한국생산제조학회지 (Journal of the Korean Society of Manufacturing Technology Engineers)

  • 제21권1호
  • /
  • Pages.33-39
  • /
  • 2012
  • /
  • 2508-5093(pISSN)
  • /
  • 2508-5107(eISSN)
한국생산제조학회 (The Korean Society of Manufacturing Technology Engineers)
권호 표지
DOI QR코드

DOI QR Code

신경회로망을 이용한 원격모니터링을 위한 가공공정의 공구마모와 표면조도에 관한 연구

A Study on the Tool Wear and Surface Roughness in Cutting Processes for a Neural-Network-Based Remote Monitoring system

  • 권정희 (창원대학교 대학원 기계설계공학과) ;
  • 장우일 (창원대학교 대학원 기계설계공학과) ;
  • 정성현 (창원대학교 대학원 기계설계공학과) ;
  • 김도언 (창원대학교 대학원 기계설계공학과) ;
  • 홍대선 (창원대학교 메카트로닉스공학부)
  • 투고 : 2010.12.27
  • 심사 : 2011.09.09
  • 발행 : 2012.02.15
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

The tool wear and failure in automatic production system directly influences the quality and productivity of a product, thus it is essential to monitor the tool state in real time. For such purpose, an ART2-based remote monitoring system has been developed to predict the appropriate tool change time in accordance with the tool wear, and this study aims to experimently find the relationship between the tool wear and the monitoring signals in cutting processes. Also, the roughness of workpiece according to the wool wear is examined. Here, the tool wear is indirectly monitored by signals from a vibration senor attached to a machining center. and the wear dimension is measured by a microscope at the start, midways and the end of a cutting process. A series of experiments are carried out with various feedrates and spindle speeds, and the results show that the sensor signal properly represents the degree of wear of a tool being used, and the roughnesses measured has direct relation with the tool wear dimension. Thus, it is concluded that the monitoring signals from the vibration sensor can be used as a useful measure for the tool wear monitoring.

키워드

참고문헌

  1. Ko, J. H., Kim, Y. T., and Lee, S. J., 2000, "Research about Tool Wear Monitoring in CNC Lathe Machining," Journal of the Korean Society of Precision Engineering, Vol. 17, No. 12, pp. 54-60.
  2. Jantunen, E., 2002, "A Summary of methods applied to tool condition monitoring in drilling", International Journal of Machine Tools & Manufacture, Vol. 42, No. 9, pp. 997-1010. https://doi.org/10.1016/S0890-6955(02)00040-8
  3. Lee, G., Kim, K. H., and Jeon, D. Y., 2002, "Tool Condition Monitoring Based on Wavelet Transform," Proceeding of the Korean Society of Mechanical Engineers Spring Conference, pp. 970-975.
  4. Sim, J. W., Kim, J. H., Yang., J. S., and Choi J. Y., 2005, "Monitoring Method for Fault Tolerance of Real-time System," Proc. of the KISS Conference, Vol. 32, No. 1, pp. 772-774.
  5. Kim, M. S., Yoo, S. S., So, J. H., and Kwak, H. S., 2001, "On-line Fault Diagnosis System using Neural Network," Journal of Korea Information and Communications Society, Vol. 26, No. 11, pp. 75-84.
  6. Lee, I. S., Shin, P. J., and Jeon, G. J., 1997, "Multiple Faults Diagnosis of a Linear System Using ART2 Neural Networks," Journal of Control, Automation and Systems Engineering, Vol. 3, No. 3, pp. 244-251.
  7. Jang, S. J., Choi, K. J., Choi, Y. H., and Hong, D. S., 2006, "A Study on the Remote Monitoring system based on the Web for Machine Tools using ART2," Proceedings of the Korean Society of Machine Tool Engineers Spring Conference, pp. 337-341.
  8. Noh, M. S., Kwon, J. H., Jang, U. I., Hong, D. S., and Jung, H. Y., 2009, "Real Time Monitoring System for Prediction of Tool Wear and Failure in Machining Processes Using ART2," ICCAS-SICE Japan Conference, pp. 3105-3110.
  9. Jang, U. I., Noh, M. S., Choi, K. J., and Hong, D. S., 2008, "Development of a Web-based Remote Monitoring System for Evaluating Degradation of Machine Tools using ART2," IEEE-ASME International Conference on Mechatronics and Embedded Systems and Applications, pp. 315-320.
  10. Kim, S. I., Oh, S. H., Mun, S. D., and Kim, T. Y., 1996, "A Study on Characteristics of Tool Wear and Surface Roughness in Face Milling of Automobile Parts," Journal of the Korean Society of Automative Engineers, Vol. 4, No. 5, pp. 223-230.
  11. Kim, C. W., Choi, K. J., Jung, S. H., and Hong, D. S., 2009, "Development of a Web-Based Remote Monitoring System for Evaluating of Machine Tools using ART2," Transactions of the Korean Society of Machine Tool Engineers, pp. 42-49.
  12. Carpenter, G., and Grossberg, S., 1989, "ART2 Selforganization of Stable Category Recognition Codes for Analog Input Patterns," Applied Optics, Vol. 26, pp. 4919-4930.
  13. Korea Standard Association, 2003, KS B ISO 8688-2, Tool Life Testing in Milling - Part 2 : End milling.