• International Journal of Internet, Broadcasting and Communication
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• 제10권4호
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• pp.70-74
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• 2018

In order to ensure the flow of goods available and more flexible, reduce labor costs, many factories and industrial zones around the world are gradually moving to use automated solutions. One of them is to use Automated guided vehicles (AGV). Currently, there are a line tracing method as an AGV operating method, and a method of estimating the current position of the AGV and matching with a factory map and knowing the moving direction of the AGV. In this paper, we propose ceiling Light and guided line based moving direction estimation algorithm using multi-camera on the AGV in smart factory that can operate stable AGV by compensating the disadvantages of existing AGV operation method. The proposed algorithm is able to estimate its position and direction using a general - purpose camera instead of a sensor. Based on this, it can correct its movement error and estimate its own movement path.

• 대한임베디드공학회논문지
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• 제15권2호
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• pp.95-101
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• 2020

In situations where mobile robots are operated either by autonomous systems or human operators, such as smart factories, priority-based teleoperation is crucial for the multiple operators with different priority to take over the right of the robot control without conflict. This paper proposes a priority-based teleoperation system for multiple operators to control the robots. This paper also introduces an efficient joystick-based robot control command generation algorithm for differential-drive mobile robots. The proposed system is implemented with ROS (Robot Operating System) and embedded control boards, and is applied to Pioneer 3AT mobile robot platform. The experimental results demonstrate the effectiveness of the proposed joystick control command algorithm and the priority-based control input selection.

• 전자통신동향분석
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• 제34권2호
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• pp.51-59
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• 2019

Edge computing, which is computing on the edge of the network, is becoming a market value as a means of overcoming the fear of communication disconnection and delay reduction, which are the technical weaknesses of cloud computing. Edge computing is continuously expanding applications in various applications such as safety industry, smart factories, autonomous vehicles, mobile communications, and AR/VR. Looking at edge computing trends from Microsoft, IBM, HPE, and Dell EMC, current edge computing must be understood as an integral binding technology and not as a simple complement to the cloud. This paper examines market trends in edge computing and analyzes the impact of edge computing on major related industries.

• 한국산업융합학회 논문집
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• 제22권2호
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• pp.235-241
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• 2019

The shoe manufacturing process is very low compared to other industries due to the labor-intensive process. As automation and smart factories are becoming more and more automated, changes in the shoe manufacturing process are also needed. In this paper, we want to standardize the fuse manufacturing process by modularizing it. First, we defined the terms of shoeupper and fuse process, the shoe upper fuse process by function and classified it as a modular process. The fuse process can be modularized with pattern supply module, pattern recognition module, pattern laminate module, pattern waiting module, adhesion module, heat pressing module, transmission module, etc.

• 로봇학회논문지
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• 제14권1호
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• pp.1-7
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• 2019

Recently, smart factories have attracted much attention as a result of the 4th Industrial Revolution. Existing factory automation technologies are generally designed for simple repetition without using vision sensors. Even small object assemblies are still dependent on manual work. To satisfy the needs for replacing the existing system with new technology such as bin picking and visual servoing, precision and real-time application should be core. Therefore in our work we focused on the core elements by using deep learning algorithm to detect and classify the target object for real-time and analyzing the object features. We chose YOLO CNN which is capable of real-time working and combining the two tasks as mentioned above though there are lots of good deep learning algorithms such as Mask R-CNN and Fast R-CNN. Then through the line and inside features extracted from target object, we can obtain final outline and estimate object posture.

• 소성∙가공
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• 제31권2호
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• pp.103-108
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• 2022

Systematic quality control based on real time data is required for modern factories. This study introduced a method of predicting punch wear in the trimming process of automobile parts. Based on monitoring data of the mass production process using a bolt-type piezo sensor, it was shown that precursor symptoms of die wear could be predicted from the change in load pattern with respect to production volume. The load pattern that changed according to the wear of the die was verified by numerical analysis.

