• 한국융합학회논문지
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• 제9권3호
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• pp.1-14
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• 2018

4차 산업혁명은 제조업을 시작으로 전 산업의 환경을 빠르게 변화시키고 있으며, 4차 산업혁명에 포함된 신기술이 이러한 변화를 주도하고 있다. 국내 중소기업은 4차 산업혁명에 따른 변화가 필요하며, 특히 스마트 공장의 도입이 필요한 시기이다. 본 연구는 스마트 공장 도입에 대해 중소기업의 현황을 SWOT 분석을 통해 성공적인 도입을 위한 전략을 제언하였다. 강점 활용 전략으로 첫째 우수한 경쟁력을 통한 활성화, 둘째 우수한 기술력과 정보화를 이용, 셋째 세계적인 네트워크 기반의 환경을 활용을 제언하였으며, 약점 보완 전략으로는 첫째 정보보안에 대한 인식 제고, 둘째 기술 표준화 수립을 위한 평가 체계 확립, 셋째 전문 인력 확보를 위한 인력 양성 추진으로 제언하였다. 본 연구의 시사점은 중소기업에 효과적인 전략과 4차 산업 혁명에 따른 다양한 외부의 전략을 이해하고 대비할 수 있도록 스마트 공장의 필요성에 대한 제언을 하였다.

• 융복합기술연구소 논문집
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• 제7권2호
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• pp.21-23
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• 2017

Smart Factories could be regarded as a result of the integration of various key technologies of the fourth industrial revolutions. In smart factory, the IoT (Internet of things) is applied to capture the data generated by the production facility, store and analyze data generated in real time using Big Data technology. In addition, 3D printers are used to print expensive and complex parts, industrial robots supply materials and parts to the production site, store finished products in warehouses. In this paper, we introduced the definition of smart factory and change of job market. Also, we summarize several national policies to support enhancing transformation process of smart factory.

• 전자통신동향분석
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• 제36권1호
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• pp.99-108
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• 2021

Digital twins are digital replicas of objects and systems in the real world. These digital replicas in a virtual environment can be connected with smart sensors and a variety of analyses, and simulations of real-time data from these sensors enable effective the operation, rapid feedback, and future predictions of real world phenomena. Until now, digital twins have been adopted and used mainly in the field of manufacturing, especially for smart factories. As digital twins are expected to be useful not only for productivity improvement but also for social problem solving, it is predicted that they will be extended to other fields such as those of transportation and cities. Digital twins will especially help realize smart cities through real-time monitoring, operation, and predictions using virtual digital twin cities. This paper summarizes the trends in digital twins for smart cities, the concept of digital twins, their application to smart cities, the strategies of various countries, and the development status of companies.

• Journal of Multimedia Information System
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• 제9권3호
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• pp.209-218
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• 2022

Industrial IoT applications, including smart factories, require two problem-solving to build data monitoring systems required by services from distributed IoT sensors (smart sensors). One is to overcome proprietary protocols, data formats, and hardware differences and to uniquely identify and connect IoT sensors, and the other is to overcome the problem of changing the server-side data storage structure and sensor data transmission format according to the addition or change of service or IoT sensors. The IEEE 1451.4 standard-based or IPMI specification-based smart sensor technology supports the development of plug-and-play sensors that solve the first problem. However, there is a lack of research that requires a second problem-solving, which requires support for the plug-in of IoT sensors into remote services. To propose a solution for the integration of these two problem-solving, we present a IoT sensor platform, a service system architecture, and a service plugin protocol for the MQTT-based IIoT application environment.

• 융합경영연구
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• 제8권3호
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• pp.23-36
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• 2020

Purpose: The purpose of this study is to identify the strategic direction of organizations and their employees to efficiently utilize smart factories and enhance business performance among Korean manufacturing companies. Research design, data, and methodology: We derived a structured research model to check the mediated effect of utilization of smart factory between the characteristics of smart factory and the innovation activities. Results: Quality characteristics of smart factory and Innovation activities were all found to have a statistically significant effect on utilization of smart factory, utilization of smart factory was found to have a statistically significant effect on the business performance. And it has been shown that the utilization of smart factory is partially mediated relative to the quality characteristics of smart factory and business performance and relative to innovation activities and business performance. Conclusions: Smart factory builders can reflect the areas that affect utilization of the smart factory in their strategies by considering the quality characteristics of the smart factory and innovation Activities. Therefore, smart factory builders can identify the quality characteristics of smart factory and reflect them in the process and analyze active utilize measures through the innovative activities of the employees of the organization, thereby influencing business performance.

• 산업경영시스템학회지
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• 제42권4호
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• pp.76-83
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• 2019

The South Korean government is actively assisting the supply of the smart factory solutions to SMEs (Small & Medium-sized Enterprises) according to its manufacturing innovation 3.0 policy for the smart manufacturing as the 4th industrial revolution era unfolds. This study analyzed the impacts of the smart factory solutions, which have been supplied by the government, on the companies performances. The effects of the level of smart factory and the operation capabilities for the smart factory solutions on company performances, and the mediating effects of manufacturing capabilities have been analyzed using SPSS and AMOS. The data for this survey-based study were collected from the SMEs which implemented the smart factory solutions since 2015. The results show that the level of smart factory solutions adopted and operation capabilities for the smart factories do not have direct effects on the company performances, but their mediating effects on the manufacturing capabilities matter and the manufacturing capabilities effect directly on the company performances. In addition significant factors boosting the operation capability for the smart factory and the levels of the smart factory solutions are identified. Finally, the policy direction for enhancing the smart factory effects is presented, and the future research directions along with the limitations are suggested.

