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AI/ML for Yield Learning and Test Optimization in Semiconductor Manufacturing: A Review of Adaptive Testing, Smarter Limits, and Diagnostic Preservation

2026-05-22

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<title>Abstract</title> <p>With the increase in complexity of semiconductor devices at advanced technology nodes with billions of transistors, the traditional static test methods and rule-based yield management systems are insufficient to meet high-volume quality, throughput, and cost targets. Machine learning and other advances in artificial intelligence have formed enabling technologies to evolve yield learning...

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Literature Corpus work: 431c074d-2ff9-5700-90c2-ae8d51dae44a
DOI: 10.21203/rs.3.rs-9464431/v1

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