For attribute data with (very) low rates of defectives, attractive control charts can be based on the maximum of subsequent groups of r failure times, for some suitable r≥1, like r=5. Such charts combine good performance with often highly needed robustness, as they allow a nonparametric adaptation already for Phase I samples of ordinary size. In the present paper we address the problem of extending this approach to the situation where two characteristics have to be monitored simultaneously. Generalization to the multivariate case is straightforward
In this article we consider a control chart based on the sample variances of two quality characteris...
Parametric and nonparametric multivariate control charts that are proven very useful in monitoring t...
The T² chart and the generalized variance |S| chart are the usual tools for monitoring the mean vect...
For attribute data with (very) small failure rates often control charts are used which decide whethe...
For attribute data with (very) small failure rates control charts were introduced which are based on...
Monitoring multivariate and high-dimensional data streams is often an essential requirement for qual...
This article proposes two Shewhart charts, denoted np(xy) and np(w) charts, which use attribute insp...
Because the in-control distribution and parameters are generally unknown, control limits have to be ...
Many multivariate quality control techniques are used for multivariate variable processes, but few w...
In this article, we consider the synthetic control chart with two-stage sampling (SyTS chart) to con...
Autocorrelated data are common in today's process control applications. Many of these applications i...
In this paper, three single-control charts are proposed to monitor individual observations of a biva...
In this article, we consider the synthetic control chart with two-stage sampling (SyTS chart) to con...
In this paper a useful multivariate statistical process control method is proposed. In spite of the ...
For attribute data with (very) small failure rates control charts based on subsequent groups of r fa...
In this article we consider a control chart based on the sample variances of two quality characteris...
Parametric and nonparametric multivariate control charts that are proven very useful in monitoring t...
The T² chart and the generalized variance |S| chart are the usual tools for monitoring the mean vect...
For attribute data with (very) small failure rates often control charts are used which decide whethe...
For attribute data with (very) small failure rates control charts were introduced which are based on...
Monitoring multivariate and high-dimensional data streams is often an essential requirement for qual...
This article proposes two Shewhart charts, denoted np(xy) and np(w) charts, which use attribute insp...
Because the in-control distribution and parameters are generally unknown, control limits have to be ...
Many multivariate quality control techniques are used for multivariate variable processes, but few w...
In this article, we consider the synthetic control chart with two-stage sampling (SyTS chart) to con...
Autocorrelated data are common in today's process control applications. Many of these applications i...
In this paper, three single-control charts are proposed to monitor individual observations of a biva...
In this article, we consider the synthetic control chart with two-stage sampling (SyTS chart) to con...
In this paper a useful multivariate statistical process control method is proposed. In spite of the ...
For attribute data with (very) small failure rates control charts based on subsequent groups of r fa...
In this article we consider a control chart based on the sample variances of two quality characteris...
Parametric and nonparametric multivariate control charts that are proven very useful in monitoring t...
The T² chart and the generalized variance |S| chart are the usual tools for monitoring the mean vect...