The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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A statistical procedure of analyzing container ship operation data for finding fuel consumption patterns

연료 소비 패턴 발견을 위한 컨테이너선 운항데이터 분석의 통계적 절차

  • Kim, Kyung-Jun (Department of Industrial and Management Engineering, Pohang University of Science and Technology) ;
  • Lee, Su-Dong (Department of Industrial and Management Engineering, Pohang University of Science and Technology) ;
  • Jun, Chi-Hyuck (Department of Industrial and Management Engineering, Pohang University of Science and Technology) ;
  • Park, Kae-Myoung (Korean Register of Shipping) ;
  • Byeon, Sang-Su (Hyundai Ocean Service CO., LTD.)
  • 김경준 (포항공과대학교 산업경영공학과) ;
  • 이수동 (포항공과대학교 산업경영공학과) ;
  • 전치혁 (포항공과대학교 산업경영공학과) ;
  • 박개명 ((사)한국선급) ;
  • 변상수 (현대해양서비스(주))
  • Received : 2017.07.05
  • Accepted : 2017.10.08
  • Published : 2017.10.31
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Abstract

This study proposes a statistical procedure for analyzing container ship operation data that can help determine fuel consumption patterns. We first investigate the features that affect fuel consumption and develop the prediction model to find current fuel consumption. The ship data can be divided into two-type data. One set of operation data includes sea route, voyage information, longitudinal water speed, longitudinal ground speed, and wind, the other includes machinery data such as engine power, rpm, fuel consumption, temperature, and pressure. In this study, we separate the effects of external force on ships according to Beaufort Scale and apply a partial least squares regression to develop a prediction model.

본 연구는 컨테이너선의 연료 소비 패턴의 발견을 위해 운항데이터 분석의 통계적 절차를 제안한다. 우리는 현 시점의 연료 소비를 발견하기 위해 연료 소비에 영향을 미치는 변수들을 파악하는 동시에 예측 모델을 개발 및 적용하는 것을 목적으로 한다. 선박의 데이터는 크게 운항데이터와 기기데이터로 분류할 수 있으며, 운항데이터는 항로, 항해 정보, 대수속도, 대지속도, 바람과 같은 외력에 대한 정보 등이 있고, 기기데이터는 엔진출력, RPM, 연료 소모량, 기기들의 온도 및 압력 등이 있다. 본 연구에서, 우리는 선박에 미치는 외력의 영향을 Beaufort Scale (BFS)을 기준으로 구분한 후에 PLS 회귀분석을 통한 예측 모델을 개발하였다.

Keywords

References

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