a new method is developed for a fast identification of the stability situation of industrial processes. the proposed method includes two factor ratios of the control constants for the upper and lower control limits to process these constants. an indication ratio is then defined as the ratio of the maximum data range value to the difference between the maximum and average values for individual d...

Control charts are used to identify the presence of assignable cause of variation in the process. Non-parametric control chart is an emerging area of recent development in the theory of SPC. Its main advantage is that it does not require any knowledge about the underlying distribution of the variable. In this paper a non-parametric control chart for controlling variability has been developed. I...

Control charts are themost extensively used technique to detect the presence of special cause variations in processes. They can be classified intomemory andmemoryless control charts. Cumulative sum and exponentially weightedmoving average control charts are memory-type control charts as their control structures are developed in such a way that the past information is not ignored as it is done i...

Fault detection and root cause identification are both important tasks in Multivariate Statistical Process Control (MSPC) for improving process and product quality. Most traditional control charts, including Hotelling’s T 2 chart and the Multivariate Exponential Weighted Moving Average (MEWMA) chart, separate the two tasks into independent and successive procedures by signaling the existence of...

This paper proposes a new chart with the generalized likelihood ratio (GLR) test statistics for monitoring the process variance of a normally distributed process. The new chart can be easily designed and constructed and the computation results show that it provides quite a satisfactory performance, including the detection of the decrease in the variance and the individual observation at the sam...