Scan chain diagnosis has long been used to identify manufacturing defects and yield issues in early ramp. Identifying and eliminating these yield issues quickly and efficiently are required to ensure business success of a product. Root-causing defect mechanisms that produce yield loss require a combination of fault isolation and failure analysis. The advent of new technologies, like backside power in advanced process nodes, have made fault isolation extremely challenging. In this webinar, we describe three new software-based technologies that provide accurate localization to enable efficient failure analysis of both front-end and back-end line defects. We also present results for each of these techniques. These technologies can alleviate the pressure on fault isolation for front-end of line defects and provide reduced area for back-end of line defects for Physical Failure Analysis (PFA).
What can you learn from this webinar:
- Scan technology
- Chain diagnosis
- Directed FA using scan chain diagnosis
- Global signal diagnosis
- Cell-aware chain diagnosis
- Layout-aware chain diagnosis
- Yield improvement using directed FA
Who would benefit most from the content in this webinar:
- Product engineers using scan diagnosis data
- Yield analysts
- Fault isolation engineers, failure analysis engineers
Meet the Speaker
Jayant D'Souza
Principal Technical Product Manager
Jayant D’Souza is the Principal Technical Product Manager for yield learning products in the Siemens EDA Tessent® group. He has about 18 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 (USA).