A novel nbti-aware chip remaining lifetime prediction framework using machine learning

Yu Guang Chen, Ing Chao Lin, Yong Che Wei

研究成果: Conference contribution

摘要

Negative-Bias Temperature Instability (NBTI) poses serious threats to modern ICs and may lead to timing and functional failure. If these failures occur in industrial automated production systems, the malfunctioning system can cause significant economic losses due to unacceptable fabrication quality and yield. Although preventive maintenance is a useful way to avoid such a situation, executing preventive maintenance on a frequent basis will also introduce significant production line downtime. To accurately execute the preventive maintenance just before circuit failure occurs, a chip remaining lifetime estimation method is in demand. In this paper, we propose a framework for predicting the remaining lifetime of the chip. This framework can adapt to changes in the process and operating voltage. The framework tracks representative aging indicators through machine learning methods in order to predict the remaining lifetime of the chip. In addition, we also investigate the impact of changes in hyperparameters, such as training sample sizes, on prediction performance. The experimental results show that the proposed framework achieves an average accuracy and precision of 97.3% and 97.2%, respectively, and the accuracy is 2.54% higher than the strategy used to determine chip health level in a previous work.

原文English
主出版物標題Proceedings of the 22nd International Symposium on Quality Electronic Design, ISQED 2021
發行者IEEE Computer Society
頁面476-481
頁數6
ISBN(電子)9781728176413
DOIs
出版狀態Published - 2021 四月 7
事件22nd International Symposium on Quality Electronic Design, ISQED 2021 - Santa Clara, United States
持續時間: 2021 四月 72021 四月 9

出版系列

名字Proceedings - International Symposium on Quality Electronic Design, ISQED
2021-April
ISSN(列印)1948-3287
ISSN(電子)1948-3295

Conference

Conference22nd International Symposium on Quality Electronic Design, ISQED 2021
國家/地區United States
城市Santa Clara
期間21-04-0721-04-09

All Science Journal Classification (ASJC) codes

  • 硬體和架構
  • 電氣與電子工程
  • 安全、風險、可靠性和品質

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