A Least Angle Regression Control Chart for Multidimensional Data

被引:65
作者
Capizzi, Giovanna [1 ]
Masarotto, Guido [1 ]
机构
[1] Univ Padua, Dept Stat Sci, I-35121 Padua, PD, Italy
关键词
Change-point detection; Exponentially weighted moving average; Multistage process; Profile monitoring; Statistical process control; Variable selection; WEIGHTED MOVING AVERAGE; MULTISTAGE MANUFACTURING PROCESSES; PHASE-I ANALYSIS; LINEAR PROFILES; DIAGNOSIS; ROBUSTNESS; NONNORMALITY; SCHEMES; LASSO;
D O I
10.1198/TECH.2011.10027
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In multidimensional applications, it is very rare that all variables shift at the same time. A statistical process control procedure would have superior efficiency when limited to the subset of variables likely responsible for the out-of-control conditions. The key idea of this article consists of combining a variable selection method with a multivariate control chart to detect changes in both the mean and variability of a multidimensional process with Gaussian errors. In particular, we develop a control chart for Phase II monitoring which integrates the least angle regression algorithm with a multivariate exponentially weighted moving average. Comparisons with related multivariate control schemes demonstrate the efficiency of the proposed control chart in a wide range of practical applications, including profile and multistage process monitoring. Further, the proposed scheme may also provide valuable diagnostic information for fault isolation. Supplemental materials, including an R package, are available online.
引用
收藏
页码:285 / 296
页数:12
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