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Accelerating Yield and Failure Analysis with Diagnosis

Overview

Learn about methodologies for yield improvement and defect identification for digital semiconductor devices. Scan diagnosis, a software-based technique, can effectively identify defects in digital logic and scan chains. This flow has been successfully applied in industrial practice to achieve a high physical failure analysis success rate and improved yield. The webinar will also cover recent advancements in diagnosis technology and industrial case studies.

What You Will Learn

In this webinar you will learn about ways that allow failure analysis to regain its effectiveness and position as a key contributor to yield improvement in digital semiconductor devices, as well as significantly improve the analysis of field returns.
Topics to be covered include:

  • Best practices for data collection and diagnosis of digital semiconductor devices
  • Statistical analysis of diagnosis results to pick the correct dies for an effective failure analysis
  • Layout-aware diagnosis
  • Scan chain diagnosis
  • Correlating diagnosis and DFM analysis results
  • Case studies
     

About the Presenter

Presenter Image Geir Eide

Product Marketing Manager, Silicon Learning Products

Geir Eide is the Product Marketing Manager for the Silicon Learning Products in the Silicon Test Solutions Group at Mentor Graphics. Eide has been involved in semiconductor test and design-for-test for the last 15 years and has held positions as Development Engineering Manager and Technical Marketing Engineer at Mentor Graphics. Previously, Eide held an applications management position at Teseda Corporation. He earned BS and MS degrees in Electrical and Computer Engineering from the University of California at Santa Barbara.

Who Should View

  • Engineers and managers responsible for digital semiconductor product design, test, quality, or yield
  • Engineers and managers responsible for digital semiconductor product and technology advancement
  • Failure Analysis Lab Managers or Process Engineers
  • Engineers involved in manufacturing production or process development
  • Anyone involved with the impact of low yield or low product quality
     

Products Covered

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