DOI QR코드

DOI QR Code

A Study on Big Data Platform Based on Hadoop for the Applications in Ship and Offshore Industry

조선 해양 산업에서의 응용을 위한 하둡 기반의 빅데이터 플랫폼 연구

  • Kim, Seong-Hoon (Dept. of Naval Architecture & Ocean Engineering, Seoul Nat'l Univ.) ;
  • Roh, Myung-Il (Dept. of Naval Architecture & Ocean Engineering and Research Institute of Marine Systems Engineering, Seoul Nat'l Univ.) ;
  • Kim, Ki-Su (Dept. of Naval Architecture & Ocean Engineering, Seoul Nat'l Univ.)
  • 김성훈 (서울대학교 조선해양공학과 대학원) ;
  • 노명일 (서울대학교 조선해양공학과 및 해양시스템공학연구소) ;
  • 김기수 (서울대학교 조선해양공학과 대학원)
  • Received : 2016.04.30
  • Accepted : 2016.05.31
  • Published : 2016.09.01

Abstract

As Information Technology (IT) is developed constantly, big data is becoming important in various industries, including ship and offshore industry where a lot of data are being generated. However, it is difficult to apply big data to ship and offshore industry because there is no generalized platform for its application. Therefore, this study presents a big data platform based on the Hadoop for applications in ship and offshore industry. The Hadoop is one of the most popular big data technologies. The presented platform includes existing data of shipyard and is possible to manage and process the data. To check the applicability of the platform, it is applied to estimate the weight of offshore plant topsides. The result shows that the platform can be one of alternatives to use effectively big data in ship and offshore industry.

Keywords

References

  1. Bae, D.M., Park, H.S. and Oh, K.H., 2013, Big Data Trend and Policy Implication, Information and Communication Policy, 25(10), pp.37-74.
  2. Lee, H.H., 2013, Application of Big Data for Strengthen of Manufacturing Business, Seoul, Korea Korea Institute for Industrial Economics and Trade.
  3. Kim, S.R. and Kang, M.M., 2014, The Trends and Prospects in Cloud-Based Bigdata Technology, Journal of Korean Institute of Information Scientists and Engineers, 32(2), pp.22-31.
  4. Kim, S.R. and Kang, M.M., 2014, Today and Tomorrow of Big Data Analysis Technology, Journal of Institute of Information Scientists and Engineers, 32(1), pp.8-17.
  5. Kim, Y.J., Park, J.K., Lee, J.H., Yang, H.Y. and Jung, M.A., 2013, A Study on the Bigdata Technology and Analysis Technique for Vessel Design Automation, Journal of Korea Institute of Communication Sciences, 2013(6), pp.213-215.
  6. Lee, D.H., 2014, Analysis of Production Process in Shipbuilding Industry using Process Mining, Ph.D. thesis, Pusan National University, Korea.
  7. Kim, W.K., 2014, The Trends and Prospects in Cloud-Based Bigdata Technology, Journal of Mechanical Science and Technology, 54(12), pp.49-52.
  8. Kim, K.I., Jung, J.S. and Park, K.K., 2013, Assessment of External Force Acting on Ship using Big Data in Maritime Traffic, Journal of Korea Intelligent Information System Society, 23(5), pp.379-384. https://doi.org/10.5391/JKIIS.2013.23.5.379
  9. Apache, Definition of Hadoop, http://hadoop.apache.org
  10. Kim, W.K., Park, M.K. and Han, M.K., 2012, Design of a Framework for Support System of Ship Design Engineering, Journal of Korea Institute of Information and Communication Engineering, 16(10), pp.2316-2322. https://doi.org/10.6109/jkiice.2012.16.10.2316
  11. Um, T.S., Roh, M.I., Shin, H.K. and Ha, S., 2014, Simplified Model for the Weight Estimation of Floating Offshore Structure Using the Genetic Programming Method, Transactions of the Society of CAD/CAM Engineers, 19(1), pp.1-11. https://doi.org/10.7315/CADCAM.2014.001
  12. Ha, S., Um, T.S., Roh, M.I. and Shin, H.K., 2015, A Structural Weight Estimation Model of FPSO Topsides using an Improved Genetic Programming Method, appears in Ships and Offshore Structure, doi: 10.1080/17445302.2015.1099246.
  13. Kerneur, J., 2010, Worldwide Survey of FPSO Units, Houston, Offshore Magazine.
  14. Clarkson, 2012, The Mobile Offshore Production Units Register 2012, 10th ed., London, Clarkson.