Change patterns of time series-based control charts

被引:31
作者
Hu, SJ [1 ]
Roan, C [1 ]
机构
[1] PERCEPTRON INC,FARMINGTON HILLS,MI 48024
关键词
autocorrelated process; statistical process control; time series analysis;
D O I
10.1080/00224065.1996.11979680
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Autocorrelation in process measurements results in false alarms when traditional control charts, such as (X) over bar and R charts, are applied in process monitoring. A popular approach proposed in the literature is to use time series models to remove the autocorrelation, and then to apply control charts to the residuals, or prediction errors. However, when a time series model is used to remove the autocorrelation, the change patterns may be severely altered, making the interpretation of a process change and root cause analysis erroneous. This paper develops charts for the comparison of change patterns for two types of additive process faults before and after applying time series modeling. The process changes are sustained mean shifts and sporadic spikes. These charts provide improved understanding of the characteristics of autocorrelated processes.
引用
收藏
页码:302 / 312
页数:11
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