• Progress in Superconductivity and Cryogenics
• /
• v.25 no.4
• /
• pp.65-69
• /
• 2023

Hydrogen is an eco-friendly energy source and is being actively researched in various fields around the world, including mobility and aerospace. In order to effectively utilize hydrogen energy, it should be used in a liquid state with high energy storage density, but when hydrogen is stored in a liquid state, BOG (boil-off gas) is generated due to the temperature difference with the atmosphere. This should be re-condensed when considering storage efficiency and economy. In particular, large-capacity liquid hydrogen storage tank is required a gaseous helium circulation cooling system that cools by circulating cryogenic refrigerant due to the increase in heat intrusion from external air as the heat transfer area increases and the wide distribution of the gas layer inside the tank. In order to effectively apply the system, thermo-hydraulic analysis through process analysis is required. In this study, the condenser design and system characteristics of a gaseous helium circulation cooling system for BOG recondensation of a liquefied hydrogen storage tank were compared.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.3
• /
• pp.528-550
• /
• 2024

Warehousing demand prediction is an essential part of the supply chain, providing a fundamental basis for product manufacturing, replenishment, warehouse planning, etc. Existing forecasting methods cannot produce accurate forecasts since warehouse demand is affected by external factors such as holidays and seasons. Some aspects, such as consumer psychology and producer reputation, are challenging to quantify. The data can fluctuate widely or do not show obvious trend cycles. We introduce a new model for warehouse demand prediction called MAGRU, which stands for Multi-layer Attention with GRU. In the model, firstly, we perform the embedding operation on the input sequence to quantify the external influences; after that, we implement an encoder using GRU and the attention mechanism. The hidden state of GRU captures essential time series. In the decoder, we use attention again to select the key hidden states among all-time slices as the data to be fed into the GRU network. Experimental results show that this model has higher accuracy than RNN, LSTM, GRU, Prophet, XGboost, and DARNN. Using mean absolute error (MAE) and symmetric mean absolute percentage error(SMAPE) to evaluate the experimental results, MAGRU's MAE, RMSE, and SMAPE decreased by 7.65%, 10.03%, and 8.87% over GRU-LSTM, the current best model for solving this type of problem.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.35 no.1
• /
• pp.53-58
• /
• 2011

Ultra-precision miniaturized machine tools essential for manufacturing accurate machine components in micro/meso-scale have been developed. To realize high accuracy using mMTs, geometric errors, which are considered as the main sources of inaccuracy should be identified and compensated. The conventional systems for measuring geometric errors, such as a laser interferometer, can measure only one geometric error in a single setup and they involve complicated measurement procedures. A measurement system using PSDs is a promising alternative but the measurable range of such systems is limited to the active range of the PSDs. The proposed measurement system using PSDs can overcome the limit of small measurable range. Further, the mounting errors that could occur during set-up process can be avoided. In this paper, an algorithm corresponding to the system was analyzed and experiments were carried out.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.32 no.1
• /
• pp.26-33
• /
• 2009

The directions of the road are divided into two, the right-hand side and left-hand side of the road, by the convention and specific native method in the world. This paper deals with the characteristics and behaviors of drivers who are accustomed to driving on right-hand side of the road, drive with a handle on the left-hand side, and comparing with left-hand side drivers. The driver's eye movements were measured by eye camera and questionnaires were used for measuring subjective evaluation such as driving mental workload. The experimental results indicated even if the experts who had much experience on right-hand side driving, they had lower driving skill than novice driver, accustomed to driving on left-hand side. In terms of mental workload, MCH rating scale and MNASA-TLX, the right-hand side drivers were in lower stress condition than the left-hand side drivers because of having much driving experience. However, they conducted a few mistakes by confusing the position of turn signal and windshield wiper because of their driving habit or traits and it lead to operation mistakes. These results can be applied effectively to develop the driving support information with changed environments.

• Journal of Biosystems Engineering
• /
• v.40 no.1
• /
• pp.28-34
• /
• 2015

Purpose: This study aimed to install an RTK-GPS (Real Time Kinematic-Global Positioning System) and IMU (Inertial Measurement Unit) on a tractor used in a farm to measure positions, pasture topography, posture angles, and vibration accelerations, translate the information into maps using the GIS, analyze the characteristics of grass harvesting work, and establish new technologies and construction standards for pasture infrastructure improvement based on the analyzed data. Method: Tractor's roll, pitch, and yaw angles and vibration accelerations along the three axes during grass harvesting were measured and a GIS map prepared from the data. A VRS/RTK-GPS (MS750, Trimble, USA) tractor position measuring system and an IMU (JCS-7401A, JAE, JAPAN) tractor vibration acceleration measuring systems were mounted on top of a tractor and below the operator's seat to obtain acceleration in the direction of progression, transverse acceleration, and vertical acceleration at 10Hz. In addition, information on regions with bad workability was obtained from an operator performing grass harvesting and compared with information on changes in tractor posture angles and vibration acceleration. Results: Roll and pitch angles based on the y-axis, the direction of forward movements of tractor coordinate systems, changed by at least $9-13^{\circ}$ and $8-11^{\circ}$ respectively, leading to changes in working postures in the central and northern parts of the pasture that were designated as regions with bad workability during grass harvesting. These changes were larger than those in other regions. The synthesized vectors of the vibration accelerations along the y-axis, the x-axis (transverse direction), and the z-axis (vertical direction) were higher in the central and northwestern parts of the pasture at 3.0-4.5 m/s2 compared with other regions. Conclusions: The GIS map developed using information on posture angles and vibration accelerations by position in the pasture is considered sufficiently utilizable as data for selection of construction locations for pasture infrastructure improvement.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.41 no.1
• /
• pp.94-101
• /
• 2018

