After
attending the semiconductor manufacturing conference SEMICON Europa in Munich
last week, our main takeaway is clear: smart manufacturing has permeated every
aspect of the semiconductor industry as its principles are applied not only to each
process in the manufacturing cycle, but to each and every detail along the way,
ultimately increasing efficiencies and productivity while also making
semiconductor manufacturing more adaptable and sustainable.
Big data
analytics are used in smart manufacturing to streamline the manufacturing
processes, optimize the supply chain, analyze tools
and eliminate workplace inefficiencies.
Engineering
yield management systems make semiconductor manufacturing and test data easily
accessible. Manufacturers that use yield management tools spend less time
gathering data and have more time for analysis. A yield analysis system transforms
data into valuable, actionable information, making the data work for you.
DR YIELD’S YieldWatchDog
is the premium yield analysis solution that does both of these things: it makes
big data easily accessible and also performs complex and advanced analysis. YWD
monitors the entire manufacturing process, providing equipment monitoring and
full supply chain visibility. Enhanced data visualization tools enable
manufacturers deep insight into their manufacturing and test data.
In
addition, YieldWatchDog provides a deep root cause analysis of the data,
allowing manufacturers to take immediate action when there’s an issue. Its predictive
analytics can prevent yield excursions by sending warnings to engineers when an
anomaly is detected.
YieldWatchDogXI is an artificial intelligence layer with smart
pattern recognition, tool analytics and multivariate data monitoring,
harnessing the power of the data and unlocking its value through cutting-edge
AI analytics.
State-of-the-art
new smart fabs are designed and built using detailed digital 3D models to
determine the most efficient placement of tools, conveying systems, water lines
and pumps to name a few.
Digitalization
enables different platforms of an organization worldwide to communicate and
work together, sharing data and knowledge. Using smart goggles, for example,
technicians and engineers can collaborate on projects, troubleshoot or share
new technologies – clearly a huge advantage over travelling.
Another
interesting way smart manufacturing is practiced is by using so-called
scheduling software that calculates the most efficient path and timing for each
lot and tool, taking into account restrictions and requirements, thus increasing
throughput, decreasing the downtime on tools while ensuring wafers are produced
in a timely manner.
Robotics are
and always have always been essential to the advanced semiconductor
manufacturing industry. They cannot be beat in terms of precision, are capable
of learning and collecting large amounts of data and can be continuously
reprogrammed and reconfigured. Robotics perform the majority of manufacturing
tasks and transport the highly sensitive wafers.
The
semiconductor industry continues to push the limits of technology further than
anyone could have imagined. Smart manufacturing is the most technologically
advanced and efficient methodology to increased throughput, higher efficiency,
less waste, less downtime and more productive shifts, with more clearly defined
employee tasks and improved materials planning. By applying smart manufacturing,
semiconductor manufacturers can massively increase revenues while driving down
costs and also decreasing CO² output. We are proud to be able to
offer a turnkey solution as part of smart manufacturing.
About DR YIELD software & solutions GmbH
DR YIELD provides the leading-edge advanced analytics software YieldWatchDog for analysis and control of semiconductor manufacturing and test data. This enables semiconductor manufacturers as well as Fabless companies to improve important manufacturing dimensions such as equipment availability, throughput, operating costs and yield. Once installed YieldWatchDog allows you to get actionable insights into your data. For detailed information click here