Search Results (583)

Tool wear modeling in CNC turning processes is critical for proactive maintenance and process optimization in intelligent manufacturing. However, traditional physics-based models lack adaptability, while machine learning approaches are often limited by poor interpretability. This study develops Kolmogorov–Arnold Networks (KANs) to address the trade-off between accuracy and interpretability in lathe tool wear modeling. Three KAN variants (KAN-A, KAN-B, and KAN-C) with varying complexities are proposed, using feed rate, depth of cut, and cutting speed as input variables to model flank wear. The proposed KAN-based framework generates interpretable mathematical expressions for tool wear, enabling transparent decision-making. To evaluate the performance of KANs, this research systematically compares prediction errors, topological evolutions, and mathematical interpretations of derived symbolic formulas. For benchmarking purposes, MLP-A, MLP-B, and MLP-C models are developed based on the architectures of their KAN counterparts. A comparative analysis between KAN and MLP frameworks is conducted to assess differences in modeling performance, with particular focus on the impact of network depth, width, and parameter configurations. Theoretical analyses, grounded in the Kolmogorov–Arnold representation theorem and Cybenko’s theorem, explain KANs’ ability to approximate complex functions with fewer nodes. The experimental results demonstrate that KANs exhibit two key advantages: (1) superior accuracy with fewer parameters compared to traditional MLPs, and (2) the ability to generate white-box mathematical expressions. Thus, this work bridges the gap between empirical models and black-box machine learning in manufacturing applications. KANs uniquely combine the adaptability of data-driven methods with the interpretability of physics-based models, offering actionable insights for researchers and practitioners. Full article

This research article examines the CO₂ laser cutting performance of Fused Filament Fabricated Acrylonitrile Styrene Acrylate (ASA) thermoplastics by analyzing the influence of plate thickness, laser power, and cutting speed on four quality characteristics: surface roughness (Ra), top kerf width (Top KW), bottom kerf width (Bottom KW), and bottom heat-affected zone (Bottom HAZ). Forty-five experiments were conducted using five thickness levels, three power levels, and three cutting speeds. To model and predict these outputs, seven machine learning approaches were employed: Autoencoder, Autoencoder–Gated Recurrent Unit, Autoencoder–Long Short-Term Memory, Random Forest, Extreme Gradient Boosting (XGBoost), Support Vector Regression, and Linear Regression. Among them, XGBoost yielded the highest accuracy across all performance metrics. Analysis of Variance results revealed that Ra is mainly affected by plate thickness, Bottom KW by cutting speed, and Bottom HAZ by power, while Top KW is influenced by all three parameters. The study proposes an effective prediction framework using multi-output modeling and hybrid deep learning, offering a data-driven foundation for process optimization. The findings are expected to support intelligent manufacturing systems for real-time quality prediction and adaptive laser post-processing of engineering-grade thermoplastics such as ASA. This integrative approach also enables a deeper understanding of nonlinear dependencies in laser–material interactions. Full article

Plasma jet cutting is a non-conventional process commonly used in modern industry for processing metal sheets and preparing them for subsequent technological steps. In this context it is very important to achieve the best possible final-quality workpiece to minimize additional post-processing costs, and time. This is especially challenging by the plasma jet processing of aluminum and its alloys. In this paper, a comprehensive analysis regarding the machinability and optimal circular quality of aluminum alloy 5083 was performed. Process parameters whose effects were analyzed are the cutting speed, arc current and cutting height. The circular quality was considered through responses: the circular kerf width, circular bevel angle, and circularity error on the top and bottom sheet of the metal side. To design functional relations between the process inputs and quality performances, an artificial intelligence fuzzy logic technique supported by ANOVA was applied. In order to define the process conditions that result in optimal cut quality responses, the multi-objective optimization of hybrid grey relational analysis (GRA) and the fuzzy logic approach was presented. Corresponding surface plots were created to determine the Pareto front of optimal solutions that simultaneously optimize all circular quality objective functions. The optimization procedure was confirmed through a test in which the mean absolute percentage error represented as the validation metric. Full article

