An agent-based system for abnormal flow detection in semiconductor production line

Dong Chang Lee, Sung Bae Cho

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

Abstract

In this paper, we propose an agent-based system to detect abnormal process flow in semiconductor manufacturing process. A large-scale automation system like a semiconductor line is composed of multi-agents. Each agent carries out only a given role with autonomy. Therefore, even if an abnormality occurs, it might cause huge accident easily. For quality control, it is necessary to detect such anomalies promptly and take necessary measures, but the system complexity is so high that process managers are unable to detect abnormalities. In order to allow the administrator to quickly recognize the problem situation, we propose an agent that monitors process flow, and detects abnormal flow, and verify its validity using the data.

Original languageEnglish
Title of host publicationICCAS 2017 - 2017 17th International Conference on Control, Automation and Systems - Proceedings
PublisherIEEE Computer Society
Pages2015-2020
Number of pages6
ISBN (Electronic)9788993215137
DOIs
Publication statusPublished - 2017 Dec 13
Event17th International Conference on Control, Automation and Systems, ICCAS 2017 - Jeju, Korea, Republic of
Duration: 2017 Oct 182017 Oct 21

Publication series

NameInternational Conference on Control, Automation and Systems
Volume2017-October
ISSN (Print)1598-7833

Other

Other17th International Conference on Control, Automation and Systems, ICCAS 2017
CountryKorea, Republic of
CityJeju
Period17/10/1817/10/21

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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  • Cite this

    Lee, D. C., & Cho, S. B. (2017). An agent-based system for abnormal flow detection in semiconductor production line. In ICCAS 2017 - 2017 17th International Conference on Control, Automation and Systems - Proceedings (pp. 2015-2020). (International Conference on Control, Automation and Systems; Vol. 2017-October). IEEE Computer Society. https://doi.org/10.23919/ICCAS.2017.8204285