Intelligent Monitoring and Control of Semiconductor Manufacturing Equipment

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Citation: Janet Leeann Murdock and Barbara Hayes-Roth. (1991) Intelligent Monitoring and Control of Semiconductor Manufacturing Equipment. In KSL-91-35, December,1991.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author Janet Leeann Murdock and Barbara Hayes-Roth
title Intelligent Monitoring and Control of Semiconductor Manufacturing Equipment
number KSL-91-35
institution Knowledge Systems, AI Laboratory
year 1991
month December
Bibtex more
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abstract This paper describes efforts to apply AI methods to enhance the quality and efficiency of semiconductor manufacturing in a state-of-the-art fabrication device called the "rapid thermal multiprocessor(RTM)". Semiconductor fabrication involves many complex processing steps with limited opportunities for measurement of process and product properties. By applying more knowledge to that limited data, AI monitoring and control methods augment classical control methods through detection of abnormalities and trends, prediction of failures, diagnosis, planning of corrective action sequences, explanation of diagnoses or predictions, and reaction to anomalous conditions that classical control systems typically would not correct. An architecture for AI control is described that adapts to complex changing environments such as that foundin fabrication facilities. We illustrate architectural capabilities and our research efforts directed at reasoning about physical components of the RTM with scenarios from RTM wafer fabrication as well as from our parallel effort in monitoring intensive care patients.

KSL Technical Report ID: KSL-91-35
Facts about Intelligent Monitoring and Control of Semiconductor Manufacturing EquipmentRDF feed
Abstract This paper describes efforts to apply AI m … This paper describes efforts to apply AI methods to enhance the quality and efficiency of semiconductor manufacturing in a state-of-the-art fabrication device called the "rapid thermal multiprocessor(RTM)". Semiconductor fabrication involves many complex processing steps with limited opportunities for measurement of process and product properties. By applying more knowledge to that limited data, AI monitoring and control methods augment classical control methods through detection of abnormalities and trends, prediction of failures, diagnosis, planning of corrective action sequences, explanation of diagnoses or predictions, and reaction to anomalous conditions that classical control systems typically would not correct. An architecture for AI control is described that adapts to complex changing environments such as that foundin fabrication facilities. We illustrate architectural capabilities and our research efforts directed at reasoning about physical components of the RTM with scenarios from RTM wafer fabrication as well as from our parallel effort in monitoring intensive care patients. ort in monitoring intensive care patients.
Author Janet Leeann Murdock and Barbara Hayes-Roth  +
Bibtype techreport  +
Has author Janet Leeann Murdock and Barbara Hayes-Roth  +
Has identifier KSL-91-35  +
Has publishing details December,1991  +
Has title Intelligent Monitoring and Control of Semiconductor Manufacturing Equipment  +
Has where published KSL-91-35  +
Has year 1991  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-91-35  +
Month December  +
Number KSL-91-35  +
Process note YES  +
Title Intelligent Monitoring and Control of Semiconductor Manufacturing Equipment  +
Year 1991  +
Retrieved from "http://tw.rpi.edu/wiki/Intelligent_Monitoring_and_Control_of_Semiconductor_Manufacturing_Equipment"
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