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