Optimizing Semiconductor Yield with Robust WAT and PCM Processes

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Optimizing Semiconductor Yield with Robust WAT
and PCM Processes https//yieldwerx.com/
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Wafer Acceptance Testing (WAT) and Process
Control Monitoring (PCM) are instrumental
elements within the semiconductor manufacturing
industry. They are crucial tools utilized
predominantly by fabless companies that seek to
monitor and enhance their yield and defect rates.
WAT/PCM is the systematic measurement of various
device parameters during different stages of
wafer processing. It establishes control over the
manufacturing process, leading to better
consistency and quality of the final product.
This measurement process aims to build a
comprehensive database of process information,
useful for a variety of process enhancement and
control activities. Understanding the Composition
of WAT Data On average, the wafer acceptance test
(WAT) data consists of 40 to 100 tests per wafer.
These tests help monitor the consistency of key
parameters across the wafer lot, such as sheet
resistance, oxide thickness, junction depth, gate
length, and others. The data are critical to
Fab's (foundry's) statistical process control
system (spc), facilitating continuous improvement
and helping to reduce variances in the
manufacturing process. The Role of Data Delivery
and Yield Management Systems After the completion
of the semiconductor manufacturing process, the
data is delivered to the fabless customer by the
Fab. Typically, the data is delivered per lot,
with one lot containing around 25 wafers. ASCII
CSV or Excel is the preferred format for data
delivery due to its wide acceptability by data
analysis and management software. This data is
integral to modern yield management systems (YMS)
or yield analysis systems. Whether they are
cloud-based or on-premise, these systems securely
process and store this data, ensuring its
integrity and accessibility for subsequent
analysis. The data is divided by wafer ID, and
then further segmented into each site, i.e., the
location of testing on the wafer, which allows
for a comprehensive and detailed
analysis. Advantages of Data Analysis and
Visualization Although the size of WAT data is
relatively small, it offers enormous benefits in
terms of data analysis and visualization. Despite
its compact size, it can provide comprehensive
insights into the manufacturing process,
potentially identifying variations or shifts in
process parameters. Visualization tools are
extensively used to interpret WAT data. These
tools help in identifying abnormalities or
deviations in the data, which can serve as early
warnings for potential yield loss or reliability
issues. Detecting such issues at the earliest
stages can help companies prevent substantial
losses and continually improve their
manufacturing processes.
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The Importance of Correlating WAT
Data Correlating WAT data against wafer sort and
final test data can provide meaningful insights
into the causes of yield loss, reliability, and
quality issues. This analysis can identify
problematic trends, forming a foundation for
effective communication with Fab to understand
and rectify the root cause analysis in
semiconductor. In essence, this correlation is a
vital tool for decision-making and continuous
improvement in the semiconductor manufacturing
process. Automation of the correlation process,
achieved through the deployment of suitable
algorithms and tools, enables rapid
identification of problem areas. Once these areas
have been identified, relevant teams can address
the root cause, preventing recurrence and
enhancing overall yield and reliability. The
Imperative for Clean and Consolidated Data A
well-implemented system that effectively
processes and analyzes WAT data requires clean
and consolidated data, especially at the final
test stage. Given the vast number of parameters
and the complexity of semiconductor devices, the
risk of data contamination or inconsistency is
high. Implementing data cleansing methodologies
is crucial to ensure the integrity and
reliability of the WAT data. Effectively
processing and analyzing WAT data can result in
substantial cost savings in the semiconductor
manufacturing industry by improving manufacturing
processes, reducing yield loss, and alleviating
reliability issues. Hence, investing in WAT/PCM
monitoring and subsequent data management and
analysis is a worthy endeavor for any
semiconductor manufacturing organization.
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• Conclusion
• The growth of the semiconductor industry is
  directly proportional to the ability to
  efficiently manufacture high-quality and
  high-performance semiconductor devices. This
  efficiency and quality heavily rely on robust
  monitoring and control of the manufacturing
  process, and here, WAT and PCM play a pivotal
  role.
• WAT and PCM have been an integral part of the
  semiconductor manufacturing process for several
  decades. Still, with increasing chip complexity
  and decreasing geometries, their role is becoming
  even more critical. Moving forward, the
  semiconductor industry should continue to invest
  in advanced WAT/PCM systems, automated data
  analysis, and correlation tools, and stringent
  data management protocols to keep up with the
  ever-increasing demands of the market.
• References
• Dehan, M. (2010). Wafer acceptance test What,
  why, and how? In 2010 IEEE International Test
  Conference.
• Mathew, J., Rao, M. (2003). Statistical
  analysis of wafer acceptance test (WAT) data. In
  2003 IEEE International Conference on
  Semiconductor Electronics (ICSE).
• Semiconductor Manufacturing Technology, 2nd
  Edition by Michael Quirk and Julian Serda,
  ISBN-13 978-0130815200
• Yield Management Strategies for Semiconductor
  Manufacturing Industries A Structural Approach.
  Sunil Kumar Nair, World Scientific, 2018, ISBN
  9789813235865