Knowledge-based power monitoring and fault prediction system for smart factories
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S.I. : NEW DIRECTIONS IN KNOWLEDGE-BASED PERSONAL COMPUTING
Knowledge-based power monitoring and fault prediction system for smart factories Eun Kim 1 & Duck-Haing Huh 2 & Seokhoon Kim 3 Received: 27 February 2019 / Accepted: 23 November 2019 # Springer-Verlag London Ltd., part of Springer Nature 2019
Abstract With the recent spread of the 4th Industrial Revolution, the intellectualization of industry is progressing rapidly. In particular, companies in various field are interested in converting existing factories into smart factory, and the number of cases where the smart factory template is applied is increasing. In this paper, we design and implement an IoT-based power monitoring and data collection system that enables monitoring of power consumption as well as the detection of abnormal power consumption in a smart factory. The system consists of power measurement devices, data analysis servers, and knowledge-based web and smartphone applications. The power measurement device uses IoT sensors to measure power consumption and sends collected data to the server. The server analyzes the data collected from the device using R and exploits the analysis results to provide predictions about the failure of equipment and facilities in the smart factory. From this point of view, we can expect improvement in not only cost-efficiency but also product quality. Keywords Smart factory . Power monitoring . Failure detection . Prediction
1 Introduction Beginning in Germany in the late 2000s with the aim of increasing efficiency in the social, economic, and industrial sectors by making existing industries more intelligent, the Industry 4.0 was accelerated by the IoT, BigData, Cloud computing, and AI technologies that were recently developed, thereby enabling the emergence of a new paradigm of in the 4th Industrial Revolution [1]. The 4th Industrial Revolution has been spreading across the industry in various forms,
* Seokhoon Kim [email protected] Eun Kim [email protected] Duck-Haing Huh [email protected] 1
MSC Education Department, Kyungnam University, Changwon, Korea
2
Electrical Engineering Department, Moonsung University, Changwon, Korea
3
Department of Computer Software Engineering, Soonchunhyang University, Asan, Korea
including smart factory, smart cars, and smart homes, and, in particular, smart factory is rapidly spreading for various purposes such as increasing productivity, maintenance of facilities, and prevention of safety accidents [2]. The main purpose of building a smart factory is to improve productivity and product quality through intelligent automation processes. In such cases, a factory that implements process automation based on facility and logistics automation, factory automation, factory energy management, product development, supply chain management (SCM), and enterprise resource planning (ERP) contains the overall elements of a smart factory [3]. Among these, the research and implementation cases in terms of productivity and quality control of products are increasing [4, 5]. For this envir
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