
다이캐스팅 공정 지능화를 위한 데이터 수집, 처리, 분석 및 활용 기술 개발
Abstract
This study aims to achieve process intelligence by implementing a technology that collects, processes, analyzes, and utilizes data of die-casting processes. To achieve this goal, the system infrastructure, including hardware and software, was established to collect, process, and store data of the main die-casting processes, i.e., casting, post-processing, and quality inspection. Next, data analysis algorithms were developed to address die-casting quality problems by using the data collected from the established infrastructure. Finally, a 3D model-based visualization technology was implemented to visualize the data analysis results and support the monitoring of important data. The proposed technology was verified by implementing it in an actual die-casting factory. Furthermore, a reference model was presented for implementing the intelligent die-casting processes.
Keywords:
Die-casting process, Edge computing, Data analytics, Defect prediction, Defect cause diagnosis, 3D VisualizationAcknowledgments
본 논문은 한국생산기술연구원의 중소・중견기업 생산기술 실용화 및 기술지원 사업의 세부사업인 “제조혁신지원사업(KITECH JH-20-0003)”의 지원으로 수행한 연구입니다.
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Principal Researcher in the Manufacturing Process Platform R&D Department, Korea Institute of Industrial TechnologyHer research interest is Cyber-Physical Systems (CPS), Digital Twin, and Data Analytics System.
E-mail: ljy0613@kitech.re.kr