• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.39-51
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• 2004

Product factory is a real-time financial product design system for the Internet customers. The hybrid product is a product taking combined characteristics of two different products. Hybrid product factory is a product factory that designs hybrid products from two different products based on both business rules and customer requirements. Though the importance of product factory is emphasized in the industry, there has not been much research peformed regarding product factory. In this research, we developed a product factory system that designs hybrid products. To design a hybrid product, it is necessary to have a method to combine attributes and values of two different products, and a method to control the combining operations to properly reflect business requirements. In this research, we developed low different combining operators and business rule representations. rn addition, to prove the effectiveness of this methods, we implemented a prototypical system and demonstrated on cases regarding financial loan products.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.191-194
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• 2003

Product factory is a real-time financial product design system for the Internet customers. Recently, as the number of the Internet customers increases, the importance of the product factory becomes more emphasized. However, there is not much research performed regarding its definition, properties, requirements, nor implementation. In this research, we make a clear definition of product factory, and analyze the requirements of the system from the perspectives of functions and services, and we propose an architecture that reflects the analyzed requirements. In additions, we implemented a prototypical system based on the proposed architecture to prove the usefulness of this research.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.107-115
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• 2017

Recently, much attention in building smart factory have been dramatically increased. Despite the growing interest in smart factory, few guidelines exist how to successfully build smart factory. The purpose of this study is to investigate successful cases in building smart factory in Korea. Drawing on the analysis of successful cases, we suggest the valuable guidelines and directions toward success of smart factory. As a result, in the case of large-size firms, it is an effective strategy that expanding from a model factory to whole factory for successful smart factory building. In addition, in the case of medium and small-size firms, it is an effective strategy that upgrading from low-level step to high-level step for successful smart factory building. Therefore, this study provides companies and government with specific and practical success strategies as well as industrial policy improvements.

• KNOM Review
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• v.23 no.1
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• pp.18-25
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• 2020

Recently, a research on a smart factory was developed from a concept of factory automation(FA) to the formation of collecting and analyzing data. This trend is accelerated as the development of communication technology(5G) and IoT devices are developed in various ways according to the field situation. In addition, digital transformation has been actively conducted in the strengthening corporate competitiveness, and various optimization studies are being conducted through process re-adjustment by combining data received from various IoT equipment and automated facilities. Therefore, in this paper, we propose a system architecture and its related components in diagnosing and repairing facility failure using a prediction system which is one of the related researches.

• Journal of the Korea Society for Simulation
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• v.31 no.1
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• pp.29-41
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• 2022

As one of the alternatives to solve the problem of unstable food supply and demand imbalance caused by abnormal climate change, the need for plant factories is increasing. Airflow in plant factory is recognized as one of important factor of plant which influence transpiration and heat transfer. On the other hand, Digital Twin (DT) is getting attention as a means of providing various services that are impossible only with the real system by replicating the real system in the virtual world. This study aimed to develop a digital twin model for airflow prediction that can predict airflow in various situations by applying the concept of digital twin to a plant factory in operation. To this end, first, the mathematical formalism of the digital twin model for airflow analysis in plant factories is presented, and based on this, the information necessary for airflow prediction modeling of a plant factory in operation is specified. Then, the shape of the plant factory is implemented in CAD and the DT model is developed by combining the computational fluid dynamics (CFD) components for airflow behavior analysis. Finally, the DT model for high-accuracy airflow prediction is completed through the validation of the model and the machine learning-based calibration process by comparing the simulation analysis result of the DT model with the actual airflow value collected from the plant factory.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.91-100
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• 2022

Major developed countries are seriously considering smart factories to increase their manufacturing competitiveness. Smart factory is a customized factory that incorporates ICT in the entire process from product planning to design, distribution and sales. This can reduce production costs and respond flexibly to the consumer market. The smart factory converts physical signals into digital signals, connects machines, parts, factories, manufacturing processes, people, and supply chain partners in the factory to each other, and uses the collected data to enable the smart factory platform to operate intelligently. Enhancing personalized value is the key. Therefore, it can be said that the success or failure of a smart factory depends on whether big data is secured and utilized. Standardized communication and collaboration are required to smoothly acquire big data inside and outside the factory in the smart factory, and the use of big data can be maximized through big data analysis. This study examines big data analysis and standardization in smart factory. Manufacturing innovation by country, smart factory construction framework, smart factory implementation key elements, big data analysis and visualization, etc. will be reviewed first. Through this, we propose services such as big data infrastructure construction process, big data platform components, big data modeling, big data quality management components, big data standardization, and big data implementation consulting that can be suggested when building big data infrastructure in smart factories. It is expected that this proposal can be a guide for building big data infrastructure for companies that want to introduce a smart factory.

