engineering framework intended to support comparative machining parameter selection for quartz sintered materials. The approach integrates CAD/CAM-based analysis, an illustrative Design of Experiments (DOE) framework, and preliminary experimental validation to improve process planning and machining quality. The analysis focuses on key technological parameters, including cutting speed (vc), feed rate (f), and depth of cut (ap), evaluated across cutting, milling, and finishing stages. The results indicate that feed rate is the dominant parameter influencing process stability, surface quality, and edge integrity. A practical transition region of approximately 1200 mm/min was identified, above which increased vibration, defect formation, and surface degradation occur. The complementary DOE analysis confirms the relative importance of process parameters and reveals interaction effects, particularly between feed rate and depth of cut, which significantly influence defect formation under high-load conditions. Preliminary industrial observations provide trend-oriented support for the simulation-predicted process behavior. Based on the integrated analysis, a preliminary technological operating region was identified (vc = 1080–1320 m/min, f = 800–1200 mm/min, ap = 0.5–1.0 mm), suggesting a practical compromise between machining efficiency and surface integrity. The proposed methodology provides preliminary engineering support for comparative process planning and defect-reduction-oriented parameter selection in the machining of brittle materials. The novelty of this work lies in the integration of CAD/CAM simulation, DOE-based interaction analysis, and experimental validation for supporting the identification of a practical technological operating region for machining brittle materials. The presented results should therefore be interpreted as engineering-oriented comparative process-planning guidelines rather than statistically generalized machining laws. The presented study should be interpreted as an exploratory simulation-assisted engineering investigation intended to support comparative process planning rather than as a fully experimentally validated machining model. Full article

Photovoltaic modules require efficient sunlight modulation, including enhanced visible transmittance and conversion of unused ultraviolet light. This study develops a synthetic optical coating that achieves both functions by integrating down-conversion BAM (BaMgAl₁₀O₁₇:Eu²⁺, Mn²⁺) nanophosphors into a silica anti-reflection sol. The key novelty lies in a synergistic surface engineering strategy that decouples dispersion stabilization from luminescence protection. Five dispersants are systematically compared under combined ball and sand milling. The polyester-modified acrylic long-chain dispersant (DK062) yields a stable nanodispersion with an average particle size of 228 nm and a Zeta potential of −7.61 mV, effectively suppressing re-agglomeration while retaining high photoluminescence. Subsequent surface modification with KH570 grafts a dense silane passivation layer via Si–O–M covalent bonds, further increasing the photoluminescence intensity by 1.39-fold. The optimized nanophosphors are incorporated into a commercial anti-reflection sol and dip-coated onto photovoltaic glass. At a doping concentration of 2‰ and a withdrawal speed of 8 mm/s, the resulting DCSAR coating exhibits an average transmittance of 91.16%—slightly higher than that of the pure anti-reflection coating (90.96%)—while showing strong green emission at 515 nm. Industrial on-site testing further demonstrates an average transmittance of 94.20%–94.31% with uniform green emission. This work provides a scalable route to fabricate highly transparent, light-converting anti-reflection coatings by combining dispersant-assisted milling and silane passivation. Full article

Background/Objectives: The objective of this study was to design and optimize a continuous wet granulation process for Amiodarone hydrochloride tablets using a Design of Experiments approach. The study compared and evaluated the characteristics of granules and tablets produced via a high-shear mixer (batch process) and a twin-screw granulator (continuous process). Methods: For process optimization, a central composite design was applied to establish a design space, defining screw speed and milling size as critical process parameters (X) and dissolution rate, flowability, assay, disintegration time, and friability as dependent variables (Y). Results: Comparative results between the two processes revealed no significant differences in in-process control parameters, and all formulations successfully met the target dissolution profiles. Notably, the similarity factor (f₂) was calculated to be above 50, through which dissolution equivalence was successfully demonstrated with a high level of statistical certainty. Regarding process efficiency, lead time measurements confirmed that the continuous process dramatically reduced manufacturing time by more than 80% compared to the batch process. Conclusions: This study validates the feasibility of converting batch-based drug manufacturing to a continuous platform without altering the formulation, presenting an effective process strategy for enhancing productivity and operational efficiency in the pharmaceutical industry. Full article

