Journal of Korean Society for Quality Management (품질경영학회지)

Korean Society for Quality Management (한국품질경영학회)
권호 표지
DOI QR코드

DOI QR Code

Development of Load Profile Monitoring System Based on Cloud Computing in Automotive

클라우드 컴퓨팅 기반의 자동차 부하정보 모니터링 시스템 개발

  • Cho, Hwee (Department of Industrial Engineering, Ajou University) ;
  • Kim, Ki-Tae (Department of Industrial Engineering, Ajou University) ;
  • Jang, Yun-Hee (Department of Industrial Engineering, Ajou University) ;
  • Kim, Seung-Hwan (Department of Industrial Engineering, Ajou University) ;
  • Kim, Jun-Su (Department of Industrial Engineering, Myongji University) ;
  • Park, Keoun-Young (Department of Industrial Engineering, Myongji University) ;
  • Jang, Joong-Soon (Department of Industrial Engineering, Ajou University) ;
  • Kim, Jong-Man (Department of Industrial Engineering, Myongji University)
  • 조휘 (아주대학교 산업공학과) ;
  • 김기태 (아주대학교 산업공학과) ;
  • 장윤희 (아주대학교 산업공학과) ;
  • 김승환 (아주대학교 산업공학과) ;
  • 김준수 (명지대학교 산업공학과) ;
  • 박건영 (명지대학교 산업공학과) ;
  • 장중순 (아주대학교 산업공학과) ;
  • 김종만 (명지대학교 산업공학과)
  • Received : 2015.11.19
  • Accepted : 2015.12.14
  • Published : 2015.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Purpose: For improving result of estimated remaining useful life in Prognostics and Health Management (PHM), a system which is able to consider a lot of environment and load data is required. Method: A load profile monitoring system was presented based on cloud computing for gathering and processing raw data which is included environment and load data. Result: Users can access results of load profile information on the Internet. The developed system provides information which consists of distribution of load data, basic statistics, etc. Conclusion: We developed the load profile monitoring system for considering much environment and load data. This system has advantages such as improving accessibility through smart device, reducing cost, and covering various conditions.

