LAUSR

Conventional multivariate cumulative sum control charts are more sensitive to small shifts than T 2 control charts, but they cannot get the knowledge of manufacturing process through the learning of in-control data due to the characteristics of their own structures. To address this issue, a modified multivariate cumulative sum control chart based on support vector data description for multivariate statistical process control is proposed in this article, which is named D - MCUSUM control chart. The proposed control chart will have both advantages of the multivariate cumulative sum control charts and the support vector data description algorithm, namely, high sensitivities to small shifts and learning abilities. The recommended values of some key parameters are also given for a better application. Based on these, a bivariate simulation experiment is conducted to evaluate the performance of the D - MCUSUM control chart. A real industrial case illustrates the application of the proposed control chart. The results also show that the D - MCUSUM control chart is more sensitive to small shifts than other traditional control charts (e.g. T 2 and multivariate cumulative sum) and a D control chart based on support vector data description.