Test Innovations: Crossing the Chasm to a Chiplet Ecosystem
Speaker: Ming Zhang, PDF Solutions
Abstract:
This paper explores the role of test innovations, particularly the application of Artificial Intelligence (AI), in addressing the design and manufacturing challenges of the burgeoning chiplet ecosystem. Key industry shifts, including 3D integration, the proliferation of new fabs, and the use of AI to create AI chips, have introduced complexities such as process variation, supply chain security, and intricate verification processes. To bridge this gap, AI-driven adaptive testing offers significant opportunities. By leveraging a robust AI infrastructure for model deployment, businesses can use machine learning on wafer sort data to predict final test failures. A case study demonstrates that this “Data Feed Forward” approach allows for the elimination of redundant final tests with zero or near-zero defective parts per million (DPPM) impact, achieving skip rates above 88%. This significantly enhances efficiency, reduces costs, and improves system quality in high-volume manufacturing.
Keywords: chiplet ecosystem, test innovations, enterprise AI, adaptive testing, machine learning, data feed forward (DFF), semiconductor manufacturing, wafer sort, final test, supply chain management.
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