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Case Study of Design and Implementation for Hadoop-Based Integrated Facility Monitoring System

하둡 기반의 통합설비 모니터링시스템 설계 및 구현 사례 연구

  • Received : 2013.11.15
  • Accepted : 2013.12.31
  • Published : 2014.02.15

Abstract

SCADA and DCS that have performed automatic control and monitoring activities increase the productivity of enterprise in industries. In such systems, although their performance had been improved, there are still many deficiencies in predictive maintenance which can foresee the risk of any kinds of accidents. Because the data acquisition systems of main facilities are being distributed throughout the whole plant and therefore, integration of data obtained from the systems is very difficult. Accordingly, techniques that acquire meaningful information from the gathered data through realtime analysis still need to be improved. This paper introduces a developed facility monitoring system which can predict equipment failure and diagnose facility status through big data analysis to improve equipment efficiency and prevent safety accidents.

Keywords

References

  1. Anja, G. et al. (2011), Query Optimization Using Column Statistics in Hive, IDEAS, Proceedings of the 15th Symposium on International Database Engineering and Applications.
  2. Armbrust, M. et al. (2010), A View of Cloud Computing, Communications of the ACM, 53(4), 50-58.
  3. Dean, J. et al. (2004), MapReduce : Simplified Data Processing on Large Clusters, Sixth Symposium on Operating System Design and Implementation, 137-150.
  4. GE Intelligent Platforms (2013), Proficy Monitoring and Analysis Suite, http://www.ge-ip.com/files/files/13513.pdf.
  5. Hahm, Y. K. et al. (2012), Big Data changes business management, Samsung Economic Research Institute, Seoul, Korea.
  6. Kang, M. M. et al. (2012), Analytics and Utilization of Big Data, Journal of The Korea Information Science Society, 30(6), 25-32.
  7. Kim, S. R. et al. (2012), The Future of Big Data, Journal of The Korea Information Science Society, 30(6), 18-24.
  8. POSCO (2013), Introduction Document for POSCO IMC Center.
  9. Shvachko, K. et al. (2010), The Hadoop Distributed File System, In Proceedings of the 26th IEEE Transactions on Computing Symposium on Mass Storage Systems and Technologies, 1-10.
  10. Son, M. S. et al. (2012), To be a leader in the Big Data era, LG Economic Research Institute, LGERI Report, 2-6.
  11. Shim, T. G. et al. (2011), Hadoop Complete Guide, Hanbit Media, Seoul, Korea.
  12. Vertica Systems (2009), Managing Big Data with Hadoop and Vertica.
  13. Yun, M. R. (2012), Taking advantage and problem of Big Data, The Federation of Korean Information industries Issue Report, 10-13.

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