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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/28466

Title: Diagnosability of Semiconductor Manufacturing Equipment
Authors: Yuan Lin Wen;M.D. Jeng;Yi Sheng Huang
Contributors: NTOU:Department of Electrical Engineering
國立臺灣海洋大學:電機工程學系
Keywords: Fault Diagnosis;Linear Programming;Petri Net;Semiconductor Manufacturing
Date: 2006-01
Issue Date: 2011-10-21T02:37:39Z
Publisher: Materials Science Forum
Abstract: Abstract:Diagnosis of discrete event systems such as complex semiconductor manufacturing equipment has become more and more difficult such that it cannot be performed based on experience. Systematic approaches for the diagnosis problem are urgently needed. In this paper, we present an algorithm of polynomial complexity in the number of nodes for computing a sufficient condition of diagnosability of semiconductor manufacturing equipment modeled by Petri nets. Our algorithm is more efficient than previous ones since no state enumeration is necessary. This gives us an advantage to solve large real-world problems. Our algorithm is formulated as a linear programming problem, which is well-known to be of polynomial complexity in the worst case. We use a Metal-Organic Vapor Phase Epitaxy system that is simplified from real-world semiconductor manufacturing equipment applications to illustrate our proposed approach.
Relation: 505-507, pp.1135-1140
URI: http://ntour.ntou.edu.tw/handle/987654321/28466
Appears in Collections:[電機工程學系] 期刊論文

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