AI-Powered Analytics Using Empirical Data from In-Field Measurements and Reliability Qualification

Standards and regulatory expectations in automotive and HPC applications suggest compliance to challenging reliability requirements. Particularly, semiconductor aging and degradation needs to be managed proactively in-field. This paper presents stress testing results for an advanced process technology node that are characterized via aging models usable for in-field deployment, thereby enabling calculations of useful RAS and FuSa metrics. We discuss an end-to-end approach managing semiconductor degradation challenges, helping the industry to tackle tough quality requirements.