Hair-like surfaces in nature consist of high-aspect-ratio fibers with diameters below 100μm, falling to several tens of micrometers in softer hairs. These fine fiber arrays govern tactile softness, flexibility, surface texture, and mechanical response. Conventional fiber-spinning methods produce fine fibers effectively but offer limited control over the position, direction, and patterned arrangement of individual fibers. Here we propose a fused deposition modeling (FDM)-based strategy that combines melt extrusion with geometric drawing to fabricate PLA hair-like fibers. PLA melted fully at the processing temperature of 250oC, well below the thermal degradation onset near 330oC. DSC analysis showed that faster cooling suppressed thermodynamic crystallization, indicating that the final fiber structure is governed by drawing history and rapid cooling rather than by increased crystallinity. As the printing speed increased, the fiber diameter decreased nonlinearly, following D ≈ 106.3 v-0.45, in excellent agreement with the D v-0.5 scaling predicted by the continuity equation. Tensile strength and modulus increased with printing speed, whereas elongation and toughness decreased, indicating drawing-induced molecular orientation. These results demonstrate that FDM can serve as a programmable platform for fabricating biomimetic hair-like fiber arrays with predictable diameter and mechanical properties.
This study investigated the ultrasonic fatigue behavior of ABS and of a high-strength photopolymer resin (Rigid Black) fabricated by digital light processing (DLP) additive manufacturing. The dynamic elastic modulus of both materials was measured so that specimens could be designed to satisfy the 20 kHz resonance condition. ABS specimens were CNC-machined, whereas Rigid Black specimens were DLP-printed and post-cured. Thermal effects were minimized by compressed-air cooling with a 0.3 s/3 s duty cycle. S-N curves showed that fatigue life increased as the stress amplitude decreased for both materials. ABS exhibited higher fatigue strength and a more consistent life distribution, which is attributed to its homogeneous microstructure. Rigid Black showed lower fatigue strength with greater scatter, reflecting the anisotropy and interfacial inhomogeneity introduced by layer-by-layer fabrication. Fractographic analysis revealed that ABS underwent mixed-mode ductile-fatigue fracture through crazing, whereas Rigid Black failed in a brittle manner, with directional crack propagation driven by process-induced defects. These results confirm the feasibility of ultrasonic fatigue evaluation for DLP-printed polymer components and provide a basis for assessing the durability of additively manufactured parts.
This study examined how knee sleeve application affects the knee adduction moment (KAM), knee adduction angle (KAA), and knee muscle activation during gait in eleven healthy individuals. Participants completed walking trials under four conditions: a control condition without a sleeve (Normal) and three sleeve conditions with distinct compression characteristics (Motion, Slim, and Strong). KAM, KAA, and surface electromyography (EMG) from five lower limb muscles were compared across conditions. Neither KAM nor KAA differed significantly among the conditions (p > 0.05). In contrast, knee extensor EMG was lower under specific sleeve conditions than under Normal (p < 0.05). Because muscle forces contribute substantially to knee contact force during gait, this reduced activation may indicate lower internal knee joint loading. These findings suggest that, in healthy individuals, certain knee sleeves may alter neuromuscular strategies without producing detectable changes in KAM or KAA, although further validation is needed.
3D printing is emerging as a promising solution for the automotive industry, as it offers economic advantages in smallbatch, high-variety production and mitigates climate impact by eliminating mold fabrication. This study compares the carbonemission reduction potential and economic feasibility of fused deposition modeling (FDM)—the most widely used polymer 3D printing process—with those of conventional injection molding at the actual component level. The analysis shows that the environmental burden of mold manufacturing in injection molding is substantial, confirming the advantage of FDM in low-volume production. Specifically, for production volumes below 645 units, FDM performs better in reducing carbon emissions. These findings indicate that FDM can serve as a sustainable alternative for low-volume manufacturing in automotive applications.