High-quality microgrooves obtained in micro-milling titanium alloy Ti6Al4V are still challenging work due to the dependence of burr formation and surface roughness on cutting parameters. In this paper, the systematic analysis of the micro-milling process was conducted to obtain high-quality titanium alloy Ti6Al4V microgrooves, which is based on single-factor experiments, orthogonal experiments, intuitive analysis, range analysis, regression analysis, and multi-objective optimization. The range of factors and factors of orthogonal experiments were determined by single-factor experiments. Orthogonal experiments were conducted with a three-factor three-level design, which regards the total top-burr width and the bottom surface roughness of microgrooves as the response variables, and factors are spindle speed, feed per tooth, and the axial depth of cut. The optimal cutting parameters, which minimize the surface roughness and burr formation, and the main influence factor were determined by intuitive analysis, range analysis, regression analysis, and NSGA-II multi-objective optimization. Simultaneously, high-quality complex microgrooves were achieved with the optimal cutting parameters. The method of systematic experimental design and data analysis in this paper can provide the theoretical guideline and technical support for the processing development of complex parts. Full article

High-temperature sintered conductive silver paste serves as a critical material in the fabrication of electronic components, with its performance directly influencing device reliability and integration density. In this work, conductive silver paste was prepared via a ball milling method by dispersing silver powder (conductive filler), glass powder (binder), and ethyl cellulose (EC, thickener) in an organic carrier composed of α-terpineol, diethylene glycol butyl ether acetate (DBA), and dimethyl phthalate (DMP) at specific ratios. The effects of the formulation composition and preparation process on the rheological properties of the paste as well as the electrical and mechanical properties of the resulting films were systematically investigated. The results indicated that sintering time and temperature exerted regular effects on the resistance of the silver paste; ball milling speed and duration influenced the particle size distribution, thereby affecting the resistance behavior; thixotropy significantly impacted the resistance characteristics. Under optimal conditions, where the organic carrier consisted of α-terpineol, DBA, and DMP at a ratio of 6:3:1, with 30 wt.% silver powder, 18 wt.% glass powder, and 4 wt.% EC, combined with a sintering temperature of 500 °C for 50–60 min, a ball milling speed of 500–600 r/min, and a ball milling time of approximately 1.5 h, the obtained silver paste exhibited pronounced shear-thinning behavior and excellent thixotropy, indicating favorable processability. The corresponding silver paste film demonstrated the lowest resistivity, superior bending resistance, and good adhesion to both PET and glass substrates. This study provides valuable insights for the design and preparation of high-performance, high-temperature sintered conductive silver pastes. Full article

Wet stirred-media milling (WSMM) is among the most widely used techniques for producing high-drug-loaded stable nanosuspensions, owing to its ease of scale-up, good repeatability, operational versatility and broad applicability. However, WSMM is also associated with high energy demand, substantial heat generation, and extended milling times. To reduce energy consumption, optimize the process and gain a deeper understanding of breakage kinetics, robust mechanistic models should be investigated. In this study, a microhydrodynamic (MHD) model framework is examined, and the first closed-form analytical solution for granular temperature $\theta$, a key parameter in the MHD model, is derived. In addition, an existing power consumption correlation from the literature is adopted and extended by introducing an additional parameter that accounts for bead-size effects, and the resulting improved formulation is embedded into the analytical framework. This integration facilitates continuous evaluation of power consumption, $\theta$ and the additional MHD parameters across the milling parameter space. With backward compatibility and high-quality fitting performance, the improved power consumption model enables robust, reliable, and systematic evaluation of sensitivities and trade-offs over diverse milling conditions, including varying stirrer speeds, bead loadings, and bead sizes. Full article