With the development of industrial technology and science, production and manufacturing facilities have been enhanced and improved, and the importance of the safety of workers has also been regulated and limited by various safety management methods. As a way to secure the safety of the workers from the production facility, the fail-safe and fool-proof methods are now being applied. Any possible insecure behavior and unsafe conditions can be removed by adopting the standards and specifications that are now secure the safety of workers and equipment. This research analyzes EN ISO 13849-1 international and European standards during CE certification. In order to secure acceptable reduced risks, the risk assessment process of ISO 12100 and the processes for reducing its risk are applied. In the current ISO 13849-1 standard, the criteria for the required performance level PLr (Required Performance Level) for the applicable risk and safety functions through the risk assessment are subjective and not subdivided. Therefore, the evaluation criteria are likely to cause judge's judgement error due to qualitative judgement. This research focuses on evaluation and acceptable performance level setting for the safety circuit of the equipment. We propose an objective and specific evaluation criteria to secure safety, and the proposed evaluation criteria are applied to the case study of the safety circuit for the equipment. In order to secure the safety of the entire safety circuit, the improvement of the MTTFd and DC level related to the SRP/CS (Safety-Related Parts of Control Systems)' lifetime is required for the future research.

• Journal of the Korean Applied Science and Technology
• /
• v.35 no.4
• /
• pp.1338-1347
• /
• 2018

In this study, Ti-mesh based electrodes were fabricated for the application of anode to the electrolysis process for wastewater treatment using Pd electroless plating method. The removal performance of the prepared Pd / Ti-mesh electrode was evaluated as representative dye RO16, and the durability and performance were maximized by varying the electrode manufacturing conditions. As a result, it was confirmed that the coating condition had no significant effect on the performance, and that the heat treatment process greatly affected the performance and the durability was improved. In addition, we tried to maximize performance and durability by complexing Ir, Ru, and Ta. However, as the thickness of the layer increased due to the limitation of the coating method, the resistance increased and the performance decreased accordingly.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.45 no.4
• /
• pp.233-239
• /
• 2022

The injection molding process is a process in which thermoplastic resin is heated and made into a fluid state, injected under pressure into the cavity of a mold, and then cooled in the mold to produce a product identical to the shape of the cavity of the mold. It is a process that enables mass production and complex shapes, and various factors such as resin temperature, mold temperature, injection speed, and pressure affect product quality. In the data collected at the manufacturing site, there is a lot of data related to good products, but there is little data related to defective products, resulting in serious data imbalance. In order to efficiently solve this data imbalance, undersampling, oversampling, and composite sampling are usally applied. In this study, oversampling techniques such as random oversampling (ROS), minority class oversampling (SMOTE), ADASYN(Adaptive Synthetic Sampling), etc., which amplify data of the minority class by the majority class, and complex sampling using both undersampling and oversampling, are applied. For composite sampling, SMOTE+ENN and SMOTE+Tomek were used. Artificial neural network techniques is used to predict product quality. Especially, MLP and RNN are applied as artificial neural network techniques, and optimization of various parameters for MLP and RNN is required. In this study, we proposed an SA technique that optimizes the choice of the sampling method, the ratio of minority classes for sampling method, the batch size and the number of hidden layer units for parameters of MLP and RNN. The existing sampling methods and the proposed SA method were compared using accuracy, precision, recall, and F1 Score to prove the superiority of the proposed method.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.3
• /
• pp.139-147
• /
• 2023

The metal bush assembling process is a process of inserting and compressing a metal bush that serves to reduce the occurrence of noise and stable compression in the rotating section. In the metal bush assembly process, the head diameter defect and placement defect of the metal bush occur due to metal bush omission, non-pressing, and poor press-fitting. Among these causes of defects, it is intended to prevent defects due to omission of the metal bush by using signals from sensors attached to the facility. In particular, a metal bush omission is predicted through various data mining techniques using left load cell value, right load cell value, current, and voltage as independent variables. In the case of metal bush omission defect, it is difficult to get defect data, resulting in data imbalance. Data imbalance refers to a case where there is a large difference in the number of data belonging to each class, which can be a problem when performing classification prediction. In order to solve the problem caused by data imbalance, oversampling and composite sampling techniques were applied in this study. In addition, simulated annealing was applied for optimization of parameters related to sampling and hyper-parameters of data mining techniques used for bush omission prediction. In this study, the metal bush omission was predicted using the actual data of M manufacturing company, and the classification performance was examined. All applied techniques showed excellent results, and in particular, the proposed methods, the method of mixing Random Forest and SA, and the method of mixing MLP and SA, showed better results.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.10
• /
• pp.289-299
• /
• 2016

Weapon systems require reliability in the development phase for efficient combat readiness. Improved reliability in various manufacturing processes have been achieved using data analysis. However, data analysis in the development phase is difficult due to problems such as the lack of data, high cost, and the importance of security. Therefore, Post Logistics Support (PLS) data collected following integration is analyzed for long-term quality improvement of weapon systems. In this study, we propose a methodology for examining the correlation between the failure rate and PLS data as follows: First, key variables affecting reliability were identified the correlation between variables on the failure rate examined. Second, corresponding analysis was conducted for determining the correlation between patterns of categorical data. Third, extract categories with the higher contribution and quality of representation, and find the highest variable correlated with failure period through visualization. Then, after selecting patterns which have shorter failure period, the cause of decreased reliability was confirmed through frequency analysis. This study will contribute to improving reliability when developing new weapon systems and will help to strengthen the combat readiness of military.