A Study on Estimating the Next Failure Time of a Compressor in LNG FPSO

LNG FPSO 압축기 고장시간 예측 방안에 관한 연구

  • Cho, Sang-Je (Dept. of Industrial Engineering, Hongik University) ;
  • Jun, Hong-Bae (Dept. of Industrial Engineering, Hongik University) ;
  • Shin, Jong-Ho (Dept. of Design and Human Engineering, UNIST) ;
  • Hwang, Ho-Jin (Korea Research Institute of Ships and Ocean Engineering)
  • 조상제 (홍익대학교 산업공학과) ;
  • 전홍배 (홍익대학교 산업공학과) ;
  • 신종호 (울산과기대 디자인 및 인간공학과) ;
  • 황호진 (선박해양플랜트연구소 해양플랜트산업기술센터)
  • Received : 2014.06.11
  • Accepted : 2014.11.11
  • Published : 2014.12.31


The O&M (Operation and Maintenance) phase of offshore plants with a long life cycle requires heavy charges and more efforts than the construction phase, and the occurrence of an accident of an offshore plant causes catastrophic damage. So previous studies have focused on the development of advanced maintenance system to avoid unexpected failures. Nowadays due to the emerging ICTs (Information Communication Technologies) and sensor technologies, it is possible to gather the status data of equipment and send health monitoring data to administrator of an offshore plant in a real time way, which leads to having much concern on the condition based maintenance policy. In this study, we have reviewed previous studies associated with CBM (Condition-Based Maintenance) of offshore plants, and introduced an algorithm predicting the next failure time of the compressor which is one of essential mechanical devices in LNG FPSO (Liquefied Natural Gas Floating Production Storage and Offloading vessel). To develop the algorithm, continuous time Markov model is applied based on gathered vibration data.


Supported by : 한국연구재단


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