This study proposes a human-in-the-loop framework that integrates operator observations into a large language model (LLM) to control process parameters for defect handling in fused deposition modeling (FDM) 3D printing. Fully autonomous LLM-based control handles ambiguous sensor data poorly and cannot detect abnormal conditions that lie beyond the installed sensors. Operator observations may compensate for these limitations, but their actual impact on LLM decision-making has not been sufficiently validated. We therefore implemented the proposed framework and defined experimental scenarios involving erroneous parameter injection and environmental disturbances. The framework was evaluated in terms of LLM response quality and print quality. The LLM achieved over 80% response quality on the defined evaluation metrics and generated appropriate parameter adjustments, improving print quality by more than 55% on average. Comparative experiments further revealed that, without operator observations, the LLM sometimes failed to recognize defects. These findings demonstrate the effectiveness of human–LLM collaboration and provide a practical foundation for intelligent FDM process control.
Cooperative 3D printing (C3DP) with multiple robotic manipulators can reduce build time through parallel deposition, but it requires layer partitioning that accounts for collision clearance, workload balance, G-code toolpath compatibility, and interlayer boundary alignment. This study presents a Voronoi- and graph-based layer partitioning framework for C3DP. STL geometry and G-code were integrated into layer-aligned data, and a 65 mm collision clearance was defined from the measured end-effector collision radius as the minimum separation preventing collisions between robots approaching nonadjacent Voronoi cells. Each layer was divided into Voronoi cells so that non-adjacent cells could be treated as collision-free regions. Cell adjacency and toolpath-based processing time were modeled as a weighted graph, and adjacent cells were clustered into workload-balanced task regions. Interlayer seed offsets staggered the partition boundaries, and graph coloring identified regions that could be printed simultaneously.The framework was evaluated by workload-balance simulations and printing experiments. Balance deteriorated when clusters were excessive relative to graph nodes. In experiments, the end-effector separation always exceeded the 65 mm clearance. Partitioned printing reduced the layer printing time from 70.063 to 63.57 min, a 9.3% reduction, and the second layer covered the preceding partition boundary, confirming the staggered-boundary implementation.
Variable inlet guide vane (VIGV) control is among the most energy-efficient flow regulation methods for axial pumps because it adjusts the inlet swirl angle directly while preserving high hydraulic efficiency. However, unlike rotational-speed control, whose performance curves scale straightforwardly through the affinity laws, VIGV control alters the intrinsic shape of the head-flow (H-Q) curve at each vane angle and therefore requires angle-specific prediction. This study proposes a transition-informed Gaussian process regression (TI-GPR) model that augments standard GPR by explicitly incorporating the gradient sign-reversal point of the S-shaped characteristic curve through adaptive region splitting and sigmoid-based blending. A four-factor evaluation covering CV strategy, training-data sparsity, input dimensionality, and model type shows that, even when only Q–H data are available (2D input), TI-GPR lowers the relative MAPE by 17.525% under sparse interpolation and by 35.938% under extrapolation relative to the baseline GPR model. Adding valve-position information (3D input) improves the accuracy of both models further, and TI-GPR retains its advantage. These results demonstrate that a minimal structural modification embedding the stability-gradient transition boundary can yield substantial predictive gains, particularly in data-scarce regimes.
In this work, Mg1-xZnxO thin films were deposited on glass substrates by the pneumatic spray technique at 450°C using a 0.15 M precursor solution of magnesium acetate and zinc acetate. The effect of Zn content (x = 0, 0.3, 0.5, and 0.7%) on the structural, morphological, optical, and electrical properties of the films was examined. XRD analysis showed that all films adopted a cubic MgO structure with diffraction peaks from the (111), (200), and (220) planes, and the crystallite size grew from 8.12 to 12.49 nm as the Zn content increased. SEM images indicated that moderate Zn incorporation improved film homogeneity, whereas higher Zn contents promoted agglomeration and surface roughening. The films transmitted well in the visible region, and the optical band gap widened from 3.56 to 3.93 eV at x = 0.3. The Urbach energy also rose with Zn content, reaching a maximum of 0.695 eV at x = 0.7, which indicates greater structural disorder. FTIR spectra confirmed that Zn incorporation modifies the chemical bonding network. The sheet resistance increased markedly with Zn content, demonstrating the strong influence of Zn doping on the optical and electrical properties of MgO thin films.