We report a passively Q-switched self-Raman laser using a dual-end composite c-cut Nd:YVO₄ crystal, which generates switchable visible emissions at 533 nm, 560 nm, and 589 nm. A Cr⁴⁺:YAG/YAG composite crystal served the role of a saturable absorber to achieve passive Q-switching. An angle-tuned BBO crystal was used to achieve the frequency mixing between the first-tokes wave and the fundamental wave. At an incident pump power of 9.5 W, the maximum average output powers were 425 mW for the 589 nm yellow laser, 193 mW for the 560 nm lime laser, and 605 mW for the 533 nm green laser, with corresponding pulse widths of approximately 3.8, 3.6, and 35.1 ns, respectively. This result shows that a passive Q-switching operation with self-Raman crystals presents a promising approach for compact multi-wavelength pulse laser sources. Full article

Considering the complexity of laser cutting technology, and difficulties and limitations when applying traditional multi-criteria decision-making (MCDM) methods, this study proposes a fuzzy MCDM methodology for the analysis of the fibre laser cutting process, assessment of alternative cutting conditions and selection of favourable cutting conditions. The experiment in fibre laser cutting of mild steel was based on a Box–Behnken design by considering three input parameters (focus position, cutting speed and oxygen pressure) and four relevant criteria for the assessment of cutting conditions (kerf width on a straight and curved cut, surface roughness and surface productivity). The proposed fuzzy MCDM methodology makes use of expert knowledge and experimental data for criteria evaluation and decision matrix development, respectively, while three fuzzy MCDM methods (fuzzy TOPSIS, fuzzy WASPAS and fuzzy ARAS) were used to determine the complete ranking of alternatives. Kendall’s tau-b and Spearman’s rho correlation tests were applied to compare the obtained ranking lists, while the stability of the ranking was assessed with the application of the Monte Carlo simulation. Finally, to approximate the fuzzy decision-making rule, a second-order model was developed to reveal the significance of process parameters and identify favourable laser cutting conditions. Full article

Perforated materials are widely used in various fields, including in medicine, for example, in trays for placing and storing cutting tools and for sterilizing disposable materials. Currently, the effective elastic modulus of orthopedic plates is higher than the effective elastic modulus of human bone tissue (the effective elastic modulus of bone ranges between 10 and 30 GPa, depending on the type of bone). This difference in effective elastic modulus leads to the phenomenon known as the stress shielding effect, where the bone experiences insufficient mechanical loading. One potential approach to influence the effective elastic modulus of orthopedic plates is through perforations in their design. Stainless steel 316L has garnered significant interest among medical engineering specialists due to its lower weight, higher strength, and superior biocompatibility. The elastic properties of perforated constructions are influenced by their internal quality, dimensions, shapes, and the overall perforation area, making their study important. An experiment was conducted on perforated plates of 316L stainless steel with perforation areas ranging from 3% to 20%. Increasing the perforation area in perforated 316L stainless steel plates (perforated plates had dimensions of 50 mm in height, 20 mm in width, and 1 mm in thickness; hole diameter of 1 mm; and pitch between the holes of 2, 3, 4, and 5 mm) from 3% to 20% resulted in a decrease in Young’s modulus of the perforated plates from 199 GPa to 147.8 GPa, determined using a non-destructive method for determining resonant frequencies using a laser vibrometer. A three-point bending test on the perforated plates confirmed these findings, demonstrating a consistent trend of decreasing Young’s modulus with increasing perforation area, from 194.4 GPa at 3.14% to 142.6 GPa at 19.63%. The three-point bending method was also employed in this study to determine the Young’s modulus of the perforated plates in order to reinforce the obtained results on the elastic properties by determining the resonance frequencies with a laser vibrometer. It was discovered that the Young’s modulus of a perforated plate cannot be determined solely by the perforation area, as it depends on both the perforation diameter and the pitch between the perforations. In addition, finite element method (FEM) simulations were conducted, revealing that increasing perforation diameter and decreasing pitch significantly reduce the Young’s modulus—with values dropping from 201.5 GPa to 72.6 GPa across various configurations. Full article