• 중국학논총
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• 제63호
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• pp.205-224
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• 2019

The results of the studies of China and Vietnam are as follows. First of all, in China, the labor market in China has been fully completing laws and regulations since the implementation of the labor contract law in 2008. Specifically, we analyzed the labor market in China for labor contracts, recruitment, and minimum wage. Next, in Vietnam, which the tertiary and quaternary industries are rapidly developing. The labor market is expected to increase because demand for foreign manpower, as the advancement of retail, finance, tourism services, Smart factories in the textile and sewing- do. The limitations of this study, however, are that there is not enough data to utilize official data for labor market analysis in China and Vietnam. If a practical investigation is conducted for analyzing the labor market in Vietnam due to the changes in the labor market

• 벤처혁신연구
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• 제5권2호
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• pp.111-127
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• 2022

4차산업혁명의 진전에 따라 스마트 팩토리에 대한 관심이 증대되고 있다. 정부차원에서 중소제조기업의 스마트 팩토리 지원 사업을 시행하고 있다. 이에 본 연구에서는 중소기업의 스마트 팩토리 도입 의도에 영향을 미치는 요인을 실증적으로 분석하였다. 특히 중소기업 CEO 의지, 종업원의 혁신 저항성, 정부지원에 대한 인식이 어떻게 도입의도에 영향을 미치는지에 초점을 두었다. 실증적인 분석을 위해 기술수용이론을 중심으로 중소기업이라는 특성과 스마트 팩토리의 기술적인 요인을 반영하여 연구 모형을 설정하였다. 이렇게 설정된 모형을 바탕으로 실증분석을 위해 중소기업 종사자를 대상으로 설문 조사를 하였다. 본 연구에서는 총 231부의 유효한 데이터를 분석에 활용하였다. 실증분석 결과는 다음과 같다. 연구 변인으로 도입된 성과기대, 사회적 영향, 기술활용역량, CEO 의지, 종업원의 혁신 저항성 모두 스마트 팩토리 도입 의도에 유의한 정(+)의 영향을 미치는 것으로 분석 되었다. 특히 종업원의 혁신 저항성은 스마트 팩토리 도입의도에 부(-)의 영향을 미치는 것으로 나타났다. 한편, 정부지원의 조절효과를 분석하기 위해 정부지원에 대한 기대가 높은 집단과 낮은 집단으로 나누었다. 그 결과 CEO의 의지, 종업원의 혁신 저항성, 사회적 영향이 스마트 팩토리 도입의도에 미치는 영향에 있어서 차이가 있는 것으로 나타났다. 반면, 성과기대, 기술활용역량이 스마트 팩토리 도입의도에 미치는 영향 관계에서는 유의한 차이가 발견되지 않았다. 이러한 실증 분석 결과를 바탕으로 본 연구가 지니는 학술적인 시사점과 실무적인 시사점을 제시하였다.

• 한국IT서비스학회지
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• 제21권2호
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• pp.97-107
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• 2022

Recently, interest in smart factories is increasing. Investments to improve intelligence/automation are also being made continuously in manufacturing plants. Facility automation based on sensor data collection is now essential. In addition, we are operating our factories based on data generated in all areas of production, including production management, facility operation, and quality management, and an integrated standard information system. When producing LCD polarizer products, it is most important to link trace information between data generated by individual production processes. All systems involved in production must ensure that there is no data loss and data integrity is ensured. The large-capacity data collected from individual systems is composed of key values linked to each other. A real-time quality analysis processing system based on connected integrated system data is required. In this study, large-capacity data collection, storage, integration and loss prevention methods were presented for optimization of LCD polarizer production. The identification Risk model of inspection products can be added, and the applicable product model is designed to be continuously expanded. A quality inspection and analysis system that maximizes the yield rate was designed by using the final inspection image of the product using big data technology. In the case of products that are predefined as analysable products, it is designed to be verified with the big data knn analysis model, and individual analysis results are continuously applied to the actual production site to operate in a virtuous cycle structure. Production Optimization was performed by applying it to the currently produced LCD polarizer production line.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제2권7호
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• pp.277-282
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• 2013

최근에 지능화된 자동차, 로봇, 공장 등에 대한 관심이 높아지면서 지능화된 모션 제어 응용을 손쉽게 작성할 수 있는 소프트웨어 플랫폼에 대한 필요성이 날로 커지고 있다. 이를 위해서 그 기능과 각종 하드웨어 지원이 풍부한 범용 운영체제를 사용하는 것이 바람직하지만, 일반적으로 개별 응용의 실시간 응답성이 항상 보장되지는 않는다. 본 논문은 범용 운영체제로서 리눅스가 산업용 실시간 시스템에 적합한지 평가하기 위해 ARM 기반 프로세서 Exynos4210 상에서 Xenomai 실시간 리눅스 패치를 적용하고 모션 제어 응용의 실시간 성능을 평가하였다. 평가결과, 백그라운드 작업 부하의 간섭에도 불구하고 모션 제어 응용에게 1ms 미만의 제어 주기를 안정적으로 제공할 수 있음을 확인하였다.