关键词: 统计过程控制, 变点, 数据深度, 概率密度轮廓

Abstract: In the stage of Phase I, it is very important to identify change point accurately. We propose an idea of change point identification based on the proximity of the data center. The proposed method transfers individual observations sequences into points in multi-dimensional space, and the variable is constructed based on data depth, then a change point location rule is developed. The simulation performance analysis result shows that new method could be used without normal distribution assumption. The comprehensive performance is better than the comparative methods.

Key words: Statistical Process Control, Change Point, Data Depth, Probability Density Profile