Background/Objectives: Akin osteotomy, in the context of corrective surgery for hallux valgus, is an effective tool available to surgeons. However, few studies have thoroughly investigated the anatomical and technical characteristics to be considered in order to perform an optimal osteotomy. This cross-sectional observational study aims to identify the ideal site for performing Akin osteotomy and to identify the factors that influence its corrective power. Methods: To this end, an analysis was conducted on a random sample of 100 patients (186 feet) who underwent X-rays without surgical treatment. Variations in the width between the metaphysis and diaphysis were measured at five different points. For each cut level, corresponding to wedge bases of 2, 3 and 4 mm, three corrective angles were calculated. In addition, the distance between the cut line and the joint was recorded. Results: The base width ranged from 12.6 to 23.2 mm, showing greater variability in the metaphyseal region. The corrective power of the osteotomy showed wide variability, ranging from 5.9 to 18.4 degrees. Four determining factors emerged: the width of the base, the inclination of the medial cortex, the height at which the cut is made and the thickness of the wedge of bone removed. The data obtained suggest that osteotomy should not be performed less than 10 mm from the joint line to avoid the risk of joint invasion. Conclusions: In conclusion, there is no universally ideal site for performing an Akin osteotomy: the choice depends on the degree of correction desired, which in turn is influenced by the factors identified in the study. Full article

Additive manufacturing, particularly Fused Filament Fabrication (FFF), provides notable advantages such as design flexibility and efficient material usage. However, components produced via FFF often exhibit suboptimal surface quality and dimensional inaccuracies. Acrylonitrile Butadiene Styrene (ABS), a widely used thermoplastic in FFF applications, commonly necessitates post-processing to enhance its surface finish and dimensional precision. This study investigates the effects of CO₂ laser cutting on FFF-printed ABS plates, focusing on surface roughness, top and bottom kerf width, and bottom heat-affected zone. Forty-five experimental trials were conducted using different combinations of plate thickness, cutting speed, and laser power. Measurements were analysed statistically, and analysis of variance was applied to determine the significance of each parameter. To enhance prediction capabilities, seven machine learning models—comprising traditional (Linear Regression and Support Vector Regression), ensemble (Extreme Gradient Boosting and Random Forest), and deep learning algorithms (Long Short-Term Memory (LSTM), LSTM-Gated Recurrent Unit (LSTM-GRU), LSTM-Extreme Gradient Boosting (LSTM-XGBoost))—were developed and compared. Among these, the LSTM-GRU model achieved the highest predictive performance across all output metrics. Results show that cutting speed is the dominant factor affecting cutting quality, followed by laser power and thickness. The proposed experimental-computational approach enables accurate prediction of laser cutting outcomes, facilitating optimisation of post-processing strategies for 3D-printed ABS parts and contributing to improved precision and efficiency in polymer-based additive manufacturing. Full article

Tropical trees represent an important potential archive of climate and ecological information, but their dendrochronology based on conventional techniques has been challenging. We conducted a pilot study of the wood anatomy and dendroclimatological potential of Juglans neotropica Diels (Juglandaceae), an IUCN Red List species, using 225 radii sampled from 57 trees in Piura (4°55′ S, 79° 56′ W), northern Peru. A total of 112 radii from 40 trees passed quality control and are included in the tree-ring width chronology for this species. J. neotropica has demonstrably annual rings, and results are consistent with reports that the species has a dormant period during the dry season, which locally is approximately June–November. Local precipitation is correlated (p = 0.10, 1-tailed test) with tree-ring growth, lagged by one year, consistent with other studies of tropical tree species. The age distribution of the sample collection of J. neotropica is young and invariant, probably because of selective cutting by local villagers. To supplement ring-width analysis, we conducted the first oxygen isotopic (δ¹⁸O) and radiocarbon (∆¹⁴C) analysis for this species on radii from two individuals; results are preliminary given sample size limitations, but consistent with dendrochronological dating, within uncertainties, in all three chronometric analyses. A two-sample composite annually-averaged δ¹⁸O anomaly data series is correlated significantly with gridded regional growing season (December–May) precipitation (1973/74–2005/06). Qualitatively consistent with simulation of ring width and δ18O, responses to El Niño events are manifested in positive ring-growth anomalies and negative isotopic anomalies following known event years. The combination of tree-ring, radiocarbon, stable isotopic analyses, and the application of sensor and chronological modeling provides a degree of confidence in the results that would not have been possible by relying on any single approach and indicates the potential for further investigation of this and other tropical tree species with uncertain ring boundaries. Full article