This study investigates ultrasonic vibration-assisted (UV) CNC milling of hardened 90CrSi steel cylindrical surfaces, with emphasis on ultrasonic horn design, experimental analysis, and multi-objective optimization of machining parameters, addressing the need for an integrated framework combining system design, experimental validation, and multi-objective optimization. A quarter-wavelength ultrasonic horn was designed and experimentally validated to operate at a frequency of 20 kHz. By adjusting the horn–workpiece system, stable vibration amplitudes were achieved to enable effective ultrasonic-assisted milling of cylindrical surfaces. Milling experiments based on a Box–Behnken design were conducted to examine the effects of vibration amplitude, cutting speed, feed rate, and radial depth of cut on material removal rate (MRR) and surface roughness (Ra). Surrogate models using response surface methodology (RSM) and Gaussian process regression (GPR) were developed to predict machining performance. A GPR-assisted NSGA-II algorithm was then applied to simultaneously maximize MRR and minimize Ra, resulting in a well-defined Pareto front that reveals the trade-off between machining productivity and surface quality. Furthermore, an AHP-based decision-making approach was employed to select preferred machining conditions from the Pareto-optimal solutions. The GPR models demonstrated high predictive accuracy (R² > 0.98), and validation experiments confirmed the reliability of the predicted optimal results, with deviations below 5%. In addition, a comparative analysis between ultrasonic-assisted and conventional milling showed that MRR increased by 10.81–40.17%, Ra decreased by 27.11–44.44%, and cutting force was reduced by 14.2–42.65%, providing direct experimental evidence of improved machinability. The results demonstrate that the proposed integrated framework provides an effective strategy for optimizing ultrasonic vibration-assisted milling processes and improving the machinability of hardened 90CrSi cylindrical surfaces. Overall, the proposed framework provides a practical and cost-effective strategy for enhancing machining performance and offers a robust approach for multi-objective optimization of ultrasonic vibration-assisted milling processes. Full article

Hybrid CNC and additive manufacturing platforms often rely on host-assisted or otherwise overdimensioned control architectures to achieve deterministic multi-axis motion, increasing system cost and complexity. This paper presents a fully microcontroller-based timer–DMA motion execution architecture that eliminates the need for external processors or FPGA-based execution, enabling deterministic multi-axis synchronization under the tested conditions in a simpler, more cost-effective way. The proposed framework integrates motion planning, precise step-time computation, and hardware-assisted pulse generation within a unified embedded control architecture. The main novelty lies in the systematic use of timer and DMA peripherals to offload time-critical pulse execution from the microcontroller core, allowing it to focus on motion planning and precise step-time computation. Unlike segmentation-based approaches, the duration of each individual step is calculated directly without fixed-interval segmentation, enabling high motion resolution while avoiding per-step interrupts that introduce jitter at high motion speeds. The architecture was validated on a hybrid platform capable of both milling and material extrusion. Experimental results confirmed real-time feasibility within practical on-chip memory limits and demonstrated very small interpolation errors caused mainly by timer quantization, comparable to those observed in host-processor-based motion systems. Machining and additive-manufacturing experiments further confirmed stable execution and accurate trajectory tracking under real operating conditions. Full article

This study investigates how key milling parameters influence both cutting noise and surface quality during the machining of laminated bamboo lumber. Using a multifactorial optimal response surface methodology, the effects of fibre orientation (0–135°), spindle speed (7000–10,000 r/min), feed rate (0.5–2.0 m/min) and milling depth (0.5–2.0 mm) were quantified through 25 experimental runs. Cutting noise, measured as peak sound pressure level (SPL), ranged from 86.8 to 95.2 dB, increasing markedly with fibre angle, feed rate, and milling depth, but exhibiting a non-linear response to spindle speed. Surface roughness (S_a) varied from 2.6 to 11.7 µm and was most strongly governed by milling depth, followed by fibre orientation and feed rate, with a significant interaction between fibre orientation and spindle speed. Quadratic regression models demonstrated strong predictive performance (R² = 0.97 for SPL; R² = 0.85 for S_a). Based on the response surfaces, optimal low-noise, high-quality machining was achieved at moderate spindle speeds, low feed rates, and shallow milling depths. These findings provide a mechanistic basis for understanding noise–roughness coupling in bamboo machining and offer practical guidance for computer numerical control processing, tool selection, and industrial noise reduction strategies in bamboo manufacturing. Full article

We report on tool wear and surface roughness for hybrid additive manufacturing of Inconel 718 components. The hybrid additive manufacturing comprises laser powder bed fusion (PBF-LB/M) and an in situ high-speed milling process, i.e., milling is performed within the powderbed, which deteriorates the surface quality by additionally occurring wear mechanisms. Therefore, in this comparative study milling path suction is used to improve tool wear characteristics and thus enhance surface quality. As a result, we quantify the improvement of the maximum tool life according to the flank wear, which is granted by the milling path suction. Additionally, the dominant wear mechanisms are investigated, revealing adherence and abrasion as the main contributing factors to wear. Furthermore, surface analysis shows an improvement of surface quality by the use of the milling path suction. Specifically, a reduction in surface roughness of hybrid manufactured Inconel 718 components down to a minimum of $Ra$ = 0.55 μm is highlighted. Full article

