Sensor-based Modeling and Monitoring of Chemical Mechanical Polishing - Softcover

Rao, Prahalada

 
9783639035643: Sensor-based Modeling and Monitoring of Chemical Mechanical Polishing
Softcover
ISBN 10: 363903564X ISBN 13: 9783639035643
Verlag: VDM Verlag Dr. Müller, 2008

Inhaltsangabe

This book provides a framework for real time control of the Chemical Mechanical Planarization (CMP) process based on combining nonlinear dynamics principles with statistical process monitoring approaches. CMP has a direct bearing on the computational speed and dimensional characteristics of solid state devices. The challenge in CMP may be narrowed to domains enveloping productivity, measured in terms of material removal rate (MRR), and quality which is usually specified in terms of surface roughness - Ra, within wafer non-uniformity (WIWNU), defect rate, etc. In this work, experimental investigations of CMP are executed with the aid of sensors. The analysis of the data reveals the presence of pronounced stochastic-dynamic characteristics. As a result, we derive a process control method integrating statistical time series analysis and nonlinear dynamics which captures ~ 80% (linear R-sq) of the variation in MRR. In this manner a novel paradigm for effective process control in CMP has been presented.

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Reseña del editor

This book provides a framework for real time control of the Chemical Mechanical Planarization (CMP) process based on combining nonlinear dynamics principles with statistical process monitoring approaches. CMP has a direct bearing on the computational speed and dimensional characteristics of solid state devices. The challenge in CMP may be narrowed to domains enveloping productivity, measured in terms of material removal rate (MRR), and quality which is usually specified in terms of surface roughness - Ra, within wafer non-uniformity (WIWNU), defect rate, etc. In this work, experimental investigations of CMP are executed with the aid of sensors. The analysis of the data reveals the presence of pronounced stochastic-dynamic characteristics. As a result, we derive a process control method integrating statistical time series analysis and nonlinear dynamics which captures ~ 80% (linear R-sq) of the variation in MRR. In this manner a novel paradigm for effective process control in CMP has been presented.

Biografía del autor

Prahalada is a PhD student at the school of industrial engineering, Oklahoma State University. His research involves sensor based process monitoring and control integrating statistical signal processing techniques with contemporary nonlinear dynamics (chaos theory) paradigms. His PhD is jointly supervised by Drs. Komanduri and Bukkapatnam.

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Verlag
VDM Verlag Dr. Müller
Erscheinungsdatum
2008
Sprache
Englisch
ISBN 10 
363903564X
ISBN 13 
9783639035643
Einband
Tapa blanda
Anzahl der Seiten
208
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Verantwortliche Person
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