• Transactions of the Korean Society of Mechanical Engineers
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• v.13 no.3
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• pp.433-442
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• 1989

Owing to the development of CNC machine tools and automatic programing software, the milling process with ball-end mill has become the most widely used process where three-dimensional precision machining is important. In this study, the ball-end milling process has been analyzed and a cutting force model has been developed to predict the cutting force acting on the ball-end mill on given machining conditions. The development of the model is based on the analysis of geometry of a ball-end mill an the oblique cutting process. The cutting edges of ball-end mills are considered as a series of infinitesimal elements and the geometry of the cutting edge element each cutting edge element is straight. The oblique cutting process in the small cutting edge element has been analyzed as orthogonal cutting process in the plane containing the cutting velocity vector and chip-flow vector. Hence, with the orthogonal cutting data obtained from orthogonal turning test, the cutting forces can be predicted through the model. The predicted cutting forces has shown a fairly good agreement with the test results in various plane cutting conditions.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.12
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• pp.979-984
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• 2016

Recently, ball screws have been used in machine tools, robot parts, and medical instruments. The demand for ball screws of high precision and reduced size is increasing because of the growth of high value-added industries. Three types of ball screws are typically used: deflector type, end-cap type, and tube type. They are also classified from C0 to C9 according to the precision level. A deflector type ball screw can reduce the variation of rotational torque and the size of the nut of the ball screw is minimized. To ensure the reliable design of ball screws, it is important to perform a structural analysis. The purpose of this study is to perform a stability evaluation through analysis of a deflector type miniature ball screw for weapon systems. The analysis is performed through Finite Elements Method (FEM) simulation to predict characteristics such as deformation, stress, and thermal effects. The interference between the shaft and the deflector for smooth rotation are also studied. Based on the results of the analysis, the development of the deflector type miniature ball screw for weapon systems is performed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.9
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• pp.1063-1070
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• 2011

The manufacturing execution system (MES) for product production handles different production processes according to the product characteristics and different types of data according to the process being considered. For efficiently providing the data pertaining to production equipment to production systems such as the MES, data collection through the equipment interface is required for obtaining the production data pertaining to field equipment. In this paper, a method is proposed for collecting the production data through the equipment interface in order to collect the various types of production-equipment data from the field. The proposed method is applied to a real manufacturing system to verify its efficiency. A more powerful MES can be constructed with a data acquisition system that acquires the status data at the shop-floor level.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.2
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• pp.79-85
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• 2006

As the portable information appliance is developed, the demand of flat panel display equipments and parts are steeply increased. Most of all, the applications of LCD such as LCD TV, monitor, digital camera, CNS(car navigation system) and game machine become diversified. With the result that the number of BLU production enterprise is increased and the research on the design of backlight with the superior optical properties is persistently in progress. In this study we developed the pattern design tools for CCFL(cold cathode flourescent lamp) backlight to improve the conventional pattern design environment in which the pattern is designed manually from the experience and the trial and error. For the verification of our research, we designed the light reflection surface patterns for a real model of backlight and we measured the brightness uniformity using the BM-7. From the brightness uniformity measurement, the BLU designed using the presented tool showed the tolerable performance only in the first try of pattern design rather than the fifth try of pattern design in case of the conventional pattern design.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.117-124
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• 2021

In this paper, we propose CANVAS (Creative ANalytics enVironment And System), an analytics system of the National Research Data Platform (DataON). CANVAS is a personalized analytics cloud service for researchers who need computing resources and tools for research data analysis. CANVAS is designed in consideration of scalability based on micro-services architecture and was built on top of open-source software such as eGovernment Standard framework (Spring framework), Kubernetes, and JupyterLab. The built system provides personalized analytics environments to multiple users, enabling high-speed and large-capacity analysis by utilizing high-performance cloud infrastructure (CPU/GPU). More specifically, modeling and processing data is possible in JupyterLab or GUI workflow environment. Since CANVAS shares data with DataON, the research data registered by users or downloaded data can be directly processed in the CANVAS. As a result, CANVAS enhances the convenience of data analysis for users in DataON and contributes to the sharing and utilization of research data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.98-105
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• 2021

The sensory stimulation of a cosmetic product has been deemed to be an ancillary aspect until a decade ago. That point of view has drastically changed on different levels in just a decade. Nowadays cosmetic formulators should unavoidably meet the needs of consumers who want sensory satisfaction, although they do not have much time for new product development. The selection of new products from candidate products largely depend on the panel of human sensory experts. As new product development cycle time decreases, the formulators wanted to find systematic tools that are required to filter candidate products into a short list. Traditional statistical analysis on most physical property tests for the products including tribology tests and rheology tests, do not give any sound foundation for filtering candidate products. In this paper, we suggest a deep learning-based analysis method to identify hand cream products by raw electric signals from tribological sliding test. We compare the result of the deep learning-based method using raw data as input with the results of several machine learning-based analysis methods using manually extracted features as input. Among them, ResNet that is a deep learning model proved to be the best method to identify hand cream used in the test. According to our search in the scientific reported papers, this is the first attempt for predicting test cosmetic product with only raw time-series friction data without any manual feature extraction. Automatic product identification capability without manually extracted features can be used to narrow down the list of the newly developed candidate products.