This study proposes a hybrid wire arc directed energy deposition (WA-DED) process that uses 3D sand-printed supports to overcome the limitations of low-angle overhang fabrication. WA-DED is a metal additive manufacturing process offering high deposition rates, cost efficiency, and suitability for large-scale components. However, because of its high heat input and molten pool instability, low-angle overhang and hollow structures remain difficult to fabricate, as the molten metal tends to collapse under gravity and thereby degrade geometric accuracy and surface quality. To address this issue, sand-printed supports were introduced. The supports provide tailored mechanical constraint and guide the solidification of the molten pool during deposition. Experiments were conducted to evaluate the feasibility of the proposed process at various overhang angles. The results show that the hybrid process markedly improves deposition stability and enables the fabrication of low-angle and curved overhang structures that conventional WA-DED cannot produce. These findings confirm the effectiveness of sand-supported WA-DED and highlight its potential for industrial applications requiring complex geometries, such as aerospace, marine, and energy components.
Demand for high-performance bonded magnets with complex geometries is growing in electric motors, sensors, and energy devices. In lithography-based composite manufacturing (LCM), the magnetic properties of anisotropic NdFeB composites depend strongly on particle alignment during curing. This study compares the magnetic characteristics of 70 wt% NdFeB composites fabricated under magnetic-field-assisted and non-aligned conditions. An in situ alignment module was integrated into the manufacturing platform to induce directional particle orientation. The magnetic flux distribution was analyzed in ANSYS Maxwell, and particle alignment behavior was simulated by discrete element method (DEM) modeling in ANSYS Rocky. Vibrating sample magnetometry confirmed that magnetic-field-assisted processing enhances the anisotropic magnetic response, in agreement with the simulation predictions.
This paper describes the calibration of a 2D vision system utilizing a high-precision robot that moves accurately along the z-axis. To achieve this, a one-axis high-precision robot was designed and manufactured, achieving a minimum travel distance of 0.007 μm during testing. The 2D vision system comprised an RGB camera, an LVDT sensor, and a laser sensor for distance measurement. Additionally, a subpixel-based algorithm was developed for the calibration and size measurement of the system. Following the calibration process with the high-precision robot, the size error was found to be within ±0.1 mm when using the LVDT sensor and ±0.2 mm with the laser sensor. Thus, the 2D vision system and calibration algorithm presented in this paper are deemed suitable for accurate object measurement by robots.
Direct-drive robot arms, often utilized in manipulators and humanoid robots, face challenges related to increased distal mass and reduced backdrivability due to motors being placed at each joint. This paper presents a 4-DOF elbow-wrist mechanism for a robot arm driven by wires. The design includes the upper arm, elbow, upper forearm, lower forearm, and wrist, with all actuators concentrated in the upper arm to minimize distal mass. To achieve this, the mechanism employs rolling-contact joints, forearm rotator idlers, and agonist-antagonist wire pairs. Additionally, a differential mechanism is integrated at the wrist, allowing for yaw rotation at the forearm while enabling roll and pitch rotations at a single point, thereby eliminating inter-axis offset and mimicking human wrist motion. A prototype was fabricated and evaluated, achieving an elbow flexion of 107°, forearm yaw exceeding 90° in both directions, wrist roll of 63° and 50° in each direction, and wrist pitch of 33° in both directions. The independence of each degree of freedom was validated, and torque efficiency from the upper arm to the wrist tip was measured and analyzed.
