SPOT: Fast and Optimal Built-In Redundancy Analysis Using Smart Potential Case Collection

With advancements in manufacturing and design technology, memory integration density has improved. However, as integration density increases, the cost of testing and repairing memory has also risen, posing a significant challenge in memory production. To address this challenge, built-in self-repair (BISR) has been proposed. Traditional built-in redundancy analysis (BIRAs) performs limited analysis of faults during the fault collection process, resulting in a significant delay in generating a repair solution after the test sequence is completed. This inefficiency arises from the time required to repair the memory posttest. This article proposes a new fast and optimal BIRA using smart potential case collection. The proposed BIRA conducts a detailed analysis of detected faults during the test process. Using this novel fault collection results, a potential case is generated. This is a repair case that can repair the memory with a high probability and is generated immediately after the test sequence ends. If the memory cannot be repaired by the potential case, an exhaustive search is conducted for the faults requiring further analysis to generate an optimal repair solution. Compared to previous studies, the proposed BIRA demonstrates extremely low analysis time with an optimal repair rate.

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Publication Details

Journal
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Published
2024-11-27
DOI
https://doi.org/10.1109/tvlsi.2024.3499955
Citations
1
Primary Topic
Engineering and Test Systems
Type
article
Field-Weighted Citation Impact
0.33
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article

SPOT: Fast and Optimal Built-In Redundancy Analysis Using Smart Potential Case Collection

Sungho Kang, Donghyun Han, Sunghoon Kim, Dayoung Kim
1 citations
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Engineering and Test Systems
0.33
article

SPOT: Fast and Optimal Built-In Redundancy Analysis Using Smart Potential Case Collection

Sungho Kang, Donghyun Han, Sunghoon Kim, Dayoung Kim
article en
1 citations

Abstract

With advancements in manufacturing and design technology, memory integration density has improved. However, as integration density increases, the cost of testing and repairing memory has also risen, posing a significant challenge in memory production. To address this challenge, built-in self-repair (BISR) has been proposed. Traditional built-in redundancy analysis (BIRAs) performs limited analysis of faults during the fault collection process, resulting in a significant delay in generating a repair solution after the test sequence is completed. This inefficiency arises from the time required to repair the memory posttest. This article proposes a new fast and optimal BIRA using smart potential case collection. The proposed BIRA conducts a detailed analysis of detected faults during the test process. Using this novel fault collection results, a potential case is generated. This is a repair case that can repair the memory with a high probability and is generated immediately after the test sequence ends. If the memory cannot be repaired by the potential case, an exhaustive search is conducted for the faults requiring further analysis to generate an optimal repair solution. Compared to previous studies, the proposed BIRA demonstrates extremely low analysis time with an optimal repair rate.

IEEE Transactions on Very Large Scale Integration (VLSI) SystemsVol. 33(3)
Yonsei University (KR)
Openalex Percentile: Top 39%
Engineering and Test Systems
0.33
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