This study experimentally investigates the laser-assisted diamond turning of high-hardness sapphire to enhance its precision machinability for defense optical components. Sapphire is an attractive material for applications such as transparent armor, sensor windows, and optical apertures due to its excellent mechanical strength, thermal and wear resistance, and outstanding optical transparency. In this research, precision cutting tests were performed on a diamond turning machine, and the resulting surfaces were characterized using a white-light interferometric profilometer. At an optimal laser power of 5 W, the surface roughness and form accuracy improved to 28.8 nm Ra and 191 nm RMS, respectively, demonstrating that laser assistance can significantly enhance surface quality. Microscopic observations after processing revealed a noticeable reduction in tool wear under laser-assisted conditions, which is likely to improve process stability and extend tool life. However, both insufficient and excessive laser power resulted in degraded surface quality compared to conventional turning, underscoring the importance of optimizing laser power. These findings highlight the potential for process optimization in laser-assisted diamond turning to improve the precision and reliability of sapphire machining, contributing to the future development of advanced manufacturing technologies for high-precision defense components.
Pad conditioning restores degraded pad surfaces after wafer polishing in chemical mechanical planarization (CMP) using diamond-embedded conditioner discs. However, conditioning also causes pad cutting, thickness reduction, and profile deformation. While previous studies mainly focused on reducing pad cut rate (PCR) and improving profile uniformity, the fundamental cutting mechanism between conditioner cutting edges and the pad remains unclear. This study investigates the cutting mechanism using CVD conditioner discs with different cutting edge densities under varying conditioning loads to control contact area and load distribution. PCR and pad profile analyses revealed that cutting behavior is primarily governed by the load applied to individual cutting edges. Higher localized loads increased the contribution of cutting to overall material removal. In the pad edge region, where the conditioner partially overhangs the pad, altered contact geometry caused a transition in cutting mode. In this region, the number of active cutting edges had a greater influence than the load per edge. These findings clarify the cutting interactions between CVD conditioner edges and pad surfaces during conditioning and provide a physical foundation for optimizing conditioning parameters to improve pad management in CMP processes.
Due to the high risks of manual labor in the steel industry, there is a growing demand for robot-based solutions to replace traditional manpower. Steel companies aim to reduce on-site personnel, minimize accidents, and enhance productivity. This study develops a robotic system to monitor conveyors in ironmaking and detect potential bearing failures. Rollers on belt conveyors contain bearings that emit abnormal noise when worn or damaged. Traditional manual inspection requires workers to approach each roller and listen directly, posing safety risks and inefficiencies. The proposed system detects faulty bearings more quickly and accurately by localizing abnormal sounds. The system comprises a manipulator with a microphone on its end-effector. The microphone collects sound along the conveyor as the manipulator moves to detect noise sources. Once an abnormal bearing is located, faster and more accurate maintenance becomes possible. This robotbased inspection method improves safety, inspection speed, and productivity.
In the rapidly evolving e-commerce industry, high-quality and consistent product images are essential for engaging consumers. Traditional manual photography often lacks consistency, while advanced robotic solutions can be overly complex and expensive for standardized cataloging. This paper details the design and validation of a 4-DOF (Degrees of Freedom) automated system for standardized product photography. The system employs a modular, fixed-platform architecture that adjusts camera height, tilt angle, object rotation, and perspective translation. An integrated control system facilitates automatic pose planning based on object size, ensuring efficient operation. We quantitatively evaluated the system's performance using metrics for perspective consistency and repeatability. Experimental results across various product types showed high stability, with minimal variance in bounding box area ratios from different viewpoints. The system exhibited exceptional repeatability in random trials, consistently achieving pair Intersection over Union (IoU) values above 0.90. This high level of geometric precision confirms the system's reliability for capturing uniform, multi-angle product images. Ultimately, this capability allows for the scalable and automated production of high-quality visuals for e-commerce.
This paper introduces a real-time gait phase detection system and algorithm utilizing non-contact distance sensing, specifically designed for wearable robotic applications. Two Time-of-Flight (ToF) sensors are positioned on the outer heel and the fifth metatarsophalangeal (MTP) joint to monitor foot-to-ground distance throughout the gait cycle. These sensors are housed in overshoe-type modules to minimize interference with natural walking and allow for easy attachment to various types of footwear. The proposed method segments gait phases using a lightweight, thresholdbased algorithm that is both computationally efficient and physically interpretable. Experimental validation with a healthy subject shows that the system reliably detects stance and swing phases, producing temporal patterns that are comparable to those of conventional pressure-based systems. Importantly, the system provides continuous data even during swing phases, facilitating smoother transitions for control systems. The simplicity and wearability of the hardware indicate its potential for real-time control in lower-limb wearable robots, gait assistance devices, and ambulatory monitoring systems.
