Title: A Novel Reversible Scan Chain Technology that Improves Chain Diagnosis Resolution by 3X.
September 23 at 12:00 PM ET (9 AM PT)
During this webinar with Siemens and a customer, attendees will learn how diagnosis resolution was improved by 3X across a large industrial case study. This improvement was facilitated by failure analysis and accelerated the yield learning for an advanced node.
In this webinar, attendees will learn about:
- Traditional unidirectional scan chain diagnosis
- Reversible scan chain diagnosis
- Proven silicon results using reversible scan technology
Jayant D'Souza is the technical product manager for silicon learning products in the Siemens EDA Tessent group. He has 16 years of experience in the design-for-test (DFT), automatic test pattern generation (ATPG), scan diagnosis and yield learning areas. He is currently focused on the application of DFT and scan on defect diagnosis and yield learning. Jayant holds an MSEE degree from the University of North Carolina at Charlotte.
Szczepan Urban graduated with master's degree from Poznań University of Technology faculty of computer science (robotics and management). He joined Mentor Graphics in 2009 as a software quality engineer in the Silicon Test Solutions division. In 2013, he moved into a software engineering role to become a software engineering team lead in 2015 and then engineering manager in 2021. He leads an engineering team with focus on diagnosis driven yield analysis.