Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
권호 표지

Fault Detection System Development for a Spin Coater Through Vibration Assessment

스핀코터의 진동 평가를 통한 이상 검출 시스템 개발

  • Moon, Jun-Hee (Department of Mechatronics, Dealim University College) ;
  • Lee, Bong-Gu (Department of Mechanical Engineering, Dealim University College)
  • Published : 2009.11.01
Download PDF
⟨ Previous Next ⟩

Abstract

Spin coaters are the essential instruments in micro-fabrication processes, which apply uniform thin films to flat substrates. In this research, a spin coater diagnosis system is developed to detect the abnormal operation of TFT-LCD process in real time. To facilitate the real-time data acquisition and analysis, the circular-buffered continuous data transfer and the short-time Fourier transform are applied to the fault diagnosis system. To determine whether the system condition is normal or not, a steady-state detection algorithm and a frequency spectrum comparison algorithm using confidence interval are newly devised. Since abnormal condition of a spin coater is rarely encountered, algorithm is tested on a CD-ROM drive and the developed program is verified by a function generator. Actual threshold values for the fault detection are tuned in a spin coater in process.

Keywords

References

  1. Chae, H. C., Ryu, I. C. and Han, C. S., "3-Dimensional Modeling and Sensitivity Analysis for Vibration Reduction of the Spin-Coater System," Journal of the Korean Society for Precision Engineering, Vol. 20, No. 2, pp. 209-217, 2003
  2. Ganta, G. and Tonoli, A., "A harmonic finite element for the analysis of flexural, torsional and axial rotordynamic behavior of discs," Journal of Sound and Vibration, Vol. 207, No. 5, pp. 693-720, 1997 https://doi.org/10.1006/jsvi.1997.1147
  3. Patton, R. J., Frank, P. M. and Clark, R. N., "Issues of Fault Diagnosis for Dynamic Systems," Springer-Verlag, 2000
  4. Yang, B. S., Hwang, W. W., Kim, D. J. and Tan, A., "Condition Classification of Small Reciprocating Compressor for Refrigerators using Artificial Neural Networks and Support Vector Machines," Mechanical Systems and Signal Processing, Vol. 19, No. 2, pp. 371-390, 2005 https://doi.org/10.1016/j.ymssp.2004.06.002
  5. Betta, G., Liguori, C., Paolillo, A. and Pietrosanto, A., "A DSP-Based FFT-Analyzer for the Fault Diagnosis of Rotating Machine Based on Vibration Analysis," IEEE Transactions on Instrumentation and Measurement, Vol. 51, No. 6, pp. 1316-1322, 2002 https://doi.org/10.1109/TIM.2002.807987
  6. Samanta, B. and Al-Balushi, K. R., "Artificial Neural Network Based Fault Diagnostics of Rolling Element Bearings Using Time-Domain Features," Mechanical Systems and Signal Processing, Vol. 17, No. 2, pp. 317-328, 2003 https://doi.org/10.1006/mssp.2001.1462
  7. Daubechies, I., "The Wavelet Transform, Time-Frequency Localization and Signal Analysis," IEEE Transactions on Information Theory, Vol. 36, No. 5,pp. 961-1005, 1990 https://doi.org/10.1109/18.57199
  8. User's Guide, "PCIS-DASK Data Acquisition Software Development Kit for NuDAQ PCI-bus Cards," Adlink Technology Inc., 2000
  9. Press, W. H., Teukolsky, S. A., Vettering, W. T. and Flannery, B. P., "Numerical Recipes, 3rd Edition," Cambridge University Press, 2007