Demonstrates effective failure analysis using automated test equipment deliverables, indicating improved product quality assurance.
In the semiconductor industry, where reliability, yield, and performance are the key competitive factors, the ATE plays a pivotal role. It enables high-speed and highly accurate testing and prepares outputs such as a test log, waveform capture, diagnostic reports, and yield statistics necessary for successful failure analysis (FA). It also helps identify signatures of failure, isolate the defect sites, and correlate suspicious test-based abnormalities with their root causes. Parametric and functional aberrations, and thus ATE generation and verification, have become major tools for engineers to correlate complex defect behaviors with behavioral-phase-level defects that are generally overlooked if one simply relies on a traditional inspection system. Future integration of ATE data into advanced analytics and machine learning will also contribute to a proactive and prospective approach to FA. There remain numerous challenges today, however, in dealing with big data, delivering diagnostic resolution, and sustaining diagnostic methodology for new architectures such as 3D ICs and advanced nodes. This paper discusses the roles of ATE deliverables in FA and addresses the latest developments, bottlenecks, and future directions toward improving diagnostic resolution and product quality assurance.
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Amrutha Sampath (2026) studied this question.
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