The Journal of China Universities of Posts and Telecommunications ›› 2024, Vol. 31 ›› Issue (2): 85-93.doi: 10.19682/j.cnki.1005-8885.2024.0002

Special Issue: 集成电路

Previous Articles     Next Articles

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


  • Received:2023-11-01 Revised:2024-02-25 Online:2024-04-30 Published:2024-04-30
  • Contact: Xin-Yi HU


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.

Key words:

K-means clustering algorithm, the upper side boundary of normal distribution, threshold, IC test equipment stability analysis