With the increasing frequency of laparoscopic surgery, interest in the application of polymeric ligation clips as a method for ligating blood vessels has grown. Automatic clip appliers with built-in polymeric ligation clips have been developed to reduce ligation time. As the built-in clip is loaded into the jaw of the applier for ligation, a high spring constant, the elastic property of the clip is required to load properly. As the built-in clip loses its elastic properties due to stress relaxation over time, a polymeric ligation clip with a high spring constant is needed to increase the shelf life of the applier. In this study, four design factors of the cavity at the clip hinge (length, width, eccentricity, and angle of the cavity) were derived and applied to the Taguchi optimization method using finite element analysis to evaluate which factor was critical. The four design factors explained 93.5% of the variation in the spring constant. The factors related to cavity width and eccentricity were significant at p<0.05. Cavity width was the most crucial factor, explaining 70.8% of the variation in the spring constant. The spring constant of the improved clip model increased by 55.4% compared with the existing model.

PCBs (Printed circuit boards) have been widely used in electronic products such as wearables, smartphones, and table computers. Recent trends of miniaturizing electric components require improvement of component density and electronic functionality by decreasing the size of micro via holes (50-110 μm), which interconnect electric signals between adjacent layers in high density interconnection (HDI) PCBs. To generate micro via holes, we studied CO₂ laser drilling with the help of pulse shape controlling using acousto-optic modulator (AOM). Pulse shape controlling is one of the key factors to reduce heat effect during the laser drilling process. To increase laser absorption, the substrate was subjected to black oxidation prior to CO₂ laser drilling. We designed a diffractive optical system using a circular aperture. Micro via holes were obtained by optimizing the optical distance. The laser drilled via hole was studied both experimentally and theoretically.

In this study, polyacetal plates were machined with an indexable drill (Ø18mm) to measure the dimensional error of holes according to the cutting conditions and investigate the influencing factors to obtain precision holes. Cutting velocity, feed, and depth of cut were selected as experimental variables, analyzed using design of experiment, and optimal cutting conditions were investigated. Cutting velocity and feed were significant factors affecting hole accuracy, whereas depth of cut had little effect. The factor with the greatest influence on hole accuracy was cutting velocity, and the dimensional error of the holes tended to increase as the cutting velocity increased. Dimensional error tended to decrease as feed increased. In addition, the interaction effect between cutting velocity and feed and cutting velocity and depth of cut were significant. In this experiment, the optimal cutting velocity, feed, and depth of cut needed to minimize the dimensional error of holes were 100 m/min, 0.15 mm/rev, and 2 mm, respectively.

This study proposes a path-tracking algorithm based on feed-forward (preview distance control) and feedback (LQR, linear quadratic regulator) controllers to reduce heading angle errors and lateral distance errors between a predefined path and an autonomous vehicle. The main objective of path-tracking is to generate control commands to follow a predefined path. The feed-forward control is applied to solve heading angle errors and lateral distance errors in the trajectory caused by curvatures of the road by controlling the steering angle of the vehicle. An LQR was applied to decrease the errors caused by environmental and external disturbances. The proposed algorithm was verified by simulating the driving environment of an autonomous vehicle using a CARLA simulator. Safety and comfort were demonstrated using the test vehicle. The study also demonstrated that the tracking performance of the proposed algorithm exceeded that of other path-tracking algorithms, such as Pure Pursuit and the Stanley Method.

Automatic transmissions, which have the advantages of compact structure and smooth shifting, are installed in various vehicles with engines and hybrid power sources. Research and development are continuously being conducted to improve power and fuel efficiency. In this study, the influence of helix direction and helix angle of the planetary gear set on thrust-bearing power loss in an automatic transmission was analyzed. A sample automatic transmission model was constructed to analyze the axial load and bearing relative rotation speed, which are the main factors in thrust-bearing power loss. The relative rotation speed of the bearing was analyzed using the sample model, and the thrust-bearing load in the axial direction was analyzed according to the helix direction of the planetary gear set constituting the model and the helix angle of the planetary gear set. The power loss occurring in thrust-bearing was derived using the analysis results of relative rotational speed and load, and the influence of the helix direction and helix angle of the planetary gear set was analyzed.