The miniaturization of smart materials has become a new trend in the modern manufacturing industry due to its enormous application in the aerospace, biomedical, and automobile sectors. Nickel–titanium (NiTi)-based binary shape memory alloys (SMAs) are one of the smart materials with certain supreme features like shape memory effect, pseudo-elasticity, high ductility, strong corrosion-resistance, and elevated wear resistance. For this, several micro-machining processes have been developed to machine NiTi SMAs. This paper summarizes all of the conventional and non-conventional micro-machining processes employed to machine NiTi SMAs. In this review process, the surface integrity, dimensional accuracy of the machined surface, cutting force and tool wear analysis during conventional and non-conventional micro-machining of NiTi SMA are evaluated mostly with the aid of input process variables like cutting speed, depth of cut, width of cut, types of coolants, tool coating, discharge voltage, capacitance, laser fluence, pulse duration, scan speed, electrolysis concentration and gap voltage. The optimization of process parameters using different methods during conventional and non-conventional micro-machining of NiTi SMAs is also analyzed. The problems faced during conventional micro-machining of NiTi SMAs are overcome by non-conventional micro-machining processes as discussed. The present study aims to recognize potential developments in the improvement of the micro-machinability of NiTi SMAs. Full article

Modern manufacturing technologies include wood processing using laser technologies. The most used laser for wood cutting is the CO₂ laser, which offers many advantages such as processing speed, efficiency, and minimal impact on the material’s structure after cutting. To achieve a high-quality cut, characterized by the cutting kerf parameters, it is necessary to know the appropriate combination of cutting parameters, primarily laser power (P) and the cutting speed (v). Therefore, this article investigates the effect of P, v, and cutting direction on the cutting kerf widths on the upper surface WKU, lower surface (WKL), and their ratio (WKR). The analysis was performed on samples of spruce, beech, and oak wood, while also evaluating the influence of the anatomical cutting direction. The correlation coefficient between the predicted values and the measured values is at least 0.94, with the mean square error not exceeding 4%. Consequently, the employed models demonstrate validity in predicting cutting kerf widths and optimizing the cutting process based on the type of timber, cutting direction, and the specified laser parameters. Full article

With the continuous scaling of CMOS technology, stress engineering has become increasingly critical at advanced technology nodes, especially in tall and narrow FinFET structures. Asymmetric layout environments (such as dual-Fin structures or poly cuts) can introduce stress imbalance originating from shallow trench isolation (STI), which in turn affects device performance. In this study, TCAD simulations were performed on n-type FinFETs representative of the 10 nm technology node, with a physical gate length of 20 nm, to investigate the correlation between asymmetric stress and device drive current. As the Fin width decreases, the asymmetric stress from STI induces noticeable performance fluctuations, with the mobility enhancement under saturation bias reaching a maximum of 8.42% at W = 6 nm. Similarly, as the Fin body angle deviates from 90° and the Fin top narrows, with W_top = 6 nm and W_bottom = 8 nm, the mobility enhancement peaks at 7.65%. The simulation results confirm that STI-induced asymmetric stress has a significant impact on the Fin sidewall channel, while its effect on the top channel is minimal. To mitigate these effects, CESL stress engineering is proposed as an effective solution to amplify the top channel current, thereby reducing the influence of asymmetric stress on device performance. A CESL stress of 2.0 GPa is shown to improve device stability by approximately 20%. Full article

