Univiariate signal preprocessing methodology for fault detection in semiconductor manufacturing process

Kyuchang Chang, Jun Geol Baek

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Many studies using sensor signals have been conducted in the field of fault detection and classification (FDC) for semiconductor manufacturing processes. This is because sensor signals generated in the semiconductor production process provide important information for predicting quality and yield of the finished product. However, as the process becomes more sophisticated and refined, normal and abnormal data with similar shape appears. They only show delicate differences and it is difficult to classify them using general classification algorithms. The purpose of this research is to present a preprocessing methodology for improving classification performance. The methodology consists of four steps based on signal segmentation and clustering methods. The experimental results illustrate the better performance of the proposed procedure.

Original languageEnglish
Title of host publicationProceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019
EditorsMeikang Qiu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages230-232
Number of pages3
ISBN (Electronic)9781728116631
DOIs
Publication statusPublished - 2019 Aug
Event22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019 - New York, United States
Duration: 2019 Aug 12019 Aug 3

Publication series

NameProceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019

Conference

Conference22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019
CountryUnited States
CityNew York
Period19/8/119/8/3

Keywords

  • Time Series Classification(TSC) Feature Extraction Fault Detection and Classification(FDC) Clustering Hierarchical Clustering Segmentation

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Human-Computer Interaction
  • Artificial Intelligence

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  • Cite this

    Chang, K., & Baek, J. G. (2019). Univiariate signal preprocessing methodology for fault detection in semiconductor manufacturing process. In M. Qiu (Ed.), Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019 (pp. 230-232). [8919603] (Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSE/EUC.2019.00051