This study employed the Taguchi method to determine the optimal milling parameters for cast steel, aiming to minimize surface roughness. The analysis indicated that the feed rate was the most significant factor, with lower feed rates resulting in improved surface finish. In contrast, spindle speed and radial depth of cut had minimal impact, while axial depth of cut and tempering temperature emerged as crucial determinants. A linear regression model accounted for 87.46% of the variance in surface roughness. The predicted optimal conditions closely aligned with experimental results, yielding only a 2.93% error and achieving an average surface roughness of 3.033 μm. These findings provide a predictive framework for achieving the desired surface quality in milling processes.
Deep-sea optical windows must withstand extreme hydrostatic pressure while maintaining optical transmittance, requiring a balance between mechanical rigidity and optical performance. Increasing thickness enhances structural strength but reduces transmittance. This study proposes a design method for deep-sea optical windows using domestically developed sapphire. Three-point bending tests were conducted on sapphire and silicon specimens, and B-criterion strength was derived using Weibull distribution to account for brittle material properties. Optical transmittance measurements established key design characteristics. Using theoretical formulations for rectangular planar optical windows under uniform external pressure, the initial design was based on experimentally derived sapphire properties. Finite element analysis of the optical window assembly confirmed sufficient structural stability margins above critical thresholds. Linear interpolation was applied to evaluate the continuous design space across discrete thickness values. A compromise solution was identified that satisfies both structural rigidity and transmittance objectives. By integrating experimental material characterization with numerical analysis, this study provides an effective framework for determining the optimal thickness of deep-sea optical windows and confirms the applicability of domestically developed sapphire as a reliable optical window material for high-pressure underwater environments.
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.
The knee adduction moment (KAM) is commonly used as a surrogate measure of medial compartment loading in individuals with medial knee osteoarthritis. This study investigated the effects of four gait modification strategies—toe-in, toeout, trunk lean, and knee thrust—on KAM peak and impulse using a within-subject design. Fourteen healthy adults performed normal walking and each modified gait condition. All gait modifications significantly reduced KAM peak compared to normal gait (p<0.05). However, a significant reduction in KAM impulse was observed only during the toe-out gait (p<0.01). Multiple regression analysis revealed that the moment arm accounted for 89–92% of the variance in KAM peak, while the combined effects of moment arm and stance time explained 87% of the variance in KAM impulse (p<0.001). The decrease in impulse during toe-out gait was primarily driven by a lower KAM peak without a significant increase in stance time. In contrast, for the other gait modifications, reductions in KAM peak were counterbalanced by prolonged stance time, resulting in no overall reduction in impulse. These findings suggest that both KAM peak and impulse should be considered when selecting gait modification strategies, with toe-out gait appearing to offer the most favorable biomechanical response in healthy adults.
Optical motion capture (OMC) systems are widely used in rehabilitation, sports, and robotics to obtain accurate segment attitudes. However, OMC marker data can be lost due to occlusions, and reliably recovering data for long-duration missing intervals remains challenging. This study proposes a method for recovering missing markers using inertial measurement unit (IMU) signals and rigid-body constraints. We implemented two recovery methods and validated their performance. The proposed method (M1) combines inter-marker distance constraints with an acceleration constraint, while the comparison method (M2) combines inter-marker distance constraints with a tilt constraint. M1 demonstrated superior performance, with an average root mean squared error that was 3.10 and 3.99 mm lower than that of M2 for the 30 and 180 s missing intervals, respectively. This performance difference arises because M1 directly utilizes measured IMU signals, whereas M2 incurs additional uncertainty due to attitude estimation errors. Furthermore, the proposed method maintained reliable performance even during long-duration missing intervals, as it operates independently of past data, preventing recovery error accumulation. These results demonstrate the feasibility of the proposed IMU-based method for recovering longduration missing marker data in OMC systems.
This study presents a method for fabricating customized insoles using fused filament fabrication (FFF) and user-specific foot shape data. We evaluated the method's effects through plantar pressure distribution and Arch Index (AI) analysis. To capture plantar contours, we designed a kit-type impression-based acquisition process. The resulting impressions were digitized using three-dimensional (3D) scanning. We aligned the scanned plantar impression with a base insole CAD model, iteratively modifying and verifying the upper surface to reconstruct a customized insole geometry. The final insole model was exported in STL format and produced using FFF with a thermoplastic polyurethane (TPU) filament and a 25% honeycomb infill structure. A subject with a high arch wore the customized insoles during daily activities for one month, with plantar pressure data collected three times before and after the wear period. After using the customized insoles, the midfoot contact area increased from approximately 10–15% to 20–25% of the total plantar contact area, and the plantar load distribution shifted from a forefoot-rearfoot concentration to a more balanced pattern. These results demonstrate that the proposed FFF-based customized insole effectively enhances medial arch support and promotes a balanced plantar load distribution.
