Skip to main content
SpringerLink
Log in

Intelligent Design of Diagnosable Systems: A Case Study of Semiconductor Manufacturing Machines

  • Conference paper
Knowledge-Based Intelligent Information and Engineering Systems (KES 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4693))

Abstract

This paper presents an intelligent approach using Petri nets for designing diagnosable discrete event systems such as complex semiconductor manufacturing machines. The concept is based on diagnosability analysis and enhancement. We use a real-world Metal-Organic Vapor Phase Epitaxy (MOVPE) system to illustrate that our proposed approach is practically useful.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Jiang, S., Huang, Z., Chandra, V., Kumar, R.: A Polynomial Algorithm for Testing Diagnosability of Discrete-Event Systems. IEEE Trans. on Automatic Control 46(8), 1318–1321 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  2. Lin, W.: Introduction to Metal-Organic Vapor Phase Epitaxy System and Technology. Instruments Today 24(2), 13–24 (2002)

    Google Scholar 

  3. Sampath, M., Lafortune, S., Sinnamohideen, K., Teneketzis, D.: Diagnosability of Discrete Event Systems. IEEE Trans. on Automatic Control 40(9), 1555–1557 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  4. Wen, Y.L., Jeng, M.D., Huang, Y.S.: Diagnosability of Semiconductor Manufacturing Equipment. Material Science Forum 505, 1135–1140 (2006)

    Article  Google Scholar 

  5. Wen, Y.L., Jeng, M.D., Jeng, L.D., Fan, P.S.: An Intelligent Technique Based on Petri Nets for Diagnosability Enhancement of Discrete Event Systems. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds.) KES 2006. LNCS (LNAI), vol. 4252, pp. 879–887. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  6. Ushio, T., Onishi, I., Okuda, K.: Fault Detection Based on Petri Net Models with Faulty Behaviors. In: Proc. of the 1998 IEEE Int. Con. on Systems, Man, and Cybernetics, pp. 113–118. IEEE Computer Society Press, Los Alamitos (1998)

    Google Scholar 

  7. Martinez, J., Silva, M.: A simple and fast algorithm to obtain all invariants of a generalized Petri nets. In: Proc. of Second European Workshop on Application and Theory of Petri Nets. Informatik-Fachberichte, vol. 52, pp. 301–310 (1982)

    Google Scholar 

  8. Chung, S.-L.: Diagnosing PN-based models with partial observable transitions. Int. J. Computer Integrated Manufacturing 18(2–3), 158–169 (2005)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept. of Electrical Engineering, National Taiwan Ocean University, Keelung 202, Taiwan

    YuanLin Wen & MuDer Jeng

  2. Dept. of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan

    Sheng-Luen Chung

  3. Dept. of Electronic Engineering, Chung-Yuan Christian University, Chung-Li 320, Taiwan

    LiDer Jeng

Authors
  1. YuanLin Wen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sheng-Luen Chung
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. LiDer Jeng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. MuDer Jeng
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Dipartimento di Scienze dell’Informazione, Università degli Studi di Milano, Via Comelico 39/41, 20135, Milano, Italy

    Bruno Apolloni

  2. Centre for SMART Systems, School of Engineering, University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. Knowledge-Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes, SA 5095, Adelaide, Australia

    Lakhmi Jain

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wen, Y., Chung, SL., Jeng, L., Jeng, M. (2007). Intelligent Design of Diagnosable Systems: A Case Study of Semiconductor Manufacturing Machines. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4693. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74827-4_110

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74827-4_110

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74826-7

  • Online ISBN: 978-3-540-74827-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation