Component-cluster-association analysis method for quality change and degradation of domestic aerospace components

In the development process of domestic aerospace components, the life enhancement test, as the test item that takes the longest time and consumes the most samples, is one of the core links to find out the reliability level of domestic components. This paper focuses on the analysis of data relevant to domestic aerospace components, both before and after the life test. The objective is to investigate the potential correlation between the quality fluctuation observed in the data before the life test and the degradation behavior of parameters observed after the life enhancement test. To achieve this target, various statistical methods were leveraged, including principal component analysis, cluster analysis, and association analysis. The proposed approach was validated through a case study involving typical domestic integrated circuits. Based on the outcomes of the case study, the method flow was refined and finalized. In the development process of domestic aerospace components, it is imperative to conduct research on the quality stability of these components and identify potential risks related to quality fluctuations promptly via employing modern statistical analysis methods. It aims to bridge the gap between classical quality and reliability theory. This study provides a theoretical basis for the control of key quality characteristics. By leveraging this method, it is possible to identify the core performance parameters that play a significant role in the quality control stage.