Browsing by Author "Shen, LC"

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An intelligent supervision system for the ion implementation in IC fabrication processes
(1998)
Shen, LC
;
Hsu, PL
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a real-time intelligent supervision system for IC ion implantation processes. A hardware interface is developed to directly extract the features from the 2-D analog image signals of a beam map. A qualitative model for the beam scanning is then obtained and the symptoms of abnormal operations can be analyzed to achieve on-line diagnosis. Furthermore, a fuzzy expert system is developed to advise operators taking appropriate adjustment for the beam scanning. This supervisory system has been implemented on Eaten NV-6200 A/AV ion implanters at the Taiwan Semiconductor Manufacturing Company. Copyright (C) 1998 IFAC.
An intelligent supervisory system for ion implantation in IC fabrication processes
(1999-02-01)
Shen, LC
;
Hsu, PL
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This pager presents a real-time intelligent supervision system for IC ion implantation processes. A hardware interface is developed, to extract the features directly from the 2-D analog image signals of a beam map. A qualitative model for the beam scanning is then obtained, and the symptoms of abnormal operations can be analyzed to achieve on-line diagnosis. Furthermore, a fuzzy expert system is developed to advise operators on making appropriate adjustments for the beam scanning. This supervisory system has been implemented on Eaten NV-6200 A/AV ion implanters at the Taiwan Semiconductor Manufacturing Company. (C) 1999 Elsevier Science Ltd. All rights reserved.
Robust fault detection and isolation with unstructured uncertainty using eigenstructure assignment
(1998-01-01)
Shen, LC
;
Chang, SK
;
Hsu, PL
;
電控工程研究所
;
Institute of Electrical and Control Engineering
A numerical implementation is presented for the eigenstructure assignment approach to the design of a robust fault detection and isolation observer, By formulating the problem of multiple fault isolation in an eigenstructure, we develop a parametric characterization of all allowable eigenspaces, which provides a diagnostic observer capable of multiple fault isolation. In addition, a well-conditioned design of the allowable eigenvectors is shown to reduce the effect of the sus;em unstructured uncertainty. The resulting diagnostic observer is robust to unstructured modeling errors without losing fault detection sensitivity. A procedure for the synthesis of a reduced order diagnostic observer is also presented to increase the computational efficiency of the proposed observer.