• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.414-419
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• 2016

A study of a precision test according to the control method of an injection molding machine was carried out. The effects of the screw stroke, holding pressure, melt temperature on both the hydraulic and electric injection molding machine were examined. In addition, hypothesis testing was performed to determine the deviation of the data obtained in the experiments. The conclusions obtained in this study were as follows. Significant deviations in the screw stroke, melt temperature and holding pressure occurred in that order. The hydraulic type showed significantly more variation between the products compared to the electric type. In addition, using a mini tab from the statistics program, a hypothesis was proposed and the P value of the injection stroke, holding pressure, melting temperature injection stroke and melting temperature had adopted a null hypothesis ($H_0$). The holding pressure, which showed mutual differences, adopted an alternative hypothesis ($H_1$).

• Journal of The Korean Association of Information Education
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• v.25 no.2
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• pp.327-335
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• 2021

This study verified the effectiveness of machine learning education programs focused on data labeling as an educational method for improving computational thinking of elementary school students. The education program was designed and developed based on the results of a preliminary demand analysis conducted on 100 elementary school teachers. In order to verify the effectiveness of the developed education program, 17 sixth-grade students attending K Elementary School were given 2 classes per day for a total of 6 weeks. In order to measure the effect of the training on improving computational thinking, the educational effects were analyzed by conducting pre-post-inspection using the "Beaver Challenge". According to the analysis, machine learning education focused on data labeling contributed to improving computational thinking of elementary school students.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.6
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• pp.431-438
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• 2016

Recently, concerns about the environment are becoming more important because of global warming and the exhaustion of earth's resources. In the aviation and automobile industries, the application of light materials is increasingly important for eco-friendly and effective. Carbon Fiber Reinforced Plastics is a composite material which great formability and the high strength of carbon fiber. CFRP, which is both light and strong, is hard to manufacture. In addition, CFRP machining has a high chance of defects. This research discusses the development of a manufacturing system package for CFRP machining. It involving CFRP Drilling/Water-jet Manufacturing Machines, Inspection/Post-processing Systems, CNC platform for an EtherCAT servo Communication, Flexible Manufacturing Systems and CFRP machining Processes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.202-208
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• 2016

In this study, the defect in connection with a C-tray was inspected using a low-cost camera. The four test items were the device overlapping in the tray, the bending of the tray, the loaded quantity of the tray, and the device pocket leaving, an algorithm was developed for defining and detecting the above defect types. Therefore, the developed handling system could extend the application of the stack of the c-tray and provide a quantity verification inspection on the packing processing. The machine operation control program, which can ensure the optimal inspection image to match the scan speed, was developed and the control program that can process the user gui and the vision image utilizing the control was developed. Overall, a mechanical system that is practicable for obtaining an image and processing the vision data was designed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.703-710
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• 2018

Although various efforts have been made every year to reduce electric fire accidents such as accident analysis and inspection for electric fire accidents, there is no effective countermeasure due to lack of effective decision support system and existing cumulative data utilization method. The purpose of this study is to develop an algorithm for predicting electric fire based on data such as electric safety inspection data, electric fire accident information, building information, and weather information. Through the pre-processing of collected data for each institution such as Korea Electrical Safety Corporation, Meteorological Administration, Ministry of Land, Infrastructure, and Transport, Fire Defense Headquarters, convergence, analysis, modeling, and verification process, we derive the factors influencing electric fire and develop prediction models. The results showed insulation resistance value, humidity, wind speed, building deterioration(aging), floor space ratio, building coverage ratio and building use. The accuracy of prediction model using random forest algorithm was 74.7%.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.3
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• pp.56-62
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• 2022

The tank engine clutch flange constitutes a tank on which the engine and transmission of the tank are mounted. The engine clutch flange is fabricated using a difficult-to-cut material that exhibits high strength and hardness. It is difficult to process and requires considerable processing expertise. In addition, the engine clutch flange for the tank requires high machining precision because it is a system in which the connection is detachable. Because it requires high processing precision, the measurement of products equally important as processing. However, productivity is low owing to the significant amount of time required to measure each product using a three-dimensional coordinate measuring machine. Hence, this study is conducted to improve the productivity of the female tank engine clutch flange. Dedicated hobs and jigs are designed and manufactured to convert the existing end-mill cutting processing into hobbing cutting processing. An engine clutch for the tanks is manufactured using the manufactured dedicated hob and jig, and the shortening time is verified by measuring the processing time. In addition, a jig for inspection is designed and manufactured to measure the precision of the product. To verify the inspected product, the product precision is measured using a contact-type three-dimensional coordinate measuring machine and a surface roughness measuring instrument. The study confirmed that the productivity of the engine clutch flange product for tanks can be improved by simplifying the process, reducing the processing time, and simplifying product inspection.

