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 FEO3 Section 4: Quality Control FEO Volume 3, May 28, 2008
A look at ways to arm process and equipment engineers with a new set of solutions for monitoring equipment vibration and acceleration at the 200 mm fabs. Plus, part 2 of 2 on an approach to maintaining small biases between CD-SEM tools for the numerous feature types found in high-volume production operations.
Murty S. Polavarapu, BAE Systems
FEO4 Section 4: Quality Control FEO Volume 4, August 28, 2008
Quality measures such as sort yield and
device performance can be significantly impacted
if particle source troubleshooting is not quick and
effective.
Bill Funsten, Spansion, Inc.
Real-Time Vibration Monitoring Optimizes 200 mm Equipment Productivity FEO Volume 3, May 28, 2008
Increased equipment productivity is key
for 200 mm fabs to realize profitability goals.
This is true especially because some products
won’t be transitioned to 300 mm production;
therefore, equipment at these 200 mm fabs
will need to keep running at optimum levels
to reduce wafer scrap and achieve maximum
yields. It is becoming increasingly imperative
that process and equipment engineers be
armed with a new set of solutions for monitoring
equipment vibration and acceleration
that provides a better feedback loop for
controlling equipment conditions in order
to accelerate yield improvements, and to
reduce machine downtime.
Dennis Bonciolini, CyberOptics Semiconductor
INTRODUCTION: Quality Control FEO Volume 2, February 29, 2008
Process and yield engineers are always working
near the limits of their ability to measure and
control process variables. Continuous vigilance is
needed to ensure tight physical and electrical
tolerances. This is true for both high-volume
operations, where millions of dollars of product
are in jeopardy; and for development fabs, where
cycles of learning, on a relatively small number
of lots, are the key product.
Bill Funsten, Spansion, Inc.
FEO5: Quality Control FEO Volume 5, November 20, 2008
Yield improvement in the semiconductor industry is a never-ending quest. It is like climbing a mountain (with occasional falls and drops that people in the industry euphemistically call “excursions”) to reach the top, only to face the reality that there is yet another peak to scale for the next technology node.
Murty S. Polavarapu, BAE Systems
FEO4 Section 4: Quality Control FEO Volume 4, August 28, 2008
Process improvements such as those suggested in these two articles are generally of more value than mere improvements in process control, as they can change the expected performance level of the process.
Robert K. Henderson, Samsung Austin Semiconductor
Matching CD-SEM Tools for Feature Size Measurement Results in a High-Volume Production Operation – Part 2 of 2 FEO Volume 3, May 28, 2008
This paper describes an approach to
maintaining small biases between CD-SEM
tools for the numerous feature types found
in high-volume production operations. Part 1
focuses on key issues complicating control
of CD-SEM feature measurement, and identifies
a simple statistical model to apply to
production data to facilitate its use in managing
CD-SEM matching. Part 2 focuses on
the specific process control approach utilizing
the model results.
Robert K. Henderson, Samsung Austin Semiconductor, Jason Malik, Samsung Austin Semiconductor
Fast Learning Cycle (FLC) Methodology for Yield Improvement FEO Volume 5, November 20, 2008
A paper that outlines a comprehensive framework – fast learning cycle – that allows for yield improvement in a complex manufacturing environment.
National Semiconductor, Inc.
Advanced Diffuser Technology Helps Reduce Vent-Up Times FEO Volume 4, August 28, 2008
Describing the effectiveness of gas diffuser technologies, which can allow rapid venting of loadlock chambers, resulting in increased tool productivity, production and overall equipment effectiveness without additional particle-related yield loss.
Chris Vroman, Entegris, Inc.
Matching CD-SEM Tools for Feature Size Measurement Results in a High-Volume Production Operation – Part 1 of 2 FEO Volume 2, February 29, 2008
This paper describes an approach to
maintaining small biases between CD-SEM
tools for the numerous feature types found
in high-volume production operations. Part 1
focuses on key issues complicating control
of CD-SEM feature measurement, and identifies
a simple statistical model to apply to
production data to facilitate its use in managing
CD-SEM matching. Part 2 focuses on
the specific process control approach utilizing
the model results.
Robert K. Henderson, Samsung Austin Semiconductor, Jason Malik, Samsung Austin Semiconductor
Litho Track-Induced Charging: Effects, Detection, Reduction & Prevention FEO Volume 5, November 20, 2008
A look at why lowering the charging from the track by reducing rinse time or rinse spin speed can help alleviate early breakdown of high voltage gate oxide capacitors.
Spansion, Inc.
Tool Optimization for Improving Productivity and Yields FEO Volume 4, August 28, 2008
A paper that describes key analytical techniques for bulk and surface characterization of tool parts.
Victor K. F. Chia, Air Liquide Electronics, Balazs NanoAnalysis, Fuhe Li, Air Liquide Electronics, Balazs NanoAnalysis
Introduction: Contamination Control FEO Volume 1, November 20, 2007
The articles included in this FEO edition
give a good overview of AMC concerns and
the monitoring techniques with the sensitivity
required for peace of mind.
Bill Funsten, Spansion, Inc.
Advances in Real-Time Airborne Molecular Contamination Monitoring FEO Volume 1, November 20, 2007
The semiconductor industry is moving
toward data on demand to monitor the
levels of cleanroom contaminants.
Dan Cowles, Balazs Analytical Services, a Division of Air Liquide Electronics U.S. LP, Scott Anderson, Balazs Analytical Services, a Division of Air Liquide Electronics U.S. LP, Hugh Gotts, Balazs Analytical Services, a Division of Air Liquide Electronics U.S. LP
Recent Developments in Airborne Molecular Contamination Control FEO Volume 1, November 20, 2007
Airborne molecular contamination
(AMC) is a relevant yield concern for
many fabs not only with regard to the
most advanced technologies, where
certainly the problems multiply.
Andreas Neuber, M+W Zander FE GmbH
Introduction: Yield & Efficiency FEO Volume 1, November 20, 2007
The papers in this section address some of the
real-world issues involved in constraint
optimization and automated real-time
dispatching.
Gregory D. Winterton, Texas Instruments, Murty S. Polavarapu, BAE Systems
A Broadband Approach to Constraint Optimization FEO Volume 1, November 20, 2007
Team member/team leader selection represents a critical management decision with very significant bottom-line implications.
Kevin Funk, Avago Technologies
Challenges in Automated Real-Time Dispatching FEO Volume 1, November 20, 2007
This article analyzes the additional challenges faced in the implementation of real-time dispatching (RTD) in a fully automated fab environment.
Brandon Lee, Chartered Semiconductor Manufacturing Ltd., Ung Tin Tin, Chartered Semiconductor Manufacturing Ltd., Lim Kian Wee, Chartered Semiconductor Manufacturing Ltd.
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