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

Authors:
Yuanlin Wen;Sheng-Luen Chung;Lider Jeng;Muder Jeng
Affiliations:
Dept. of Electrical Engineering, National Taiwan Ocean University, Keelung 202, Taiwan;Dept. of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 106, Taiwan;Dept. of Electronic Engineering, Chung-Yuan Christian University, Chung-Li 320, Taiwan;Dept. of Electrical Engineering, National Taiwan Ocean University, Keelung 202, Taiwan
Venue:
KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
Year:
2007

Citing 2
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A Simple and Fast Algorithm to Obtain All Invariants of a Generalized Petri Net

Selected Papers from the First and the Second European Workshop on Application and Theory of Petri Nets
An intelligent technique based on petri nets for diagnosability enhancement of discrete event systems

KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II

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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.