• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.216-221
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• 2022

The 4th industrial revolution is accelerating the transition to digital innovation in various aspects of our daily lives, and efforts for manufacturing innovation are continuing in the manufacturing industry, such as smart factories. The 4th industrial revolution technology in manufacturing can be used based on AI, big data, IoT, cloud, and robots. Through this, it is required to develop a technology to establish a production facility data collection and analysis system that has evolved from the existing automation and to find the cause of defects and minimize the defect rate. In this paper, we implemented a system that collects power, environment, and status data from production facility sites through IoT devices, quantifies them in real-time in a cloud computing environment, and displays them in the form of MQTT-based real-time infographics using widgets. The real-time sensor data transmitted from the IoT device is stored to the cloud server through a Rest API method. In addition, the administrator could remotely monitor the data on the dashboard and analyze it hourly and daily.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.95-121
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• 2023

This study aims to explore the combinations of services and technologies for academic libraries to use based on librarians' perception and establish effective service strategies accordingly. The literature review facilitated an understanding of Fourth Industrial Revolution technologies impacting the libraries. We discovered how technologies are transforming library services. We analyzed the academic library services to categorize their service structure. The survey revealed the necessity of introducing technology for each service category and the appropriate automation levels of services based on the perception of librarians. The survey results identified nine prioritized combinations of academic library services and technologies. Based on the analysis, we proposed the service-technology strategies for each category. This study has significance in exploring the potential for introducing and utilizing new technologies to enhance academic library services and exploring ways to combine services and technologies based on the common opinion of librarians.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.31-40
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• 2024

In the realm of domestic online fashion platform industry the manual registration of product information by individual business owners leads to inconvenience and reliability issues, especially when dealing with simultaneous registrations of numerous product groups. Moreover, bias is significantly heightened due to the low quality of product images and an imbalance in data quantity. Therefore, this study proposes a ResNet50 model aimed at minimizing data bias through oversampling techniques and conducting multiple classifications for 13 fashion categories. Transfer learning is employed to optimize resource utilization and reduce prolonged learning times. The results indicate improved discrimination of up to 33.4% for data augmentation in classes with insufficient data compared to the basic convolution neural network (CNN) model. The reliability of all outcomes is underscored by precision and affirmed by the recall curve. This study is suggested to advance the development of the domestic online fashion platform industry to a higher echelon.

• Animal Bioscience
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• v.37 no.4_spc
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• pp.775-785
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• 2024

Pork production is a significant agricultural enterprise in the United States and Canada. The United States is the third-largest global producer of pork and Canada ranks seventh in pork production. The North American Free Trade Agreement and its successor, the U.S.-Mexico-Canada Agreement, have facilitated trade and integration between the two countries. The majority of production systems are modern and intensive, characterized by large vertically integrated farms using advanced technologies. Both nations benefit from their status as major producers of feed grains, with the United States leading in corn and soybeans, while Canada excels in canola and barley production. The regulatory frameworks for food safety, animal welfare, and environmental stewardship differ slightly, with the FDA and USDA overseeing these aspects in the United States, and Health Canada and the Canada Food Inspection Agency in Canada. The United States and Canada also have well-established distribution networks for pork products, relying on both domestic and international markets. Export markets play a crucial role, with the United States being a major importer of Canadian pigs, and both countries exploring opportunities in Asia. Despite a rise in global demand, domestic pork consumption trends differ, with per capita consumption remaining stable in the USA and declining in Canada. Changing consumer preferences, including a demand for ethically raised and locally sourced pork, may influence production practices. Future trends in pig production include a focus on consumer concerns, sustainability, disease prevention, reduction of antimicrobial use, and advancements in technology. The industry is adapting to challenges such as disease outbreaks and changing regulations, with a strong emphasis on animal welfare. Labor and workforce considerations, along with advancements in technology and automation, are expected to shape the efficiency of pork production in the future.

• Tunnel and Underground Space
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• v.30 no.6
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• pp.540-550
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• 2020

Machine learning has been actively used in the field of automation due to the development and establishment of AI technology. The important thing in utilizing machine learning is that appropriate algorithms exist depending on data characteristics, and it is needed to analysis the datasets for applying machine learning techniques. In this study, advance rate is predicted using geotechnical and machine data of TBM tunnel section passing through the soil ground below the stream. Although there were no problems of application of statistical technology in the linear regression model, the coefficient of determination was 0.76. While, the ensemble model and support vector machine showed the predicted performance of 0.88 or higher. it is indicating that the model suitable for predicting advance rate of the EPB Shield TBM was the support vector machine in the analyzed dataset. As a result, it is judged that the suitability of the prediction model using data including mechanical data and ground information is high. In addition, research is needed to increase the diversity of ground conditions and the amount of data.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.170-202
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• 2001

Simulation is used to reduce a risk involved in the new project and decision-making in an organization and to save cost and time by forecasting different situations. The objectives of this research are to acknowledge the need of simulation through the real life sample and to encourage the use of the simulation method in the future consulting project by continuously making the necessary improvements. This research analyzed the effectiveness of the simulation based on the sample use of simulation method in 1994 and 1997 for the BPR project of certification issuance process at the Supreme Court. In order to evaluate the value of the proposed simulation model, we examined the gap, which existed between the simulation result and the operational data collected by visiting the actual sites where AROS (Automated Registry Office System: automation system developed by LG-EDS Systems) is being utilized. We also identified the causes for the existing gap. According to the analysis result, (1) the gap came from the status change of thinking that the concentration of certification issuance request has eased after the computerization, (2) the gap existed in the operational process because they failed to consider the situational factors of each registry office in the simulation model, and (3) lastly the gap came from the difficulty of formulating the mathematical model for predicting the complex and diverse behavior pattern of individuals requesting the certification issuance. In order to narrow the existing gaps, we made a proposal to improve the certification issuance process where software of certification issuance vending machine was upgraded in order to help the people to use the service conveniently, more part time workers were hared when there was a overload of certification issuance request, and the quality of the certification Issuance vending machine is improved, In this research, we examined an efficient way of resource allocation based on the simulation conducted in 1994 and 1997. By reflecting changes since the simulation of 1994 and allocating the clerk and machine based on the predicted results of the simulation, we maximized the efficiency of the certification issuance process. In conclusion, this research examined the future usability of simulation method based on the analysis result and identified the key issues to consider when using the simulation method in the future consulting project.

• Journal of the Korean Geotechnical Society
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• v.37 no.9
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• pp.25-36
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• 2021

Recently, the intelligent compaction technology for quality control of earthworks has brought attention as a quality control standard for earthworks. In this study, intelligent compaction technology and earthwork quality control methods were investigated and earthwork quality control procedures using intelligent compaction technology were considered based on field tests. Through the field compaction test of the silty sand (SM) fill material, it was confirmed that CMV and bearing capcaity index from plate load tests increased as the number of compactions increased. Based on the field test data, the average CMV and quality control target CMV were derived. The target CMV (34.2) was calculated through the correlation with the bearing capacity index of the plate load test, and the target CMV (36.6) was calculated through the analysis of the CMV increase rate. In this paper, the on-site compaction quality management procedure and methodology using intelligent compaction technology were discussed, and an intelligent compaction quality management method was proposed to promote the applicability of the technology.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.241-262
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• 2021

This paper reviewed the necessity of a information and communication technology (ICT)-based smart livestock system as a development strategy for the animal life industry in the future. It also predicted the trends of livestock and animal food until 2050, 30 years later. Worldwide, livestock raising and consumption of animal food are rapidly changing in response to population growth, aging, reduction of agriculture population, urbanization, and income growth. Climate change can change the environment and livestock's productivity and reproductive efficiencies. Livestock production can lead to increased greenhouse gas emissions, land degradation, water pollution, animal welfare, and human health problems. To solve these issues, there is a need for a preemptive future response strategy to respond to climate change, improve productivity, animal welfare, and nutritional quality of animal foods, and prevent animal diseases using ICT-based smart livestock system fused with the 4th industrial revolution in various aspects of the animal life industry. The animal life industry of the future needs to integrate automation to improve sustainability and production efficiency. In the digital age, intelligent precision animal feeding with IoT (internet of things) and big data, ICT-based smart livestock system can collect, process, and analyze data from various sources in the animal life industry. It is composed of a digital system that can precisely remote control environmental parameters inside and outside the animal husbandry. The ICT-based smart livestock system can also be used for monitoring animal behavior and welfare, and feeding management of livestock using sensing technology for remote control through the Internet and mobile phones. It can be helpful in the collection, storage, retrieval, and dissemination of a wide range of information that farmers need. It can provide new information services to farmers.

• Tunnel and Underground Space
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• v.32 no.1
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• pp.78-92
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• 2022

In this study, we proposed a diagnostics and assessment model for mining sites that can evaluate the smart mining technology level in a systematic and structured way. For this, the maturity of the smart mining was defined, and detailed assessment items of the diagnostics and assessment model for smart mining were derived by considering the smart factory diagnostics and assessment model (KS X 9001-3) used in the manufacturing industry. While maintaining the existing system, the existing 46 detailed assessment items were modified to be suitable for mining. As a result, a total of 29 detailed assessment items were derived in the areas of promotion strategy, process, information system and automation, and performance. Based on this, a questionnaire was designed to diagnose the level of smart mining technology, and assessment was performed by applying it to domestic iron mines. The level of smart mining technology in the study area was found to be level 2, and it could be inferred that it was about 40% lower than the average smart level of the general manufacturing industry. In addition, by using the developed model, it was possible to recognize the weak points of the mine at each stage of the introduction, operation, and advancement of smart mining, and to suggest investment and improvement directions.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.5
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• pp.799-810
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• 2022

Welding work is a production work method widely used throughout the industry, and various types of welding technologies exist. In addition, many methods are being studied to automate these welding operations using robots, but in the ship manufacturing field, welding such as painting, cutting, and grinding is also the most common operation, but the manual operation ratio is higher than in other industries. Such a high manual labor ratio in the field of ship manufacturing not only causes quality problems and production delays according to the skill of workers, but also causes problems in the supply and demand of manpower. Therefore, this paper analyzed the reason why the automation rate is low in welding work at ship manufacturing sites compared to other industries, and analyzed the production process and field environment for small and medium-sized ship manufacturing companies that repeatedly manufactured with a small quantity production method. Based on the analysis results, it is intended to propose a robot system that can easily move between workplaces and secure uniform welding quality and productivity by collaborating simple welding tasks with humans. Finally, the simulation environment is constructed and analyzed to secure the suitability of robot system application to current production site environment, work process, and productivity, rather than to develop and apply the proposed robot system. Through such pre-simulation and robot system suitability analysis, it is expected to reduce trial and error that may occur in actual field installation and operation, and to improve the possibility of robot application and positive perception of robot system at ship manufacturing sites.