• 한국인터넷방송통신학회논문지
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• 제19권3호
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• pp.73-82
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• 2019

스마트팩토리를 구축하기 위해서는 CPPS(Cyber Physical Production System)의 구축은 필수적으로 동반되어야 하는 중요한 시스템이다. CPPS를 통해서 물리적 공장을 디지털 기반의 사이버 세상으로 옮겨오고 이를 지능적, 자율적으로 모니터링하고 제어하는 것이 스마트팩토리의 실체이다. 하지만 기존에 제시된 CPPS의 아키텍처들은 추상적인 모델링 형태의 아키텍처만 제시하고 있으며, 스마트팩토리에서 데이터를 수 집 교환을 위한 국제 표준인 OPC UA Framework(Open Platform Communication Unified Architecture)을 CPPS의 기본적인 체계로 적용한 연구는 부족하였다. 이에 아키텍처 구성 실제 공장에 적용 가능한 CPPS 아키텍처로 분산되어진 필드 데이터를 수집하여 중앙에 집중화 된 서버에서 집중된 데이터 처리가 되어야만 클라우드와 IoT를 모두 포함할 수 있는 CPPS를 구현 가능하다. 본 연구에서는 중앙 처리 OPC UA Framework을 준수한 OPC UA를 기술 체계를 기반으로 중앙의 OPC UA Server를 통해 CPPS 아키텍처를 구현하고 OPC UA 모델링 처리를 통해 CPPS 논리 프로세스와 데이터 처리 프로세스가 자동으로 생성되는 방법을 포함한 CPPS 아키텍처를 제안하고 모델 공장을 실제로 구현하여 그 성능과 가용성에 대해서 연구하였다.

• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.109-121
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• 2020

As a decrease in labor became a serious issue in the manufacturing industry, smart factory technology, which combines IT and the manufacturing business, began to attract attention as a solution. In this study, we have designed and implemented a real-time remote management system for smart factories, which is connected to an IoT sensor and gateway, for plastic manufacturing plants. By implementing the REST API in which an IoT sensor and smart gateway can communicate, the system enabled the data measured from the IoT sensor and equipment status data to the real-time monitoring system through the gateway. Also, a web-based management dashboard enabled remote monitoring and control of the equipment and raw material processing status. A comparative analysis experiment was conducted on the suggested system for the difference in processing speed based on equipment and measurement data number change. The experiment confirmed that saving equipment measurement data using cache mechanisim offered faster processing speed. Through the result our works can provide the basic framework to factory which need implement remote management system.

• 한국기계가공학회지
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• 제20권9호
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• pp.90-96
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• 2021

As real-time data of factories can be collected using various sensors, the adaptation of intelligent unmanned processing systems is spreading via the establishment of smart factories. In intelligent unmanned processing systems, data are collected in real time using sensors. The equipment is controlled by predicting future situations using the collected data. Particularly, a technology for the prediction of tool wear and for determining the exact timing of tool replacement is needed to prevent defected or unprocessed products due to tool breakage or tool wear. Directly measuring the tool wear in real time is difficult during the cutting process in milling. Therefore, tool wear should be predicted indirectly by analyzing the cutting load of the main spindle, current, vibration, noise, etc. In this study, data from the current and acceleration sensors; displacement data along the X, Y, and Z axes; tool wear value, and shape change data observed using Newroview were collected from the high-speed, two-edge, flat-end mill machining process of SKD11 steel. The support vector machine technique (machine learning technique) was applied to predict the amount of tool wear using the aforementioned data. Additionally, the prediction accuracies of all kernels were compared.

• 한국분말재료학회지
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• 제27권2호
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• pp.111-118
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• 2020

The convergence of artificial intelligence with smart factories or smart mechanical systems has been actively studied to maximize the efficiency and safety. Despite the high improvement of artificial neural networks, their application in the manufacturing industry has been difficult due to limitations in obtaining meaningful data from factories or mechanical systems. Accordingly, there have been active studies on manufacturing components with sensor integration allowing them to generate important data from themselves. Additive manufacturing enables the fabrication of a net shaped product with various materials including plastic, metal, or ceramic parts. With the principle of layer-by-layer adhesion of material, there has been active research to utilize this multi-step manufacturing process, such as changing the material at a certain step of adhesion or adding sensor components in the middle of the additive manufacturing process. Particularly for smart parts manufacturing, researchers have attempted to embed sensors or integrated circuit boards within a three-dimensional component during the additive manufacturing process. While most of the sensor embedding additive manufacturing was based on polymer material, there have also been studies on sensor integration within metal or ceramic materials. This study reviews the additive manufacturing technology for sensor integration into plastic, ceramic, and metal materials.