Journal of the Korea Convergence Society (한국융합학회논문지)

Korea Convergence Society (한국융합학회)
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Degradation-Based Remaining Useful Life Analysis for Predictive Maintenance in a Steel Galvanizing Kettle

철강 도금로의 예지보전을 위한 열화 기반 잔존수명 분석

  • Shin, Joon Ho (Department of Convergence Technology & Management Engineering, Yonsei University Graduate School) ;
  • Kim, Chang Ouk (Department of Industrial Engineering, Yonsei University)
  • 신준호 (연세대학교 일반대학원 융합기술경영공학과) ;
  • 김창욱 (연세대학교 산업공학과)
  • Received : 2019.09.18
  • Accepted : 2019.12.20
  • Published : 2019.12.28
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Abstract

Smart factory, a critical part of digital transformation, enables data-driven decision making using monitoring, analysis and prediction. Predictive maintenance is a key element of smart factory and the need is increasing. The purpose of this study is to analyze the degradation characteristics of a galvanizing kettle for the steel plating process and to predict the remaining useful life(RUL) for predictive maintenance. Correlation analysis, multiple regression, principal component regression were used for analyzing factors of the process. To identify the trend of degradation, a proposed rolling window was used. It was observed the degradation trend was dependent on environmental temperature as well as production factors. It is expected that the proposed method in this study will be an example to identify the trend of degradation of the facility and enable more consistent predictive maintenance.

제조산업 분야의 디지털트랜스포메이션의 일환인 스마트공장은 데이터 기반으로 모니터링 및 분석 그리고 예측을 통해서 의사결정 방식을 획기적으로 변화시키고 있다. 특히 설비에 대한 예지보전은 스마트공장의 핵심적인 요소로서 필요성이 증대되고 있다. 본 연구의 목적은 철강 도금공정의 예지보전을 위해 도금로 설비의 열화 특성을 고려한 잔존수명 분석과 예측모델을 산출하는 것이다. 상관성 분석, 다중회귀 분석, 주성분회귀 분석 그리고 시간의 경과에 따른 열화의 추이 파악을 위하여 이동회귀 방식을 제안하여 진행하였다. 그 결과 도금로 열화는 생산성 인자들과 주된 의존적 관계가 있으며, 특히 환경 온도 인자들의 영향성이 열화의 추이 변화에 관계가 있음을 추론할 수 있었다. 예측된 잔존수명을 활용하여 도금로 교체가 필요한 시점을 사전에 알려주는 예지보전을 구현하였다. 향후 설비의 열화 추이 파악에 본 연구에서 수행한 방안이 적절한 사례가 되어 보다 정합성 있는 예지보전 구현이 가능해지기를 기대한다.

Keywords

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