Abstract
A fault detection and isolation system using model-based approach for the chamber pressure of plasma etching is developed. The dynamics of chamber pressure is modeled as a linear multiple-input-single-output closed-loop system and the model parameters are extracted by the system identification technique. The obtained parameters are then converted to physically meaningful features for detecting and isolating faults. The fuzzy inference and Dempster-Shafer evidence combining techniques are employed to detect and isolate fault from the features. The system has been evaluated by the measured data that are collected via SECS-II from the employed Lam490 plasma etcher for processing practical products. The test results are satisfactory for a large amount of practical data and extensive computer simulations.
Original language | English |
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Title of host publication | 2003 IEEEI/SEMI Advanced Semiconductor Manufacturing Conference and Workshop |
Subtitle of host publication | Advancing the Science of Semiconductor Manufacturing Excellence, ASMC 2003 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 208-214 |
Number of pages | 7 |
ISBN (Electronic) | 0780376730 |
DOIs | |
State | Published - 2003 |
Externally published | Yes |
Event | 14th Annual IEEE/SEMI Advanced Semiconductor Manufacturing Conference and Workshop, ASMC 2003 - Munich, Germany Duration: 31 03 2003 → 01 04 2003 |
Publication series
Name | ASMC (Advanced Semiconductor Manufacturing Conference) Proceedings |
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Volume | 2003-January |
ISSN (Print) | 1078-8743 |
Conference
Conference | 14th Annual IEEE/SEMI Advanced Semiconductor Manufacturing Conference and Workshop, ASMC 2003 |
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Country/Territory | Germany |
City | Munich |
Period | 31/03/03 → 01/04/03 |
Bibliographical note
Publisher Copyright:© 2003 IEEE.
Keywords
- Computer vision
- Data mining
- Etching
- Fault detection
- Plasma applications
- Plasma materials processing
- Plasma measurements
- Plasma simulation
- System identification
- Testing