• Smart Media Journal
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• v.12 no.7
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• pp.9-17
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• 2023

Plant diseases and pests affect the growth of various plants, so it is very important to identify pests at an early stage. Although many machine learning (ML) models have already been used for the inspection and classification of plant pests, advances in deep learning (DL), a subset of machine learning, have led to many advances in this field of research. In this study, disease and pest inspection of abnormal crops and maturity classification were performed for normal crops using YOLOX detector and MobileNet classifier. Through this method, various plant pest features can be effectively extracted. For the experiment, image datasets of various resolutions related to strawberries, peppers, and tomatoes were prepared and used for plant pest classification. According to the experimental results, it was confirmed that the average test accuracy was 84% and the maturity classification accuracy was 83.91% in images with complex background conditions. This model was able to effectively detect 6 diseases of 3 plants and classify the maturity of each plant in natural conditions.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.5
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• pp.20-29
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• 2024

The chloride diffusion coefficient is a critical indicator for assessing the durability of concrete marine substructures. This study develops a prediction model for the chloride diffusion coefficient using data from concrete bridges located in marine exposure zones (atmospheric, splash, tidal), an aspect that has not been considered in previous studies. Chloride profile data obtained from these bridge substructures were utilized. After data preprocessing, machine learning models, including Random Forest (RF), Gradient Boosting Machine (GBM), and K-Nearest Neighbors (KNN), were optimized through hyperparameter tuning. The performance of these models was developed and compared under three different variable sets. The first model uses six variables: water-to-binder (W/B) ratio, cement type, coarse aggregate volume ratio, service life, strength, and exposure environment. The second model excludes the exposure environment, using only the remaining five variables. The third model relies on just three variables: service life, strength, and exposure environment factors that can be obtained from precision safety diagnostics. The results indicate that including the exposure environment significantly enhances model performance for predicting the chloride diffusion coefficient in concrete bridges in marine environments. Additionally, the three variable model demonstrates that effective predictions can be made using only data from precision safety diagnostics.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.105-126
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• 2023

The domestic used car market continues to grow along with the used car online platform service. The used car online platform service discloses vehicle specifications, accident history, inspection history, and detailed options to service consumers. Most of the preceding studies were predictions of used car prices using vehicle specifications and some options for vehicles. As a result of the study, it was confirmed that there was a nonlinear relationship between used car prices and some specification variables. Accordingly, the researchers tried to solve the nonlinear problem by executing a Machine Learning model. In common, the Regression based Machine Learning model had the advantage of knowing the actual influence and direction of variables, but there was a disadvantage of low Cost Function figures compared to the Decision Tree based Machine Learning model. This study attempted to predict used car prices of six domestic brands by utilizing both vehicle specifications and vehicle options. Through this, we tried to collect the advantages of the two types of Machine Learning models. To this end, we sequentially conducted a regression based Machine Learning model and a decision tree based Machine Learning model. As a result of the analysis, the practical influence and direction of each brand variable, and the best tree based Machine Learning model were selected. The implications of this study are as follows. It will help buyers and sellers who use used car online platform services to predict approximate used car prices. And it is hoped that it will help solve the problem caused by information inequality among users of the used car online platform service.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.684-692
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• 2016

In the manufacturing process of the LQFP/TQFP (Low-profile Quad Flat Package/Thin Quad Flat Package), the requirement of a 3 dimensional inspection is increasing rapidly and a 3D inspection of the shape of a chip has become an important report of quality control. This study developed a 3 dimensional measurement system based on PMP (Phase Measuring Profilometry) for an inspection of the LQFP/TQFP chip and image processing algorithms. The defects of the LQFP/TQFP chip were classified according to the dimensions. The 2 dimensional optical system was designed by the dorm illumination to achieve constant light distribution, In the 3 dimensional optical system, PZT was used for moving 90 degree in phase. The problem of 2 ambiguity was solved from the measured moir? pattern using the ambiguity elimination algorithm that finds the point of ambiguity and refines the phase value. The proposed 3D measurement system was evaluated experimentally.