As semiconductor manufacturing yield advances, the industry is increasingly turning to big data analytics to manage yield and improve productivity. By understanding the relationship between process variation and device performance, manufacturers can identify areas for improvement and make informed decisions about process changes.

1. OVERVIEW OF BIG DATA
ANALYTICS IN
SEMICONDUCTOR YIELD
MANAGEMENT
BIG DATA ANALYTICS IN SEMICONDUCTOR YIELD MANAGEMENT

2. INTRODUCTION TO BIG DATA
•As semiconductor manufacturing yield advances, the
industry is increasingly turning to big data analytics to
manage yield and improve productivity. By understanding the
relationship between process variation and device
performance, manufacturers can identify areas for
improvement and make informed decisions about process
changes.

3. CONT’D
• Big data (semiconductor data) analytics can help semiconductor manufacturers in a
number of ways, including:
• 1. Analyzing production data to identify process variation and potential causes of
yield loss;
• 2. Providing real-time feedback on process changes to help optimize manufacturing;
• 3. Predicting device performance based on process conditions;
• 4. Providing early warning of potential yield issues; and
• 5. Helping to track the root cause of yield issues.

4. HOW BIG DATA IS APPLIED IN
SEMICONDUCTOR YIELD
MANAGEMENT
•Semiconductor yield management systems is the art and
science of achieving the highest possible yield from a
semiconductor manufacturing process. In order to achieve
this, manufacturers must track, analyze and optimize a huge
amount of data. This data includes everything from
equipment performance data to recipes and process
parameters.

5. CONT’D
•In the past, all of this data was stored in silos and was
difficult to access and analyze. However, with the advent
of big data yield analytics, all of this data can now be
collected in one place and analyzed to help identify
trends and optimize process conditions.

6. BIG DATA ANALYTICS
•Big data analytics is playing an increasingly important role in
semiconductor yield management. By helping manufacturers
collect, track and analyze all of their data in one place, it is
possible to identify issues early on and make necessary
changes to improve yields. In addition, big data analytics can
help uncover hidden relationships between different process
variables that can be exploited to further improve yields.