• 디지털산업정보학회논문지
• /
• 제12권1호
• /
• pp.1-12
• /
• 2016

The current economic crisis is making new demands on manufacturing industry, in particular, in terms of the flexibility and efficiency of production processes. This requires production and administrative processes to be meshed with each other by means of IT systems to optimise the use and capacity utilisation of machines and lines but also to be able to respond rapidly to wrong developments in production and thus to minimise adverse impacts on the business. The future scenario of the "smart factory" represents the zenith of this development. The factory can be modified and expanded at will, combines all components from different manufacturers and enables them to take on context-related tasks autonomously. Integrated user interfaces will still be required at most for basic functionalities. The complex control operations will run wirelessly and ad hoc via mobile terminals such as PDAs or smartphones. The comnination of IoT, and Big Data optimisation is bringing about huge opportunities. these processes are not just limited to manufacturing, anywhere a supply chain environment exists can benefit from information provided by linked devices and access to big data to inform their decision support. Building a smart factory with smart assets at its core means reaching those desired new levels of productivity and efficiency. It means smart products that leverage advanced traceability, connectivity and intelligence. For businesses, it means being able to address the talent crunch through more autonomous. In a Smart Factory, machinery and equipment will have the ability to improve processes through self-optimization and autonomous decision-making.

• 전기학회논문지
• /
• 제63권5호
• /
• pp.713-718
• /
• 2014

DC urban railway power system consists of DC power network and AC power network. The DC power network supplies electric power to railway vehicles and the AC power network supplies electric power to station electric equipment. Recently, because of power consumption reduction and peak load shaving, intelligent measurement of regenerative energy and renewable energy adapted on DC urban railway is required. For this reason, DC smart metering system for DC power network shall be developed. Therefore, in this paper, DC voltage sensor, current sensor, and DC smart meter were developed and evaluated by performance test. DC voltage sensor was developed for measuring standard voltage range of DC urban railway, and DC current sensor was developed as hall effect split core type in order to install in existing system. DC smart meter possesses function of general intelligent electric power meter, such as measuring electricity and wireless communication etc. And, DC voltage sensor showed average 0.17% of measuring error for 2,000V/50mA, and current sensor showed average 0.21% of measuring error for ${\pm}2,000V/{\pm}4V$ in performance test. Also DC smart meter showed maximum 0.92% of measuring error for output of voltage sensor and current sensor. In similar environment for real DC power network, measuring error rate was under 0.5%. In conclusion, accuracy of DC smart metering system was confirmed by performance test, and more detailed performance will be verified by further real operation DC urban railway line test.

• 정보화정책
• /
• 제26권1호
• /
• pp.46-61
• /
• 2019

4차 산업 혁명은 산업도 교육도 대변혁을 예고하고 있다. 본 연구는 부동산 산업을 위한 교육플랫폼 제안연구로써 부동산의 최유효활용을 위해 Smart Space를 구현하는 인재교육을 목적으로 부동산 산업 인재들이 갖추어야 할 기본 RETech(Real Estate Technology)을 학습할 수 있는 SSEP(Smart Space EduPlatform)을 제안하였다. 우선, SSEP의 생태계는 지속가능성이 확보될 수 있는 기부시스템, 콘텐츠 제작도구 및 학습참여도구 등 다양한 기술적 기능, 학습자 교수자 조력자 형태의 자유로운 학습행위체계로 움직인다. 다음으로 SSEP의 서비스는 학습범주 즉, 계획 및 설계, 의사결정, 관리, 경제, 건설, 설비 6개 범주 하에 17개 중요한 RETech 강의학습 서비스와 PBL(Project-Based Learning)기반의 교육과정서비스를 제공한다. 강의서비스는 동영상 학습 콘텐츠, 부가학습자료, 학습관리 서비스가 제공되고 교육과정서비스는 교수자 워크숍, 학습자 모집 및 등록 관리, 교육과정운영 서비스들이 제공된다.

