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Predicting stability of integrated circuit test equipment using upper side boundary values of normal distribution

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In response to the growing complexity and performance of integrated circuit(IC),there is an urgent need to enhance the testing and stability of IC test equipment.A method was proposed to predict equipment stability using the upper side boundary value of normal distribution.Initially,the K-means clustering algorithm classifies and analyzes sample data.The accuracy of this boundary value is compared under two common confidence levels to select the optimal threshold.A range is then defined to categorize unqualified test data.Through experimental verification,the method achieves the purpose of measuring the stability of qualitative IC equipment through a deterministic threshold value and judging the stability of the equipment by comparing the number of unqualified data with the threshold value,which realizes the goal of long-term operation monitoring and stability analysis of IC test equipment.

K-means clustering algorithmthe upper side boundary of normal distributionthresholdintegrated circuit(IC)test equipment stability analysis

Zhan Wenfa、Hu Xinyi、Zheng Jiangyun、Yu Chuxian、Cai Xueyuan、Zhang Lihua

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School of Electronic Engineering and Intelligent Manufacturing,Anqing Normal University,Anqing 246133,China

School of Computer and Information Technology,Anqing Normal University,Anqing 246133,China

国家自然科学基金国家自然科学基金Yicheng Elite ProjectOpen Project of National Local Joint Engineering Laboratory of RF Integration and Microassembly TechnologyNational Key Laboratory of Integrated Chips and Systems ProjectAnhui University Research ProjectResearch on Testing Methods and Accuracy of High Frequency Signal Chips

6130604661640421202371KFJJ20230101SLICS-K2023162023AH0504812023AH050500

2024

10.19682/j.cnki.1005-8885.2024.0002

中国邮电高校学报(英文版)
北京邮电大学

中国邮电高校学报(英文版)

影响因子：0.419
ISSN：1005-8885
年,卷(期)：2024.31(2)
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