대한조선학회논문집 (Journal of the Society of Naval Architects of Korea)

  • 제55권3호
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  • Pages.243-251
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  • 2018
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  • 1225-1143(pISSN)
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  • 2287-7355(eISSN)
대한조선학회 (The Society of Naval Architects of Korea)
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빅데이터 분석을 이용한 해양 구조물 배관 자재의 소요량 예측

Estimation of Material Requirement of Piping Materials in an Offshore Structure using Big Data Analysis

  • 오민재 (서울대학교 해양시스템공학연구소) ;
  • 노명일 (서울대학교 해양시스템공학연구소) ;
  • 박성우 (서울대학교 협동과정 해양플랜트엔지니어링전공) ;
  • 김성훈 (서울대학교 조선해양공학과)
  • Oh, Min-Jae (Research Institute of Marine Systems Engineering, Seoul National University) ;
  • Roh, Myung-Il (Research Institute of Marine Systems Engineering, Seoul National University) ;
  • Park, Sung-Woo (Interdisciplinary Program in Offshore Plant Engineering, Seoul National University) ;
  • Kim, Seong-Hoon (Department of Naval Architecture and Ocean Engineering, Seoul National University)
  • 투고 : 2017.12.12
  • 심사 : 2018.04.09
  • 발행 : 2018.06.20
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초록

In the shipyard, a lot of data is generated, stored, and managed during design, construction, and operation phases to build ships and offshore structures. However, it is difficult to handle such big data efficiently using existing data-handling technologies. As the big data technology is developed, the ship and offshore industries start to focus on the existing big data to find valuable information from it. In this paper, the material requirement estimation method of offshore structure piping materials using big data analysis is proposed. A big data platform for the data analysis in the shipyard is introduced and it is applied to the analysis of material requirement estimation to solve the problems in piping design by a designer. The regression model is developed from the big data of piping materials and verified using the existing data. This analysis can help a piping designer to estimate the exact amount of material requirement and schedule the purchase time.

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참고문헌

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