Keywords

References

  1. Ahn, Yungbae. 2013. "Public institution evaluation system based on cloud." Master Dissertation, University of Korea.
  2. Antory, David. 2007. "Application of a Data-Driven Monitoring Technique to Diagnose Air Leaks in an Automotive Diesel Engine: A Case Study." Mechanical Systems and Signal Processing 21(2):795-808. https://doi.org/10.1016/j.ymssp.2005.11.005
  3. Camci, Fatih. et al. 2013. "Feature Evaluation for Effective Bearing Prognostics." Quality and Reliability Engineering International 29(4):477-486. https://doi.org/10.1002/qre.1396
  4. Cheng, Shunfeng, Azarian, Michael. H., and Pecht, Michael. G. 2010. "Sensor Systems for Prognostics and Health Management." Sensors 10(6):5774-5797. https://doi.org/10.3390/s100605774
  5. Choi, Kwangdoo et al. 2013. "An Empirical Study on the Influence Factors of the Mobile Cloud Storage Service Satisfaction."Journal of the Korean Society for Quality Management 41(3):381-394. https://doi.org/10.7469/JKSQM.2013.41.3.381
  6. Han, Chang-un. 2013. "Automobile evolution and the need for evolution of diagnostic techniques of electrical components." Journal of the KSME 53(7):40-43.
  7. IBM Corporation. Software Group. 2013. "IBM big data for the automotive industry."Accessed Nov. 30. http://www.oesa.org/Doc-Vault/Knowledge-Center/Operational-Performance-Content/IBM-Big-Data-for-Auto-Industry.pdf.
  8. IEEE. 2014. "IEEE PHM 2014 Data Challenge." Accessed Dec 4. http://eng.fclab.fr/ieee-phm-2014-data-challenge/.
  9. Jang, Jung-sun, and Kim, Ki-tae. 2013. "Case studies of PHM technology in the field of hybrid/electric vehicles." Journal of the KSME 53(7):35-39.
  10. Jiang, Dongxiang, and Liu, Chao. 2011. "Machine Condition Classification Using Deterioration Feature Extraction and Anomaly Determination." IEEE Transactions on Reliability 60(1):41-48. https://doi.org/10.1109/TR.2011.2104433
  11. Kohonen, Teuvo et al. 1995. "The Self-Organizing Map." Berlin: Springer.
  12. Kwan, C. et al. 2003. "A Novel Approach to Fault Diagnostics and Prognostics." In ICRA:604-609.
  13. Lee, Jay et al. 2013. "Methodology and Framework of a Cloud-Based Prognostics and Health Management System for Manufacturing Industry." Chemical engineering transactions 33:205-210.
  14. Lee, Jong-Beom, and Cho, Jai-Rip. 2000. "The Study on the High Acceleration Life Method for the Automotive Electric and Electronic Parts."Journal of the Korean Society for Quality Management 28(4):16-28.
  15. Lee, Jongmin, Yoo, Changkyoo, and Lee, Inbeum. 2003. "On-Line Batch Process Monitoring Using a Consecutively Updated Multiway Principal Component Analysis Model." Computers and chemical engineering 27(12):1903-1912. https://doi.org/10.1016/S0098-1354(03)00151-0
  16. Li, Ruoyu, Sopon, Ponrit, and He, David. 2012. "Fault Features Extraction for Bearing Prognostics." Journal of Intelligent Manufacturing 23(2):313-321. https://doi.org/10.1007/s10845-009-0353-z
  17. Makoto, Shirota. 2009. The Impact of Cloud Computing. Tokyo: Jpub.
  18. Mathew, Sony et al. 2006. "Prognostics Assessment of Aluminum Support Structure on a Printed Circuit Board." Journal of Electronic Packaging 128(4):339-345. https://doi.org/10.1115/1.2351897
  19. Medjaher, Kamal, Camci, Fatih, and Zerhouni, Noureddine. 2012. "Feature Extraction and Evaluation for Health Assessment and Failure Prognostics." In Proceedings of First European Conference of the Prognostics and Health Management Society:111-116.
  20. Peng, Ying, Dong, Ming, and Zuo, Ming, J. 2010. "Current Status of Machine Prognostics in Condition-Based Maintenance: A Review." The International Journal of Advanced Manufacturing Technology 50(1-4):297-313. https://doi.org/10.1007/s00170-009-2482-0
  21. Ramakrishnan, Arun, and Pecht, Michael, G. 2003. "A Life Consumption Monitoring Methodology for Electronic Systems." IEEE Transactions on Components and Packaging Technologies 26(3):625-634. https://doi.org/10.1109/TCAPT.2003.817654
  22. Scott, David, W. 1979. "On Optimal and Data-Based Histograms." Biometrika 66(3):605-610. https://doi.org/10.1093/biomet/66.3.605
  23. Shetty, Vidyasagar et al. 2002. "Remaining Life Assessment of Shuttle Remote Manipulator System End Effector Electronics Unit." IEEE 8:2987-2991.
  24. Song, Jongwoo. 2008. "A Comparison of Classification Methods for Credit Card Approval Using R."Journal of the Korean Society for Quality Management 36(1):72-79
  25. Vichare, Nikhil et al. 2007. "Environment and Usage Monitoring of Electronic Products for Health Assessment and Product Design." Quality Technology and Quantitative Management 4(2):235-250. https://doi.org/10.1080/16843703.2007.11673148
  26. Vichare, Nikhil, M., and Pecht, Michael, G. 2006. "Prognostics and Health Management of Electronics." IEEE Transactions on Components and Packaging Technologies 29(1):222-229. https://doi.org/10.1109/TCAPT.2006.870387
  27. Vichare, Nikhil, M. 2006. "Prognostics and Health Management of Electronics By Utilizing Environmental And Usage Loads." Ph.D Dissertation, University of Maryland.
  28. Wand, M. P. 1997. "Data-Based Choice of Histogram Bin Width." The American Statistician 51(1):59-64.
  29. Zhang, Xiaodong et al. 2005. "An Integrated Approach to Bearing Fault Diagnostics and Prognostics." In American Control Conference: 2750-2755.