Nova (NASDAQ: NVMI) today announced that its co-authored paper with GLOBALFOUNDRIES on ‘Implementation of machine learning for high volume manufacturing metrology challenges’ has been selected as the winner of the Diana Nyyssonen award for ‘best paper at SPIE‘s 2018 Advanced Lithography Symposia.’ The award was granted to Nova and GF on the opening day of the 2019 Conference. The paper is a result of the continuous partnership between the companies and demonstrates the innovation Nova promotes in advanced process control utilizing its unique and differentiated software solutions. The methodology described in the paper was already installed and is utilized by GF in high volume manufacturing.
The joint effort demonstrates that predictive metrology based on machine learning is an advantageous and complementary technique for high volume semiconductor manufacturing. The collaborative work of Nova and GF examined the suitability of machine learning to address high volume manufacturing metrology requirements for applications in both front end of line (FEOL) and back end of line (BEOL) in advanced technology nodes. Feasibility to predict CD values from an inline measurement using machine learning engines was demonstrated, as well as the usage of machine learning data to directly predict electrical parameters.
“We are honored to be selected for this prestigious award in collaboration with our partners at GF,” said Dr. Shay Wolfling, Chief Technology Officer of Nova. “This innovative metrology solution is enabled by our NOVAFitTM technology that enhances traditional modeling capabilities with advanced machine learning algorithms. The joint work with GF has demonstrated once more that through collaboration with our customers our most advanced machine-learning solutions can quickly proliferate and be validated in high volume production in advanced technology nodes.”