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Dive into the research topics where Richard J. Markle is active.

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Featured researches published by Richard J. Markle.


Metrology, inspection, and process control for microlothoggraphy. Conference | 2001

Scatterometry for shallow trench isolation (STI) process metrology

Christopher J. Raymond; Michael E. Littau; Richard J. Markle; Matthew A. Purdy

Scatterometry is a non-destructive optical metrology based on the analysis of light scattered form a periodic sample. In this research angular scatterometry measurements were performed on three wafers processed using shallow trench isolation (STI) technology. The periodic features that were measured on these wafers were composite etched gratings comprised of SiN on oxide on Si. The wafers were processed at three different etch times in order to generate different etch depths (shallow, nominal and deep). It was at this point in the process that the scatterometry measurements were performed. The scatterometry model was comprised of four parameters: Si thickness, SiN thickness, linewidth and sidewall angle. For comparison purposes measurements were also performed using a critical dimension scanning electron microscope (CD-SEM), a cross-section SEM and an atomic force microscope (AFM). The results show good agreement between the scatterometry measurements and the other technologies.


Journal of Vacuum Science and Technology | 2001

Data requirements and communication issues for advanced process control

Richard J. Markle; Elfido Coss

Data streams and communication issues are the most critical areas for successful advanced process control (APC) programs. These areas are vital for both APC run-to-run controllers and fault detection and classification (FDC) systems used for high volume manufacturing applications in the semiconductor industry. All APC systems rely on data streams to make their process changes, to keep the process on target and in control, and to otherwise signal a need for engineering involvement to make similar corrective actions. The access to, communication of, and reliability and integrity of these data streams are essential to all APC programs. APC run-to-run controllers use the data to make changes in the process. FDC systems focus on predicting pending equipment- or process- related problems or detecting them quickly when they occur. The inability to access the needed data stream can prohibit the use of APC run-to-run controllers or FDC systems on critical process operations. Worse yet, the use of unreliable or cor...


Process, equipment, and materials control in integrated circuit manufacturing. Conference | 1997

Modeling of OES data to estimate etch rate for etching equipment

Yi Cheng; Richard J. Markle; Joe Qin; Thomas F. Edgar; Michael J. Gatto; Chris Nauert

Optical emission spectroscopy (OES) data for 495 wavelengths and wafer measurements (pre- and post-oxide film thickness) from a commercial etch tool were collected for 18 oxide wafers to explore the feasibility of using OES as an in-situ sensor to estimate average oxide etch rate. A variable selection method is proposed based on the principle of partial least square (PLS) regression, which select several most informative wavelengths to build ordinary least square (OLS) regression models. Compared with the PLS models, it is found that OLS regression models based on selected wavelengths are more robust.


Advanced Process Control and Automation | 2003

Cost and revenue impact of advanced process control (APC) with an emphasis on run-to-run control (R2R)

Timothy D. Stanley; Richard J. Markle; Brad Van Eck; Brian K. Cusson; Matthew A. Purdy; K. J. Stanley

This paper takes published improvements in fabricator metrics that result from Advanced Process Control,and, applying an International SEMATECH cost model to the results, quantifies the expected economic impact. By converting the improvements in factory metrics to dollars, they can be compared. The benefits are given by equipment type, and by factory benefit mechanism. The majority of these calculations are based on Run-to-Run control.


Design, process integration, and characterization for microelectronics. Conference | 2002

Wafer-level Fault Detection and Classification on a photo track in a high volume fab

Timothy L. Jackson; Richard J. Markle; Clinton W. Miller; Edward C. Stewart; Robert A. Crowell

We will discuss Advanced Micro Devicess (AMD) Fault Detection and Classification (FDC) program strategy and our six-step project template that we have identified that must be addressed for any successful FDC effort. We will discuss the recent development and implementation of a wafer-level FDC system on a TEL CLEAN TRAC ACT 8 photo track system in AMDs Fab25, a high volume microprocessor factory. We will present our approach to designing and implementing this FDC system and demonstrate its ability to automatically identify specific wafers within a lot that require manual review. Upon manual review, the decision can be made to rework the specific wafers or the lot.


Archive | 2001

Method and apparatus for monitoring tool health

Elfido Coss; Richard J. Markle; Patrick M. Cowan


Archive | 1998

Methodology for improved semiconductor process monitoring using optical emission spectroscopy

Richard J. Markle; Michael J. Gatto; Chris Nauert; Yi Cheng; Richard Bruce Patty


Archive | 1997

Measurement system for detecting chemical species within a semiconductor processing device chamber

Michel A. Martin; Richard J. Markle; James K. Fidler


Surface and Interface Analysis | 1998

A plasma process monitor/control system

Joel O. Stevenson; Pamela P. Ward; Michael L. Smith; Richard J. Markle


Archive | 2001

Method and apparatus for fault detection using multiple tool error signals

Timothy L. Jackson; Richard J. Markle; Edward C. Stewart

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Elfido Coss

Advanced Micro Devices

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Tom Tse

Advanced Micro Devices

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