Rudolph Technologies, Inc. announced today that the SUNY College of Nanoscale Science and Engineering (CNSE), Albany, NY, has selected its Discover Enterprise Yield Management Software (YMS) to provide an integrated data warehouse and analytics system for the Global 450 Consortium (G450C) equipment development program. The Rudolph YMS will be used to combine all types of manufacturing data from defect, metrology, process, test and wafer tracking into a single system for comprehensive analysis. The software includes patented analytics specific to the semiconductor industry that will enable G450C to accelerate its process development for this strategic, half-billion dollar program for the industry.
Paul Farrar, general manager of CNSE’s G450C program, said, “As part of our focus on 450mm manufacturing we are not just qualifying the process tools and materials but also the next generation of controls and methodologies necessary to meet the new dynamics created by consumer demands. Rudolph software has an established architecture that aggregates all data collected in the factory into a single database and then applies advanced analytics to that database in order to make sense of the data. These techniques will benefit multiple industries as well as leading-edge 300mm fabs and next generation advanced packaging lines.”
“It was very gratifying to learn that CNSE, after a thorough evaluation of multiple competitive company’s technology and proposals, has chosen Rudolph to be its partner and supplier of data warehousing and analytics,” said Ardy Johnson, Rudolph’s senior vice president of corporate alliances. “We are encouraged to have this important validation of our technology.”
Discover Enterprise is a comprehensive yield management system that aggregates and stores manufacturing data and provides real-time manufacturing monitoring and in-line yield management. It is the foundation of a fully-integrated database and analytical routines that help semiconductor, LED, compound semiconductor, automotive, FPD, HDD and other related manufacturers improve yield, productivity and profitability in their manufacturing lines. It integrates and analyzes data from all inspection, metrology, process, fault detection, run-to-run and test systems in the fab and across the supply chain (from wafer to final packaging) to provide a complete report of fab-wide yield problems, turning raw data into actionable information that separates random from systematic yield loss. Engineers use this information to optimize process tool performance (fleet management) and quickly identify and correct the causes of yield excursions.