This study quantitatively investigates the deviation between the ideal and effective amplification ratios of a bridge-type displacement amplification mechanism used in ultra-precision positioning systems. It proposes region-specific optimal design strategies to mitigate this deviation. A Leave-One-Out sensitivity analysis reveals that the dominant factor influencing amplification ratio deviation shifts at an ideal amplification ratio of approximately 10. In the high-amplification region (R > 10), displacement loss due to bending of the input link is identified as the primary cause of deviation. Reinforcing the input link's thickness and incorporating a pocket structure reduces the deviation to within 12.4% while minimizing resonance frequency degradation. Conversely, in the low-amplification region (R < 7), the main issue is dynamic performance deterioration caused by oversized intermediate links. Implementing a hexagonal mass-reduction design enhances the first resonance frequency by up to 28% without compromising the amplification ratio. These findings establish differentiated design guidelines based on the target amplification ratio, enabling simultaneous improvements in precision and dynamic performance for bridge-type displacement amplification mechanisms in positioning systems.
This study presents a Python-based design tool that utilizes a data-driven backtracking method for aspheric coefficients to effectively address thermal deformation in aspheric glass lenses produced by the Glass Molding Press (GMP) process. To achieve the nanometer-level form accuracy essential for optical communications and high-power laser applications, it is crucial to compute compensation coefficients through nonlinear least-squares fitting of the lens's measured data to the standard aspheric equation. The proposed tool enhances user-friendliness with a PyQt GUI and incorporates the lmfit library, offering unique flexibility by allowing users to select or fix specific variables among up to 22 parameters, including the radius of curvature, conic constant, and aspheric coefficient, during the fitting process.
Military shelters house various high-power electronic systems that generate significant heat during operation, making effective thermal management essential for ensuring system reliability and operational stability. This study proposes a one-dimensional (1D) modeling approach for analyzing the thermal behavior of a military shelter–HVAC system using Simcenter AMESIM. The model incorporates key thermal components, such as internal heat sources, shelter structures, and HVAC performance characteristics, to accurately represent dynamic thermal behavior under realistic operating conditions. To validate the proposed 1D model, a comparative analysis was performed using threedimensional computational fluid dynamics (CFD) simulations with ANSYS Fluent, maintaining identical boundary and operating conditions. The analysis focused on the temporal and spatial variations of the internal air temperature within the shelter. Results showed a strong correlation between the AMESIM model and the CFD simulations. This approach significantly reduces computational costs and modeling complexity compared to traditional CFD-based analyses, while still providing adequate accuracy for system-level thermal performance evaluation. Consequently, the developed AMESIM-based 1D model serves as an efficient and reliable tool for the design and performance assessment of military shelter HVAC systems.
Ti-6Al-4V titanium alloy is widely utilized in aerospace components, such as torque tubes and turbine blades, due to its outstanding strength-to-weight ratio and corrosion resistance. However, controlling surface roughness during machining is challenging because the alloy's low thermal conductivity and high chemical reactivity result in unpredictable variations in Ra. Traditional contact-based measurement methods are not only time-consuming but also incompatible with in-process monitoring, creating a disconnect between production and quality control. This study introduces a CNN-LSTM hybrid model for predicting surface roughness in Ti-6Al-4V shape machining, utilizing multi-sensor CNC data. The model effectively captures spatial correlations among nine sensors and temporal dependencies in sequential operations. We implement a stratified time-series split validation that maintains chronological order while ensuring a representative distribution of Ra values, reflecting realistic deployment conditions. Data were collected from machining tests on features of a torque tube part, comprising 4,154 samples with Ra values ranging from 0.57 to 0.74 μm. The CNN-LSTM model achieved R² = 0.8512, RMSE = 0.0199 μm, and MAE = 0.0096 μm, outperforming Random Forest, XGBoost, and standalone neural networks. These results demonstrate the feasibility of non-contact, in-process surface roughness prediction in aerospace manufacturing, facilitating proactive quality control without interrupting operations.