Digital twin technology offers the advantage of monitoring the status of equipment, systems, and more in a virtual environment, allowing validation through simulation. This technology has found numerous applications in the industrial robotics field, driven by recent advancements in the manufacturing industry. Consequently, predicting machining quality using digital twin technology is imperative for ensuring high-quality processed goods. In this study, we developed a digital twin program based on a cutting-force physical model and created a performance enhancement module that allows the visualization of material removal for user convenience. The predicted cutting forces from both conventional CNC and the physical model demonstrate a high accuracy of within 2%. Within the digital twin environment, the error rate for the robotic drilling process is 13.5%. Building upon this, we developed and validated a module for material removal visualization, aiming to increase convenience for on-site operators.

Chemical mechanical planarization (CMP) is an essential polishing process in semiconductor manufacturing. Advances in memory technology, including increased capacity and performance, have increased the importance of electronic packaging. In heterogeneous integration, the interposer acts as an important intermediary between the logic die and the substrate, solving numerous I/O bump problems in high-bandwidth memory (HBM) and logic chips. Traditionally, board-to-memory connections were made through wire bonding, which required additional space for wire connections and introduced latency due to extended signal transmission paths. A through-type approach has emerged as a solution that can significantly reduce waiting time and installation space by improving space efficiency and enabling vertical connections without extending wiring. Due to these new approaches, the importance of CMP is reemerging. Implementation of this important process requires precise control of the CMP dishing/protrusion of bonding surfaces. Improper selection of Cu pad dishing/protrusion can cause problems such as increased RC delay time and signal short circuit in the wiring. In this paper, we proposed a strategy to control dishing using CMP, especially for Through-glass-via (TGV).

Autonomous robots are commonly operated on rough roads. Thus, it is essential to predict their dynamic characteristics. Even though it is possible to use real hardware to acquire a robot’s dynamic characteristics, this requires a significant amount of time and cost. Therefore, a real-time remote driving simulator must be developed to reduce these risks. Most real-time simulators employ physics engines, which are calculated using simple functional expressions based on particles. However, in this case, there is a limit to reflecting the dynamic characteristics of actual robots. In this study, a multi-body dynamic model of a robot was established. MATLAB Simulink was used to connect the vehicle model with the joystick and calculate user input signals. The PID control system determines the driving torque of the robot to satisfy the calculated signal. Gain value optimization is performed to enable real-time control. This study can be available to analyze the traversability.

Brain-computer interface (BCI) is a technology used in various fields to analyze electroencephalography (EEG) signals to recognize an individual"s intention or state and control a computer or machine. However, most of the research on BCI is on motor imagery, and research on active movement is concentrated on upper limb movement. In the case of lower limb movement, most of the research is on the static state or single movements. Therefore, in this research, we developed a deep-learning model for classifying walking behavior(1: walking, 2: upstairs, 3: downstairs) based on EEG signals in a dynamic environment to verify the possibility of classifying EEG signals in a dynamic state. We developed a model that combined a convolutional neural network (CNN) and a bidirectional long short-term memory (BiLSTM). The model obtained an average recognition performance of 82.01%, with an average accuracy of 93.77% for walking, 76.52% for upstairs, and 75.75% for downstairs. It is anticipated that various robotic devices aimed at assisting people with disabilities and the elderly could be designed in the future with multiple features, such as human-robot interaction, object manipulation, and path-planning utilizing BCI for control.

Chronic wounds necessitate periodic treatment and management due to their potential for serious complications. Recently, ultrasonic mist therapy has been introduced to treat chronic wounds efficiently. This therapy requires a noncontact spraying method to prevent side effects such as bacterial infections and pain. Therefore, research is needed on a spray nozzle tip that can effectively transmit ultrasonic energy to the wound target with misted cleaning solution mobility in a specific direction and at an appropriate speed. The performance of the nozzle tip is greatly affected by the flow characteristics inside it. Computational fluid dynamics (CFD) is a powerful tool to analyze these characteristics in detail. The behavior of the mist was analyzed in a simulation based on discrete phase model methodology in an unsteady state. Valid design parameters enabling noncontact cleaning were determined by setting the design parameters of the nozzle tip`s internal flow path and measuring the spraying speed of the mist using CFD analysis. Through the simulation results, information on the sprayed skin surface and spray characteristics are measured. Lastly, we present a nozzle tip design guide optimized for ultrasonic mist therapy.