A Comprehensive Study on the Application of Multivariate Control Chart for Online Process Monitoring in CNC Machine

This study’s primary objective is to use statistical process control tools, such as univariate control charts, multivariate (multiple variables) control charts (i.e., Hotelling T2 control chart, MEWMA control chart, and MCUSUM control chart), and process capability to regulate the CNC machine’s process parameter for a small manufacturing sector. This work focuses on monitoring the quality parameter of the final (end) product of the CNC machine using univariate control charts and multivariate control charts. In this research work, two end products are used to verify which control chart gives better results in monitoring the quality parameter of the product. However, when multiple quality characteristics come in one product or process, the univariate control chart becomes less efficient, and the multivariate control chart is used instead of the univariate control chart. This paper’s result was compared, applying the univariate control chart (x̅ chart and R chart) and multivariate control chart (Hotelling T2 control chart, multivariate exponentially weighted moving average control chart, and multivariate cumulative sum control chart) for online process monitoring and quality control. This study was essential to determine one of the best options for this control chart for the industrial process and for online monitoring of the different quality parameters of the product.