Directed energy deposition (DED) enables the efficient fabrication and repair of large metal components. However, repeated reuse of the powder generates degraded particles, which must be removed by sieving. This study used scanning electron microscopy and laser diffraction particle size analysis to characterize the sieve-rejected Inconel Alloy 939 powder collected sequentially after each of four DED processing cycles (R1–R4). The rejected powder consistently contained elongated, irregular, and satellite-attached particles, and its particle size increased progressively with each reuse cycle. The mean particle size increased by 16.8%, from 51.1 μm for R1 to 59.7 μm for R4. The D₁₀, D₅₀, and D₉₀ values also increased, with D90, for example, rising from 71.5 to 82.2 μm. These results suggest that sieving may serve as an important quality control step for maintaining powder quality when the powder is repeatedly reused in DED.

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.

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.

As AI transformation expands in manufacturing, intelligent technologies are increasingly applied to CNC machine tools and machining processes. In multi-product, small-batch production environments, frequent product changes require flexible and autonomous process planning. This study proposes a standard data integration-based intelligent process planning system that automatically performs the entire process from 3D model input to NC code generation. To enable intelligent process planning, data across all stages—from feature recognition to machining execution—must be integrated into a unified flow and connected with AI-based decision-making. The proposed system uses an ISO 14649-based XML schema to sequentially link data generated by each module, ensuring standardized information flow. Based on this framework, rulebased feature recognition, constraint-based process planning, and machine learning-based cutting condition optimization are implemented. A prototype system was developed to validate the approach, automatically generating NC code for industrial parts and performing actual CNC machining. Experimental results confirmed the feasibility and validity of the proposed system. This study demonstrates that standardized data integration combined with AI technologies can enable autonomous, flexible, and efficient process planning for advanced manufacturing environments.

The formation of a hat-profile is significantly influenced by springback and the final cross-sectional geometry, both of which are sensitive to die profile design. This study introduces a scalar-based artificial neural network (ANN) surrogate model combined with genetic-algorithm (GA) optimization to enhance die and process design efficiency. An automated ABAQUS finite-element workflow was established to generate 900 design cases. For each case, seven scalar geometric and angle responses characterizing the post-forming cross section were extracted and used to train a multilayer perceptron. This network maps four die design variables to the final geometry. The surrogate model demonstrated high predictive accuracy, with geometric and angular errors remaining small and coefficients of determination (R²) nearing 1.0. This enabled quick evaluation of new designs without the need for additional finite-element analyses. By integrating the ANN surrogate within a GA, optimal die geometries were identified that reduce springback while meeting target dimensions, showcasing the proposed framework as an effective AI-driven design tool for sheet-metal forming.

Cable chains are essential in the semiconductor industry for preventing the twisting or sagging of moving cables. They can be broadly categorized into two types based on their fastening methods, with rivet-based assembly being the most common. An alternative method utilizes integral locking features without rivets, which simplifies manufacturing and reduces production costs. However, integral cable chains are more susceptible to breakage during assembly, limiting their use in various industrial environments.This study introduces a structural design approach aimed at minimizing localized stress during assembly while ensuring the cable chain meets the required retention force. Design variables were selected from the modifiable features of the integral cable chain. Through sensitivity analysis, we identified key variables that significantly influence the retention force, which allowed us to reduce the number of design iterations. By employing finite element analysis and response surface methodology, we derived an optimal shape that achieved the target pull-out force and resulted in a 9.7% reduction in assembly stress compared to the original design.

This paper deals with the current technology status and technology development direction on shape shifting drone. A shape shifting drone is defined as a drone for which its shape and/or function of its platform in flight can be changed by shape shifting technology in order to fulfill a variety of missions effectively in harsh mission environment. A shape shifting drone can be classified as a rotary-wing based, a fixed-wing based, or a biomimetic based shape shifting drone. This work describes technology trends of domestic and foreign countries. It identifies core technologies and development direction. This work will be useful for planning research and development programs on required technology for the development of shape shifting drone in the future.

As system performance continues to improve at higher resolutions, it becomes increasingly important to establish standards for imaging degradation caused by optical windows. In this study, random surface shapes were simulated on large area optical windows with peak-to-valley (P-v) values of 0.25, 0.5, and 1.0 λ. Modulation Transfer Function (MTF) values were derived for 1,000 cases per P-v value using Monte-Carlo simulations. The specifications achieved a surface accuracy of 0.5 λ and a parallelism of 0.01 mm. MTF measurements showed that the system MTF was 13.5% prior to the installation of the optical window, and 13.1% after installation. This indicates a degradation rate of approximately 3%.

