AI-Based Design of an Efficient Final Test Scheme

This paper proposes an AI-based optimization solution to address the efficiency and cost challenges in the Final Test (FT) of semiconductor testing. Previous experiments indicate that a test throughput can be enhanced by 44.13% through multi-site dynamic load balancing, adaptive test algorithms and mixed-signal hierarchical test strategies.

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Published
2025-04-28
DOI
https://doi.org/10.1109/icaidt66272.2025.00107
Primary Topic
Engineering and Test Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Based Design of an Efficient Final Test Scheme

Chunmei Pei, Shuo Wang, Guoying Wang, Zhu Gongsheng
Engineering and Test Systems
article

AI-Based Design of an Efficient Final Test Scheme

Chunmei Pei, Shuo Wang, Guoying Wang, Zhu Gongsheng
article en

Abstract

This paper proposes an AI-based optimization solution to address the efficiency and cost challenges in the Final Test (FT) of semiconductor testing. Previous experiments indicate that a test throughput can be enhanced by 44.13% through multi-site dynamic load balancing, adaptive test algorithms and mixed-signal hierarchical test strategies.

Beijing University of Technology (CN), Beijing Polytechnic (CN)
Openalex Percentile: Top 71%
Engineering and Test Systems
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AI-Based Design of an Efficient Final Test Scheme — Chunmei Pei, Shuo Wang, et al. · (2025) | TGRS Research Map | TGRS