
doi: 10.1002/nav.21475
AbstractNonparametric control charts are useful in statistical process control when there is a lack of or limited knowledge about the underlying process distribution, especially when the process measurement is multivariate. This article develops a new multivariate self‐starting methodology for monitoring location parameters. It is based on adapting the multivariate spatial rank to on‐line sequential monitoring. The weighted version of the rank‐based test is used to formulate the charting statistic by incorporating the exponentially weighted moving average control scheme. It is robust to non‐normally distributed data, easy to construct, fast to compute and also very efficient in detecting multivariate process shifts, especially small or moderate shifts which occur when the process distribution is heavy‐tailed or skewed. As it avoids the need for a lengthy data‐gathering step before charting and it does not require knowledge of the underlying distribution, the proposed control chart is particularly useful in start‐up or short‐run situations. A real‐data example from white wine production processes shows that it performs quite well. © 2012 Wiley Periodicals, Inc. Naval Research Logistics 59: 91–110, 2012
Nonparametric procedure, Applications of statistics in engineering and industry; control charts, Self-starting, multivariate EWMA, robustness, self-starting, spatial rank, nonparametric procedure, Multivariate EWMA, statistical process control, Distribution-free, Statistical process control, Spatial rank, Robustness, Hypothesis testing in multivariate analysis, distribution-free, Directional data; spatial statistics
Nonparametric procedure, Applications of statistics in engineering and industry; control charts, Self-starting, multivariate EWMA, robustness, self-starting, spatial rank, nonparametric procedure, Multivariate EWMA, statistical process control, Distribution-free, Statistical process control, Spatial rank, Robustness, Hypothesis testing in multivariate analysis, distribution-free, Directional data; spatial statistics
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 90 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
