Maximum Multivariate Exponentially Weighted Moving Average and Maximum Multivariate Cumulative Sum Control Charts for Simultaneous Monitoring of Mean and Variability of Multivariate Multiple Linear Regression Profiles

Maximum multivariate exponentially weighted moving average and maximum multivariate cumulative sum control charts for simultaneous monitoring of mean and variability of multivariate multiple linear regression

Multivariate Exponentially Weighted Moving Average Chart for Monitoring Poisson Observations∗

In many practical situations, multiple variables often need to be monitored simultaneously to ensure the process is in control. In this article, we develop a feasible multivariate monitoring procedure based on the general Multivariate Exponentially Weighted Moving Average (MEWMA) to monitor the multivariate count data. The multivariate count data is modeled using Poisson-Lognormal distribution ...

Mixed Cumulative Sum-Exponentially Weighted Moving Average Control Charts: An Efficient Way of Monitoring Process Location

Shewhart, exponentially weighted moving average (EWMA), and cumulative sum (CUSUM) charts are famous statistical tools, to handle special causes and to bring the process back in statistical control. Shewhart charts are useful to detect large shifts, whereas EWMA and CUSUM are more sensitive for small to moderate shifts. In this study, we propose a new control chart, named mixed CUSUM-EWMA chart...

Simultaneous Monitoring of Multivariate-Attribute Process Mean and Variability Using Artificial Neural Networks

In some statistical process control applications, the quality of the product is characterized by thecombination of both correlated variable and attributes quality characteristics. In this paper, we propose anovel control scheme based on the combination of two multi-layer perceptron neural networks forsimultaneous monitoring of mean vector as well as the covariance matrix in multivariate-attribu...

Mixed Exponentially Weighted Moving Average-Cumulative Sum Charts for Process Monitoring

The control chart is a very popular tool of statistical process control. It is used to determine the existence of special cause variation to remove it so that the process may be brought in statistical control. Shewhart-type control charts are sensitive for large disturbances in the process, whereas cumulative sum (CUSUM)–type and exponentially weighted moving average (EWMA)–type control charts ...