Trunk balance is essential for physical stability, but traditional assessment tools, such as force plates and 3D motion capture systems, can be inaccessible or unsafe for patients unable to stand. This study introduces a seated trunk balance training and assessment system that combines a tilting chair with an Inertial Measurement Unit (IMU). The system features a kinematic design that transmits the user's trunk movements to the chair's seat, allowing for quantitative measurement without the need for body-mounted sensors. A pilot study was conducted to evaluate technical feasibility by comparing a seat-mounted sensor (CS-IMU) with a reference sensor (T12-IMU) attached to the T12 vertebra. Assessment items included Range of Motion (RoM), rotation accuracy, and agility. Results indicated a very high correlation for lateral bending (r = 0.958) and rotation phase angle (r = 0.990), while flexion/extension showed a moderate correlation (r = 0.691). Additionally, agility tasks demonstrated consistent results in the lateral direction (r = 0.806). These findings suggest that the proposed system can effectively quantify multi-dimensional trunk movements in a seated position, making it a valuable tool for high-risk populations, such as patients recovering from acute stroke or spinal cord injuries.
Dual-drive H-type gantry stages, powered by direct-drive linear motors, are commonly used in precision industrial applications that require high positioning accuracy over a large workspace. The cross-arm rigidly couples the two parallel axes, making strict synchronization control essential for maintaining positioning accuracy. Conventional master-master control treats the coupling effects as disturbances without accounting for the synchronization of the two motors. As a result, its performance deteriorates significantly under non-uniform load distribution, payload rotation, and directly applied torque disturbances, all of which necessitate reliable synchronization control. This study proposes a synchronization control scheme that integrates a sliding-mode controller with an uncertainty and disturbance estimator (SMC-UDE) and a feedforward torque compensator for the inertial torque induced by payload rotation. The proposed controller was implemented on a Hardware-in-the-Loop (HIL) simulator constructed with two parallel voice coil motors, and its performance was experimentally validated on the testbed. The HIL experimental results demonstrate that the SMC-UDE controller with feedforward torque-disturbance compensation achieves a quicker settling time compared to the conventional master-master control strategy. Additionally, it effectively suppresses disturbances generated by a rotary motor attached to a payload, thereby maintaining synchronization accuracy under disturbed conditions.
Cable chains are essential for guiding and protecting cables in repetitive linear-motion equipment. However, during highspeed operations, inertial effects and structural deformation can lead to position overshoot beyond the intended stroke, resulting in off-path motion and increased stress concentrations in links and joints. This study assesses the structural stability of a U-shaped cable carrier under conditions of position overshoot and suggests an optimized geometry. To analyze this, a nonlinear finite element model is employed, constraining one end of the carrier while applying a prescribed overshoot displacement to the other end. Structural stability is measured using a stability index, which is defined as the maximum reaction force at the point of yielding, when the equivalent (von Mises) stress reaches the material's yield stress. A sensitivity analysis identifies the key geometric design variables, and response surface methodology is applied to find an optimal shape that maximizes the reaction force at yielding. The proposed simulation-driven workflow offers practical design guidance for enhancing the stability of cable carriers during non-ideal overshoot events.
The development of high-performance lithium-ion battery electrodes necessitates reducing the content of conductive additives while preserving excellent electrochemical properties. In this study, multi-walled carbon nanotubes (CNTs) with approximately 3 to 7 walls were synthesized and characterized using transmission electron microscopy (TEM), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA) to confirm their morphology and purity. Electrical conductivity was assessed through powder resistivity measurements. CNT dispersions were prepared by ultrasonic treatment using N-methyl-2-pyrrolidone (NMP, 95 wt%), a dispersant (2 wt%), and CNTs (3 wt%). Thin films coated on glass slides showed surface resistances of 36 Ω/sq, indicating superior electronic conductivity compared to conventional carbon black. The optimized CNT dispersion was then mixed with NCM613 cathode active material and a binder to create electrodes containing only 1 wt% conductive additive. For comparison, reference electrodes were also prepared using conventional carbon black at a loading of 2.2 wt%. Electrochemical testing revealed that the CNT-based electrodes achieved comparable cycling stability, rate capability, and capacity retention, despite having a lower conductive additive content. These results demonstrate the feasibility of reducing conductive additive loading to 1 wt% by utilizing highly conductive CNTs, thereby increasing the proportion of active material and enhancing overall energy density.