The overload protection device is crucial in ensuring the orderly absorption of kinetic energy by the coupler buffer device. This paper studies an overload protection bolt with a cut-out zone. In the bolt impact experiment, a premature fracture of 10.9-grade M24 bolts was observed. Based on the analysis of the results, it was concluded that this phenomenon was caused by the mismatch between the mechanical properties of the bolts and the dynamic performance of the coupler. Building on this test, a numerical simulation model was established and subsequently validated. The width and depth of the inducing structure were selected as the research objects. Using the Latin Hypercube method, 78 sets of cut-out zone structure parameters were generated, and numerical simulations were performed on the cut-out induced bolts. The simulation results indicate that the peak force generated by the coupler collision leads to necking in the cut-out induced bolts, which consequently weakens their mechanical properties to some extent. Therefore, it is necessary to consider a strength margin when designing cut-out induced bolts. Based on the simulation results, a surrogate model was constructed, and the optimal bolt cut-out zone was obtained through optimization: a width of 17.74 mm and a depth of 1.37 mm. The surrogate model predicted a fracture force of 1894.13 kN for the bolts. An impact test was conducted to verify the performance of the optimized cut-out induced bolts. The experimental results showed that the cut-out induced bolts broke after the crush tube completed its kinetic energy absorption, with a fracture force of 1828.44 kN, which was a 3.59% difference from the predicted value of the surrogate model. After optimization, the fracture force of the cut-out induced bolts increased from 1147.5 kN to 1828.44 kN (a 59.34% improvement), while the fracture time extended from 20.9 ms to 69 ms, fully meeting the design requirements of the overload protection device. Full article

In the production process of cross-cutting boards, real-time measurement of dimensions online has been a long-standing technical problem in the production field. Currently, the detection of board dimensions in the production field relies on manual observation based on workers’ operational experience or stopping the machine for measurement. This paper proposes a machine vision-based real-time online measurement system for dimensional measurements of cross-cutting units. A certain angle measurement model is established by using a face-array industrial camera, and a more accurate edge contour extraction is realized by deep learning. A novel edge intersection extraction algorithm based on line fitting and least squares method was proposed to accurately measure the length, width, diagonal lines of cross-cutting boards using four intersection coordinates. The measurement of 100 cross-cutting boards in the industrial production site shows that the proposed online measurement system for cross-cut board dimensions in this article has high accuracy, with a length perception error of ±50 mm, width of ±2 mm, and diagonal difference of ±5 mm, meeting the production requirements in industrial settings. The on-site shutdown measurement work was reduced, thereby doubling the production efficiency and saving two staff members. Full article

Background/Objectives: Red blood cell (RBC) parameters are routinely used to screen for α- and β-thalassemia traits as part of prenatal diagnosis for severe fetal thalassemia in countries with a high prevalence of the disease. In clinical practice, the same cut-off values for these parameters are applied to both females and males. However, given that the normal reference ranges for some RBC parameters differ significantly between sexes, sex-specific cut-off values may be more appropriate, especially in combination. To date, the effectiveness of RBC indices in males for predicting α- and β-thalassemia traits has not been evaluated. The objectives of this study are to assess the diagnostic performance of individual and combined RBC parameters in detecting α⁰-thalassemia traits among non-anemic males. Methods: This diagnostic study is a secondary analysis of prospectively collected data from our project on prenatal control of severe thalassemia. The study population comprised male partners of pregnant women who underwent thalassemia screening during their first antenatal visit. RBC parameters, including hemoglobin (Hb), hematocrit (Hct), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), and RBC count, were measured for each participant. Carrier status for the α0-thalassemia Southeast Asian (SEA) genotype was confirmed by using a polymerase chain reaction (PCR)-based method. The diagnostic performance of each RBC parameter and their combinations, based on predictive models generated using logistic regression, was evaluated and compared using receiver operating characteristic (ROC) curves. Results: A total of 486 Thai males were recruited for the study, including 137 individuals with the α⁰-thalassemia trait and 349 with a normal α-thalassemia genotype (control group). All RBC parameters, except for Hct, differed significantly between the two groups. Among the individual indices, MCH exhibited the highest diagnostic accuracy, followed by MCV, with areas under the curve (AUCs) of 0.981 and 0.973, respectively. An MCH cut-off value of 26 pg and an MCV cut-off value of 80 fL provided a sensitivity of 100% for both indices, with specificities of 88.5% and 86.8%, respectively. The combination predictive model provided the best diagnostic performance, achieving an AUC of 0.987, which was slightly but significantly higher than that of any individual parameter. This model yielded a sensitivity of 100% and a significantly higher specificity of 90.8% at a cut-off probability of 7.0%. Conclusions: MCH and MCV demonstrated excellent screening performance for identifying α0-thalassemia carriers in males. However, the combination model exhibited even greater accuracy while reducing the false-positive rate. Implementing this model could minimize the need for unnecessary PCR testing, leading to substantial cost savings. Full article