The application of mean control chart in managing industrial processes

A New Control Chart to Monitor Mean Shifts of Bi-Variate Quality Control Processes

Application of robust multivariate control chart with Winsorized Mean: a case study

Water pH and active ingredient concentration are two of the most important variables to consider in the manufacturing process of fungicides. If these variables do not meet the required standards, the quality of the product may be compromised and lead to poor fungicide performance when water is used as the application carrier, which is in most cases. Given the correlation between the variable...

Mcusum Control Chart Procedure: Monitoring the Process Mean with Application

Multivariate cumulative sum (MCUSUM) control charts are widely used in industry because they are powerful and easy to use. They cumulate recent process data to quickly detect out-of-control situations. MCUSUM procedures will usually give tighter process control than classical quality control charts. A MCUSUM signal does not mean that the process is producting bad product. Rather it means that a...

The Effect of Estimation Error on Risk-adjusted Bernoulli GEWMA Control Chart in Multistage Healthcare Processes

Background and objectives: Risk-adjusted Bernoulli control chart is one of the main tools for monitoring multistage healthcare processes to achieve higher performance and effectiveness in healthcare settings. Using parameter estimates can lead to significantly deteriorate chart performance. However, so far, the effect of estimation error on this chart in which healthcare ...

A new chart-independent method for fast identification of control level of industrial processes using continuous data

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...