스마트공장의 에너지 절감을 위한 빅데이터 분석 및 효율화 방안

Abstract

Research and interest in manufacturing innovation and energy saving in smart factories applying advanced ICT technologies such as IoT, big data and artificial intelligence are increasing. In particular, for small and medium-sized manufacturing companies, productivity improvement and abnormality detection through manufacturing innovation are essential to realizing smart factories. Most of the existing studies focus on building an integrated platform for productivity improvement and abnormality detection by attaching IoT sensors to equipment at the production site of the manufacturing industry. However, this thesis proposes the development of an integrated platform for energy saving and anomaly detection targeting the forging process among smart factories in the manufacturing industry. Most of the existing studies are related to smart factory construction for general manufacturing industries, but this thesis is proposed integrated system for data collection and productivity improvement for energy saving and anomaly detection detection by attaching IoT devices necessary in the actual field of a forging factory. We propose a system in terms of energy saving, anomaly detection, and productivity efficiency for the collected big data from smart factories based on IoT. First, our system is designed element technologies for configuring an integrated system for data collection in smart factories, and based on these contents, we propose a system that provides necessary information to managers and expresses various information. Second, based on the data collected by the proposed integrated system, we propose the improvement method of energy efficiency through basic unit analysis for energy saving. Third, we also propose a design method for detecting anomalies targeting data collected by each facility in the forging process. Similar to previous studies, our research has similar energy saving and anomaly detection methods for smart factories, but the advantage of our research is based on data transmitted in real time based on IoT for forging factories, and we propose an integrated system by designing our own model for energy reduction and anomaly detection for energy saving of each unit.