• 한국컴퓨터정보학회논문지
• /
• 제24권5호
• /
• pp.49-58
• /
• 2019

In this paper, we propose an edge cloud platform architecture for implementing smart factory. The edge cloud platform is one of edge computing architecture which is mainly focusing on the efficient computing between IoT devices and central cloud. So far, edge computing has put emphasis on reducing latency, bandwidth and computing cost in areas like smart homes and self-driving cars. On the other hand, in this paper, we suggest not only common functional architecture of edge system but also light weight cloud based architecture to apply to the specialized requirements of smart factory. Cloud based edge architecture has many advantages in terms of scalability and reliability of resources and operation of various independent edge functions compare to typical edge system architecture. To make sure the availability of edge cloud platform in smart factory, we also analyze requirements of smart factory edge. We redefine requirements from a 4M1E(man, machine, material, method, element) perspective which are essentially needed to be digitalized and intelligent for physical operation of smart factory. Based on these requirements, we suggest layered(IoT Gateway, Edge Cloud, Central Cloud) application and data architecture. we also propose edge cloud platform architecture using lightweight container virtualization technology. Finally, we validate its implementation effects with case study. we apply proposed edge cloud architecture to the real manufacturing process and compare to existing equipment engineering system. As a result, we prove that the response performance of the proposed approach was improved by 84 to 92% better than existing method.

• 스마트미디어저널
• /
• 제13권1호
• /
• pp.18-23
• /
• 2024

스마트팜의 전력 효율 관리는 기후 변화와의 연계로 중요성을 가지고 있다. 기후 변화가 농업에 부정적인 영향을 미치는 가운데, 미래의 농업은 스마트팜을 활용하여 기후 영향을 최소화할 것으로 예상되고 있으나 스마트팜의 전력 소비는 현재의 전기 생산 체제로 인해 기후 위기를 악화시킬 우려가 있다. 이에 따라 스마트팜의 전력 사용을 효율적으로 관리하고 최적화하는 것이 필수적이다. 본 연구에서는 스마트팜 장비의 전력 사용량을 실시간으로 모니터링하고, GRU를 활용하여 1시간 뒤의 전력 사용량을 예측하는 시스템을 제안한다. CT 센서를 설치하여 전력량을 수집하고, 이를 분석하여 이상 패턴을 탐지하고 예방한다. 또한 IoT 기술과 결합하여 전체 전력 사용량을 효율적으로 관리하고 모니터링한다. 이를 통해 전력 사용을 최적화하고, 에너지 효율성을 향상시켜 탄소 배출을 줄일 수 있다. 이 시스템은 스마트팜의 에너지 관리뿐아니라 전반적인 에너지 사용 효율성을 향상시킬 것으로 기대된다.

• 한국건설관리학회논문집
• /
• 제23권2호
• /
• pp.85-94
• /
• 2022

건설산업은 생산성, 인력, 산업재해 측면에서 어려운 과제에 직면해 있다. 4차 산업혁명과 함께 다양한 첨단기술이 대두되면서, 건설분야에서는 이런 문제들을 첨단기술을 활용해 해결하려 노력하고 있다. 그 일환으로 다수 및 다종의 건설장비가 투입되는 토공현장에서 생산성과 안전성을 높이기 위한 건설장비 관제시스템을 개발하고 있는 중이다. 건설장비 관제시스템은 건설장비의 이동경로를 최적화해 생산성을 높이는 기능이 필수이다. 트럭의 현장 내 이동경로를 최적화하려면, 가설도로 위치를 최적화해야만 한다. 하지만 현재 가설도로의 품질에 관한 사항만 규정되어 있을 뿐, 효율적인 방식으로 가설도로의 위치를 결정하는 정형화된 프로세스는 없는 상황이다. 이에 본 논문에서는 현장조사와 면담/설문조사를 통해 가설도로의 위치결정과 관련된 요소 및 그 중요도를 파악한 뒤 이를 기반으로 가설도로의 위치 결정을 위한 방법론을 제시하였다. 이후 사례연구를 통해 해당 방법론이 토공작업의 생산성 향상에 도움이 됨을 확인하였다.