Fused deposition modeling (FDM) is a popular technique for polymer additive manufacturing. However, the hygroscopic nature of thermoplastic filaments can lead to moisture-related defects during extrusion. When moisture is absorbed and vaporizes inside the nozzle, bubbles form, resulting in voids within the extrudate and deposited roads. This can compromise inter-road bonding and diminish mechanical performance. This study examines how the initial moisture content of ABS filaments affects the tensile behavior of parts fabricated by FDM. ABS filaments were conditioned to seven different moisture levels through water immersion for periods ranging from 0 to 12 hours, with moisture content quantified using the loss-in-weight method (ASTM D6980). ASTM D638 Type I specimens were printed under consistent processing conditions and tested in tension (n = 5 per condition). The results showed that ultimate tensile strength (UTS) decreased as filament moisture content increased, with a maximum reduction of 9.3% observed at 0.69% moisture compared to the dried condition (0.05%). Ductility was assessed by measuring strain at break, and its relationship with moisture content is illustrated in Fig. 4, along with statistical analysis (one-way ANOVA and post-hoc comparisons). These findings offer valuable insights for moisture management and quality control in ABS FDM processes.
The control fin is a key component in a guided missile's propulsion system, stabilizing the missile's attitude and maintaining its flight trajectory under high-speed conditions. Such components demand high mechanical strength and thermal stability. However, traditional control fin designs have primarily focused on external geometry, overlooking opportunities to enhance performance through internal structural design.To address this limitation, this study proposes a design approach that integrates lattice structures within the control fin using metal additive manufacturing. A body-centered cubic (BCC) lattice was selected, with strut diameter and unit cell aspect ratio defined as the primary design variables. Finite element analysis in Abaqus was used to evaluate structural behavior, analyzing stress and displacement distributions based on variations in these lattice parameters. Manufacturability and lightweight characteristics were also assessed. Results indicate that increasing the strut diameter improves structural stability, with stress predominantly concentrated near lattice joints. Building on these findings, a non-uniform lattice design, derived from the uniform lattice analysis, was applied, demonstrating improved stress distribution and overall structural performance. This approach shows that lattice-based internal structures, enabled by metal additive manufacturing, can significantly enhance the structural performance of guided missile control fins while achieving substantial weight reduction.
With the rapid growth of AI and Big Data, reducing energy consumption in data centers has become a significant challenge. Small-scale server rooms, which often depend on standalone cooling units instead of specialized infrastructure, are especially vulnerable to airflow inefficiencies and localized hotspots. While traditional HVAC theory can estimate total cooling loads, it does not effectively predict the local thermal distributions that depend on equipment placement. This study employs Computational Fluid Dynamics (CFD) to address these limitations. It focuses on a server room containing five HPCs and three cooling units, comparing theoretical HVAC calculations with 3D thermal fluid analysis conducted using Ansys Fluent. The research evaluates the thermal performance of the existing layout (Model 1) and suggests an improved configuration (Model 2). The findings reveal that strategic equipment placement can eliminate hotspots and stabilize operations while reducing the necessary cooling capacity. This research provides a practical framework for enhancing energy efficiency in small-scale server environments.
This study proposes a novel flow-field design strategy that incorporates porous inserts into the bipolar plate (BP) flow channels to address flooding and improve the performance of polymer electrolyte membrane fuel cells (PEMFCs). The BPs were fabricated by maintaining the traditional flow-field structure while varying the number and arrangement of melamine foam inserts, with the electrochemical performance changes analyzed comparatively. The findings revealed that the configuration featuring five porous inserts achieved the highest performance enhancement, with a peak power density increase of approximately 13.4% compared to the conventional cell. This improvement is attributed to localized pressure gradients created by the porous inserts, which facilitated transverse gas transport toward the gas diffusion layer and reduced flooding in the flow channels. However, excessive insertion resulted in increased flow resistance and mass transport limitations, leading to performance degradation. The study also confirmed the impact of insert arrangement on PEMFC performance. Overall, the introduction of porous inserts into BP flow channels, without the need for additional machining processes, offers an effective method for managing water and gas transport in PEMFCs, providing valuable insights for flow-field optimization and the development of high-performance fuel cell systems.
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