Tool wear remains a critical limiting factor in machining performance, particularly in dry cutting conditions where friction and tribological interactions dominate. This study investigates the influence of a 5–8 μm PVD-deposited TiN coating on the wear behavior of high-speed steel (HSS) end mills during milling of three representative wood species (oak, beech, and fir). A spatially resolved wear evaluation methodology was employed, based on ten measurement points distributed along a 20 mm active cutting edge, enabling simultaneous assessment of mean wear and maximum localized wear (Umax). A factorial experimental design combining material type and feed rate (1500–2500 mm/min) was analyzed using two-way ANOVA with effect size quantification (η²). The results reveal a statistically significant reduction in mean wear for TiN-coated tools (F = 7.46, p = 0.0195, η² = 0.34), corresponding to an average decrease of approximately 46% compared to uncoated tools. Maximum wear was influenced by both coating (F = 14.73, p = 0.0028, η² = 0.399) and material (F = 4.37, p = 0.040, η² = 0.237). The experimental findings are interpreted through a tribological framework, indicating a transition from abrasion- and micro-chipping-dominated degradation in uncoated tools to a controlled wear regime in TiN-coated tools, characterized by reduced asperity penetration, delayed crack initiation, and limited tribochemical interactions. These results demonstrate that coating effects dominate global wear evolution, while material properties influence localized degradation. The proposed combined experimental–statistical–mechanistic approach provides a robust framework for understanding and optimizing tool performance in dry machining environments. Full article

Opuntia ficus-indica (L.) Mill., also named Cactus pear, is a crop widespread in many countries with Mediterranean and subtropical climates, where it represents a valuable source of food. However, in southern Europe, this fruit market is limited to a few months, from summer to autumn. The possibility to extend the ripening period of fruit is represented by the special pruning of the first bloom flush and consequent new development of late flowers and fruits. Extending the cultivation period would allow farmers to maximize the crop’s potential, thereby extending the Cactus pear market season throughout much of the year. In this study, conducted in southern Sardinia (Italy), progressive pruning was applied with the aim of evaluating the fruit characteristics in relation to this type of cultivation, also considering the weather conditions during the experimental period. Morphological traits and physicochemical compositions of fruit picked in four harvests during two sampling seasons from August 2022 to March 2023, and from August 2023 to March 2024 were compared. According to principal component analysis (PCA), most of the observed characters showed significant differences among harvest periods but also between the two seasons of cultivation (year of cultivation: r = 0.722 on PC1), suggesting that the meteorological trend strongly modulated fruit traits. Some fruit qualities were partially lost during the winter months, such as juice acidity and total soluble solids (TSS). October was the month with the highest TSS levels (13.5 ± 0.25), followed by August, January and March. On the other hand, juiciness and fresh weight remained unchanged or even improved in fruit harvested out-of-season. As observed in the redundancy analysis (RDA) a contribution of 54% due to weather variability emerged. In Particular, TSS levels, pH and juice dry matter were associated with high temperatures, solar radiation, and wind intensity. Wind speed was also moderately linked with betalain content. Moreover, high relative humidity was associated with lower pH values, higher water content, and higher fruit fresh weight. A significant difference was found between the two years in betalains content (80.0 ± 3.7 µg·mL⁻¹ in 2022–2023 and 28.2 ± 2.5 µg·mL⁻¹ in 2023–2024). The breakdown in the 2023–2024 season was likely due to the strong heat wave of July 2023 (up to 47 °C), which caused their partial degradation. In light of seasonal variability, this work provides some useful insights for future management of Cactus pear, also considering the possibility of usefully extending the period of cultivation and harvesting. Full article