• IE interfaces
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• v.16 no.1
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• pp.63-69
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• 2003

Virtual Manufacturing is a technology facilitating effective development and agile production of products via computer models representing physical and logical schema and the behavior of the real manufacturing systems including manufacturing resources, environments and products. For the successful application of this technology, a virtual factory as a well-designed and integrated environment is essential. To construct a virtual factory in effective and concurrent manners, a supporting information infrastructure for managing diverse models of virtual factory is very important. In this paper, we constructed the web-based information management system for many engineering activities related with a virtual factory. Using this system, users can handle all information and diverse digital files including attributes, parameters, 3-D CAD files, simulation models, and etc. of a cell, line and whole factory. We expect that this information management system for a virtual factory helps us achieve great time savings and advances in accuracy for construction and maintenance activities of virtual factories.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.161-164
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• 2018

최근 제조업의 근로 시간 단축 및 전문 노동력의 감소로 인하여 발생할 수 있는 문제를 개선할 수 있는 스마트 팩토리(Smart Factory)가 주목받고 있다. 스마트 팩토리는 생산품의 불량률을 줄이고, 숙련공 없이 비숙련공만으로 현장 가동이 가능하다는 점 등의 긍정적 효과를 기대할 수 있다. 그러나 스마트 팩토리는 높은 설비 도입 비용, 업무 시스템 재설계 등의 문제점이 등이 있으며, 특히 보안의 취약성이 심각하다. 그렇기 때문에 많은 기업이 현실에서 스마트 팩토리를 도입하는 어려움을 겪고 있다. 본 논문에서는 스마트 팩토리의 다양한 보안 사고를 유형 및 정형화시키고 여러 보안 사고를 유발하는 취약한 부분을 구체화하여 스마트 팩토리의 보안 연구의 방향성을 제시하고자 한다.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.89-97
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• 2015

Plant factory was started in Europe in the 1960. Thanks to the development of seeds science, nutrient study, environment control technology and automated systems, it has developed into the form of full artificial light system. In recent years, productivity of plant factory has increased with the convergence of ICT. An interest in plant factory has increased with several outstanding achievements. However, the plant factory industry is still stuck at an introductory stage and government investment has been reduced. In order to verify the feasibility of the plant factory, we conducted a survey targeting experts in politics, R&D and business field. We analyze the feasibility of investment in plant factory and strategies to enhance the competitiveness of plant factory.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.218-223
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• 1993

In this paper, we present a full digital control scheme which controls currents and speed of the permanent magnet AC servo motor with large range of bandwidth and high performance. The current equations of the permanent magnet AC servo motor are linearized by feedback linearization technique. Both acceleration feedforward terms and IP controllers, whose gains are functions of motor speed, are used in order to control motor currents. In addition the phase delays in current control loops are compensated by placing phase lead-lag compensators after current commands, which make it possible to avoid high gains in the current controllers. Unity power factor can be achieved by the proposed current controller. Pulsewidth modulation is performed by way of the well-known comparison with a triangular carrier signals. The velocity controller is designed on the basis of the linearized model of the permanent magnet AC servo motor by the proposed current controller. The performance of the entire control system is analyzed in the presence of uncertainty in the motor parameters. The proposed control scheme is implemented using the digital signal processor-based controller composed of an Analog Device ADSP 2111 and a NEC78310. The pulsewidth modulation (PWM) signals are generated through a custom IC, SAMSUNG-PWM1, which has the outputs of current controllers as input. The experimental results show that the permanent magnet AC servo motor can be always driven with high dynamic performance by the proposed full digital control scheme of motor speed and motor current.