• Design & Manufacturing
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• v.13 no.2
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• pp.54-59
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• 2019

CNC(Computer Numerical Control) machine tools are being used in various industrial fields such as aircraft and automobiles. The machining conditions used in the mold industry are used, and the simulation and the experiment are compared. The tool used in the experiment was carried out to increase the reliability of the simulation of the cutting machining. The program used in the 3D-FEM (finite element method) was the AdvantEdge and predicted by down-milling. The tool model is used 3D-FEM simulation by using the cutting force, temperature prediction. In this study, we carried out the verification of cutting force by using a 3-axis tool dynamometer (Kistler 9257B) system when machining the plastic mold Steel machining of NAK-80. The cutting force experiment data using on the charge amplifier (5070A) is amplified, and the 3-axis cutting force data are saved as a TDMS file using the Lab-View based program using on NI-PXIe-1062Q. The machining condition 7 was the most similar to the simulation and the experimental results. The material properties of the NAK-80 material and the simulation trends reflected in the reverse design of the tool were derived similarly to the experimental results.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.621-635
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• 2020

Water quality models are scientific tools that simulate and interpret the relationship between physical, chemical and biological reactions to external pollutant loads in water systems. They are actively used as a key technology in environmental water management. With recent advances in computational power, water quality modeling technology has evolved into a coupled three-dimensional modeling of hydrodynamics, water quality, and ecological inputs. However, there is uncertainty in the simulated results due to the increasing model complexity, knowledge gaps in simulating complex aquatic ecosystem, and the distrust of stakeholders due to nontransparent modeling processes. These issues have become difficult obstacles for the practical use of water quality models in the water management decision process. The objectives of this paper were to review the theoretical background, needs, and development status of water quality modeling technology. Additionally, we present the potential future directions of water quality modeling technology as a scientific tool for national environmental water management. The main development directions can be summarized as follows: quantification of parameter sensitivities and model uncertainty, acquisition and use of high frequency and high resolution data based on IoT sensor technology, conjunctive use of mechanistic models and data-driven models, and securing transparency in the water quality modeling process. These advances in the field of water quality modeling warrant joint research with modeling experts, statisticians, and ecologists, combined with active communication between policy makers and stakeholders.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.244-251
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• 2020

This paper presents a design of the Meta-Class Repository (MCR) which maintain syntactically analyzed and structured meta-class information from UML diagrams, and then proposes 'meta-class,' also known as super-class, to construct structured information analyzed syntactically. The MCR is a collection of these meta-classes which contains the information extracted from diagrams. This paper also presents a design of the Code Generation Engine (CGE) which roles generating codes corresponding classes from UML diagrams based on the MCR maintaining a collection of meta-classes which is syntactically-analyzed and constructed in previous process. The logics of CGE are designed to generate codes collaborated with MCR and CGE with integration. The logics of CGE mechanism is presented with the form of finite state machine to present the algorithms of code generation formally and have the advantages of simplicity and easiness in development.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.319-328
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• 2021

Parallel administration of numerous drugs increases Drug-Drug Interaction (DDI) because one drug might affect the activity of other drugs. DDI causes negative or positive impacts on therapeutic output. So there is a need to discover DDI to enhance the safety of consuming drugs. Though there are several DDI system exist to predict an interaction but nowadays it becomes impossible to maintain with a large number of biomedical texts which is getting increased rapidly. Mostly the existing DDI system address classification issues, and especially rely on handcrafted features, and some features which are based on particular domain tools. The objective of this paper to predict DDI in a way to avoid adverse effects caused by the consumed drugs, to predict similarities among the drug, Drug pair similarity calculation is performed. The best optimal weight is obtained with the support of KHA. LSTM function with weight obtained from KHA and makes bets prediction of DDI. Our methodology depends on (LSTM-KHA) for the detection of DDI. Similarities among the drugs are measured with the help of drug pair similarity calculation. KHA is used to find the best optimal weight which is used by LSTM to predict DDI. The experimental result was conducted on three kinds of dataset DS1 (CYP), DS2 (NCYP), and DS3 taken from the DrugBank database. To evaluate the performance of proposed work in terms of performance metrics like accuracy, recall, precision, F-measures, AUPR, AUC, and AUROC. Experimental results express that the proposed method outperforms other existing methods for predicting DDI. LSTMKHA produces reasonable performance metrics when compared to the existing DDI prediction model.