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DC Field Value Language
dc.citation.conferencePlace KO -
dc.citation.title 2014년 춘계 한국 CAD/CAM 학회 학술대회 -
dc.contributor.author 이승철 -
dc.date.accessioned 2023-12-20T00:09:59Z -
dc.date.available 2023-12-20T00:09:59Z -
dc.date.created 2017-01-06 -
dc.date.issued 2014-02-13 -
dc.description.abstract This paper addresses a new intelligent information technology designed for automated manufacturing diagnostics and maintenance decision support. This new solution, Factory EKG Technology (F-EKG), can help manufacturing enterprises to trace and record minimal motions in their automated machinery processes, detect process variation in real time, and provide early warnings to conduct preventive maintenance before failures actually occur. The technology fills the gap in the current diagnostics and fault detection tools heavily based upon sensing technology, rather that it digitizes existing PLC information to the rhythm of machine processes, which is enables faster detection of process behavior changes. We demonstrate the effectiveness of F-EKG with the real industrial applications. -
dc.identifier.bibliographicCitation 2014년 춘계 한국 CAD/CAM 학회 학술대회 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/40118 -
dc.language 영어 -
dc.publisher 한국 CAD/CAM 학회 -
dc.title.alternative Diagnostics of Automated Manufacturing Processes Using Event Time Durations -
dc.title 이벤트 시간 정보를 이용한 장비 이상 진단 -
dc.type Conference Paper -
dc.date.conferenceDate 2014-02-12 -

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