Mentor Graphics YieldAssist Supports Automated,Server-based Use Model for Rapid Yield Learning
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WILSONVILLE, Ore., October 23, 2006 – Mentor Graphics Corporation (Nasdaq: MENT) today announced that its YieldAssist™ tool now supports an automated, server-based use model for high volume diagnosis of wafer test failures. With the ability to quickly and accurately identify and isolate yield-limiting defects, the YieldAssist product represents a new era in the analysis of manufacturing failures, and enables a new source of yield learning. YieldAssist takes failure information directly from manufacturing scan test, and through advanced diagnostics, identifies failure causes. With this new functionality, YieldAssist is now a fully automated diagnosis job server that monitors multiple directories for failure logs from Automatic Test Equipment (ATE) and manages the diagnosis runs and resources. The server dispatches jobs to machines running diagnosis, balancing the load for maximum throughput. Results are collected into a database for future analysis and reporting. The system is fault tolerant, restarting or removing diagnosis machines that have become unavailable, and marking the queue for easy stop and restart. Furthermore, volume diagnostics is architected in a way that ensures no loss in accuracy, whether processing one failing die or 10,000. “With the improvements in the YieldAssist product, we have made it more efficient for users to get diagnosis results on large volumes of production test failures,” said Greg Aldrich, Director of Marketing, Design-for-Test product group, Mentor Graphics. “We are on the path to moving YieldAssist from a pure automated scan diagnosis solution to a powerful yield learning tool.” About YieldAssist About Mentor Graphics
Mentor Graphics and TestKompress are registered trademarks; YieldAssist and FastScan are trademarks of Mentor Graphics Corporation. All other company or product names are the registered trademarks or trademarks of their respective owners. For more information, please contact: Sonia Harrison
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