Fault detection of cycle-based signals using wavelet transform in FAB processes

Jun Seok Kim, Jae Hyun Lee, Ji Hyun Kim, Jun Geol Baek, Sung Shick Kim

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


This paper presents a wavelet multiresolution analysis based process fault detection algorithm to improve the accuracy of fault detection. Using Haar wavelet, coefficients that well reflect the process condition are selected and Hotelling's T2 control chart that uses the selected coefficients is constructed for assessing the process condition. To enhance the overall efficiency and accuracy of fault detection, the following two steps are suggested: First, a denoising method that is based on wavelet transform and soft-thresholding. Second, coefficient selection methods that use the difference in the variance. For performance evaluation, various types of abnormal process conditions are simulated and the proposed algorithm is compared with other methodologies. Also, We apply the proposed algorithm to the industrial data of the dry etching process, which is one of the FAB processes. Our method has a better fault-detection performance for various sections and various changes in mean than other methods.

Original languageEnglish
Pages (from-to)237-246
Number of pages10
JournalInternational Journal of Precision Engineering and Manufacturing
Issue number2
Publication statusPublished - 2010 Apr


  • Control chart
  • Cycle-based signal
  • Fault detection
  • Wavelet transform

ASJC Scopus subject areas

  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering


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