• 대한임베디드공학회논문지
• /
• 제15권2호
• /
• pp.79-85
• /
• 2020

IIoT stands for Industrial Internet of Things used in manufacturing, healthcare, and transportation in networked smart factories. Recently, IIoT's environment requires an automated control system through intelligent cognition to improve efficiency. In particular, IIoT can be applied to automatic calibration of production equipment for improved management in industrial environments. Such automation systems require a wireless network for transmitting industrial data. Self-calibration systems in laser transmission paths using wireless networks can save resources and improve production quality by real-time monitoring and remote control of laser transmission path. In this paper, we propose a wireless networked system for self-calibration of laser equipment that requires a laser transmission path, and we show the results of the prototype evaluation. The self-calibration system of laser equipment measures the coordinates of the laser points with sensors and sends them to the host using the proposed application protocol. We propose a wireless network service for the wired motor controller to align the laser coordinates. Using this wireless network, the host controls the motor by sending a control command of the motor controller in an HTTP message based on the received coordinate values. Finally, we build a prototype system of the proposed design to verify the detection performance and analyze the network performance.

• 한국BIM학회 논문집
• /
• 제11권2호
• /
• pp.24-32
• /
• 2021

Recently, starting with smart construction research, interest in technology that automates construction site management using artificial intelligence technology is increasing. In order to automate construction site management, it is necessary to recognize objects such as construction equipment or workers, and automatically analyze the relationship between them. For example, if the relationship between workers and construction equipment at a construction site can be known, various use cases of site management such as work productivity, equipment operation status monitoring, and safety management can be implemented. This study derives a real-time object detection platform architecture that is required when performing construction site management using deep learning technology, which has recently been increasingly used. To this end, deep learning models that support real-time object detection are investigated and analyzed. Based on this, a deep learning model development process required for real-time construction site object detection is defined. Based on the defined process, a prototype that learns and detects construction site objects is developed, and then platform development considerations and architecture are derived from the results.

• 한국건축시공학회지
• /
• 제16권6호
• /
• pp.535-544
• /
• 2016

정부차원에서 한국형 'K-Smart City'모델을 활용하여 건설과 ICT산업의 융합사업인 해외 Smart City시장 진출을 적극 추진하고 있다. Smart City사업의 특성상 시설물 시공품질과 ICT시스템 개발품질이 동시에 확보되어야 Smart City시설물의 품질향상이 가능하다. 그러나 Smart City사업 특성에 맞는 통합된 품질관리 프로세스 및 가이드가 미흡한 실정이다. 이로인해 국내 실증 프로젝트에서는 건설 품질관리와 ICT 품질관리가 분리된 형태로 관리되어 Smart City시공품질이 저하되는 문제점이 발생되고 있다. 본 연구에서는 Smart City프로젝트 구축단계의 시공품질 향상을 위하여 현장시공(통합운영센터 및 현장설비)과 ICT시스템 개발공정이 융합된 통합품질관리 프로세스를 연구하였다. Smart City사례 프로젝트에 본 연구에서 제안한 통합품질관리 프로세스를 적용한 결과, 시공검측시 시설물 부적합건 발생이 22% 감소하였고, ICT인프라 납품자재의 품질시험을 추가로 실시하여 18%의 부적합 사항을 설치전에 조치하여 시공품질이 향상되는 것을 확인하였다. 본 연구에서 제안한 통합품질관리 프로세스는 향후 Smart City 현장에 활용이 가능할 것으로 기대한다.

• International journal of advanced smart convergence
• /
• 제4권1호
• /
• pp.137-144
• /
• 2015

Development of the yarn sorting equipment (khonhook) by slide way due to the principle of engineering that cause of workers on the long of motion time. The data was collected from the weaving group Ban Nongkok village, Nakornratchasima Province, THAILAND. According to the study, the step of yarn sorting (konhook) was one of the steps that affect long of motion time. The problem was the inadequate capacity equipment. The objective of research was to study and develop the yarn sorting equipment (konhook). The fabric used in the study was 64 meters in length and 1 meter in width. Researchers studied the processes the yarn sorting (konhook) which it consists of seven sub steps, 1) the thread tube setting, 2) yarn bunching, 3) tying a knot at the end of yarn, 4) looping the yarn into a pillar, 5) sorting the yarn (konhook), 6) crossing pillars and 7) taking out the yarn. Researchers focused on studying yarn sorting process (konhook) by designing and creating a device for yarn sorting (konhook) for reducing yarn sorting (konhook) time by the original method performance indicators. The results found that the developed yarn sorting equipment (konhook) ) by slide way could reduce working time from 7.24 minutes to 6.08 minutes of the original equipment yarn sorting (konhook). This means it could make the process 16.02 % faster. This also helps reducing the distance of workers' movement from 2,234 meters to 8 meters. This is 99.64 % shorter.