Minimum quantity lubrication (MQL) is a promising green technology for high-speed milling of GH4169. However, the full-chain oil mist penetration mechanism remains unclear, limiting precise parameter regulation. Based on a cross-scale mechanism, this study develops a semi-empirical oil mist penetration efficiency model coupling four key parameters and conducts single-factor and orthogonal high-speed milling experiments to validate the model and analyze the regulation mechanism using milling force and surface roughness. The experimental results show relative deviations below 6%, demonstrating good model validity and robustness. The influence hierarchy is spindle speed > nozzle orientation > nozzle angle > nozzle distance. Spindle speed and nozzle orientation are strongly coupled dominant parameters with a “drive-adaptation” mechanism, while nozzle distance and nozzle angle are weakly coupled, only notable under extreme conditions. The optimal parameters obtained via BP neural network and NSGA-II are nozzle orientation −X, angle 22.43°, distance 14.96 mm, and spindle speed 16,581 rpm. Under this combination, minimum Surface Roughness Ra of 0.17 μm and milling force of 24.27 N are achieved, reducing surface roughness by 85.32% and milling force by 53.52% versus the worst condition and reducing roughness by 28.57% versus the baseline while maintaining milling force within a reasonable range. This study clarifies the physical mechanism of MQL oil mist penetration, extending conventional macroscopic parameter optimization. The proposed cross-scale framework offers theoretical and engineering guidance for MQL parameter design in green precision machining of nickel-based superalloys. Full article

High-speed laser cladding (HLC) technology can provide high cooling rates and low dilution rates for the preparation of metastable Fe-based amorphous phases. In this work, the effects of Ta content on the microstructure, mechanical properties, and soft magnetic performance of Fe-based amorphous alloys were systematically investigated. The results indicated that Ta remained uniformly dispersed within the FeSiB amorphous powder, and no new phases were formed after mechanical ball milling. The higher mixing enthalpy of Ta and its atomic radius difference from other elements (such as Fe, Si, B) were beneficial in improving glass-forming ability (GFA), and with an increase in Ta element content from 0% to 2%, 4% and 6%, the amorphous phase content was 48.6%, 51.5%, 60.4% and 54.8%, respectively. The average microhardness of the coating with a Ta content of 4% was 1310 HV_0.2, which was 50HV_0.2 higher than before; in addition, the wear rate reduced from 2.21 × 10⁻⁴ mg·N⁻¹·m⁻¹ to 2.06 × 10⁻⁴ mg·N⁻¹·m⁻¹. Also, corrosion tests showed that the coating with a Ta content of 4% displayed superior corrosion resistance compared to that before the Ta addition. However, because the element Ta could alter the local electronic environment and enhance the local magnetic anisotropy of FeSiB, the saturation magnetic flux density (Ms) decreased from 1.64 T to 1.56 T, and the coercivity (Hc) increased from 0.9 A/m to 1.3 A/m, which caused degradation of the soft magnetic properties. Full article

This study investigates the influence of selected technical and technological parameters on cutting forces and power consumption during the milling of medium-density fibreboards. Unlike previous studies that focus primarily on force measurement, this work integrates experimental analysis with machine learning-based predictive modelling to improve process understanding and prediction accuracy. The main objective was to experimentally measure orthogonal cutting force components (F_x, F_y, F_z) and electrical power consumption under varying spindle speeds (14,000, 16,000 and 18,000 rpm), feed speed (6, 8 and 10 m/min), and milling strategies (conventional and climb), and to evaluate the suitability of the obtained data for predictive modelling. Cutting forces were measured using a Kistler 9257B piezoelectric dynamometer, and power consumption was recorded by a three-phase power quality analyser. Statistical analysis confirmed significant effects of machining parameters on force components, total cutting force, and power consumption. Spindle speed showed the strongest influence on total cutting force and power consumption, while milling strategy predominantly affected F_x and F_y components. Power consumption increased with increasing spindle speed. Based on the measured data, several machine learning models were developed to predict the total cutting force. The Fine Tree algorithm demonstrated the best performance, achieving validation metrics of R² = 0.9 and RMSE = 0.60 (MSE = 0.36, MAE = 0.48), and improved testing performance with R² = 0.95 and RMSE = 0.44 (MSE = 0.20, MAE = 0.36). After model comparison using RMSE, R², training time, and model size, a Fine Tree model was identified as the most suitable, achieving high prediction accuracy without signs of overfitting. The results confirm that experimentally obtained data on cutting force and electrical energy consumption are suitable for reliable predictive modelling in CNC milling of MDF boards. However, it is necessary to work with those components that have the greatest dependence on speed, feed, or type of milling, and these are the force components measured on the x and y axes. Full article