In this study, we present the fabrication of dual-morphing vascular stents using an additive-lathe printing method and two different shape-memory polymers. Traditional additive manufacturing techniques confront significant challenges in producing vascular stents with complex, hollow, mesh-like structures due to limitations such as a flat printing bed and the placement of supports. To overcome these obstacles, we employed a lathe-type additive manufacturing system with a rotatable base substrate, enabling precise fabrication of cylindrical-shaped stents. To achieve shape transformability, we used shapememory polymers as the stent materials, offering the advantage of minimally invasive surgery. Two distinct shape-memory polymers, with different transition temperatures (35 and 55oC), were printed using the additive-lathe method. The printed stents consisted of two distinct parts that underwent dual-stage morphological changes at the different temperatures. By manipulating the printing paths, the dual-morphing properties of the stents could be adjusted in both longitudinal and circumferential directions. This innovative approach could be a solution to several limitations associated with the application of stents in diseased vascular tissues with complex shapes, facilitating minimal invasion during surgical procedures.

The objective of this study was to present a rotary manipulating system driven by a rotary actuator based on twisted shape memory alloy (SMA) wires. The rotary actuator was composed of two oppositely twisted SMA wires connecting a rotor and a stator through a shaft. Two oppositely twisted SMA wires could generate bidirectional rotary motions upon actuation of each twisted SMA wire corresponding to the direction against the twist direction of each SMA wire. A manipulator was designed and fabricated by integrating manipulating arms, the rotary actuator, and a Hall effect magnetic rotary encoder which could measure the angular position of the rotary motion. We modeled and characterized the manipulator upon application of a ramp current input to each twisted SMA wire. A proportional-integral-derivative (PID) controller was designed and implemented to control the proposed rotary manipulator. Reference angular position tracking performances of the manipulator were evaluated with a series of experiments.

SFT, which has a high glass fiber content, is one of the effective methods to replace metal and secure weight reduction and price competitiveness. Also, paintless injection molding in which a functional pattern is applied to the mold surface can eliminate the cost of painting. In this study, three types of SFTs were manufactured by adding round glass fibers measuring Φ7 and Φ10 μm and flat glass fiber measuring 27 × 10 μm for the experiment. DOE (Design of Experiment) was conducted to confirm the change in the warpage of the product and the gloss of the micro pattern due to the cross-sectional shape of glass fibers and the major injection conditions. Based on the results, it was identified that the flat SFT had a very small warpage compared to the round SFTs, and the holding pressure was the main factor in the warpage of all three SFTs. The Φ7 μm SFT had the largest gloss value, and the Φ10 μm SFT and the flat SFT had similar average values. All SFTs demonstrated an enormous change in gloss according to the change in mold temperature. The flat SFT had the smallest standard deviation in both warpage and gloss.

The subtle feature is one of the characteristic lines and represents the most noticeable line in the automotive panel. In this study, we proposed a method to predict the radius of curvature of products according to the material, its thickness, its punch angle, and its punch radius. The radius of curvature was divided into three regions, namely, the non-linear, transition, and linear regions. In the non-linear region, the prediction model for the radius of curvature with different forming conditions was derived using the finite element analysis. In the linear region, the radius of curvature was assumed to be the sum of the punch radius and the thickness of the material. In the transition region, a model connecting two regions (Non-linear and linear region) was developed based on the continuity condition. The prediction model presented a very small RMSE with the value of 0.314 mm. Using the prediction model, the radius of curvature with various forming variables could be predicted and the required radius of punch, to obtain a certain value of the radius of curvature, could be precisely predicted.

SFT, which has a high glass fiber content, is one of the effective methods to replace metal and secure weight reduction and price competitiveness. This study evaluated the effect of glass fiber shape on mechanical properties in injection molding by fabricating SFT with a glass fiber content of 60%. Three types of SFTs were manufactured by adding round glass fibers of Φ7 μm and Φ10 μm and flat glass fibers of 27 × 10 μm. DOE (Design of Experiment) conducts to confirm the change in tensile strength due to changes in significant injection conditions. As a result of the experiment, Φ7 μm SFT and flat SFT have similar tensile strength and Φ10 μm SFT showed the lowest tensile strength value. As for the standard deviation of strength value, the Φ7 μm SFT had the largest standard deviation, and the Φ10 μm SFT showed the slightest change in the injection conditions. In flat SFT, it confirms that the tensile strength increased as the molding temperature increased. The fracture surface observes using SEM. It founds that the tensile strength lowers due to the small glass fiber density and many pullouts at the fracture surface of Φ10 μm with weak strength.

Injection molding is one of most widely-used polymer processing technologies in which hot polymer fills a mold cavity, and is solidified during the subsequent cooling process. In the mold filling stage, the mold temperature should be high to improve flow characteristics, and low to reduce cooling time during the cooling stage. To fulfill these objectives, rapid mold heating technology has been developed to raise mold temperature, without significant increase in cycle time. While the conventional rapid heating technologies required dedicated facilities such as steam heating or high-frequency induction heating system and has a limitation in uniform heating, the purpose of this study was to develop a facile and conformal mold heating unit that uses a carbon nanotube (CNT) film heater. The CNT film heater was used to heat a curved mold with high temperature uniformity, by maintaining uniform distance from the mold surface. The developed conformal heating technology was then applied to a singly curved mold and a multiply curved mold. Considering that the resulting temperature uniformity is superior to the conventional oil heating, the conformal mold heating technology using the CNT film heater can be used to improve part quality and productivity in various molding processes.