The EWMA chart for the standard deviation is a useful tool for monitoring the variability of a process quality characteristic. The performance of this chart is usually evaluated under the assumption of known parameters. However, in practice, process parameters are estimated from an in-control Phase I data set. A modified EWMA control chart is proposed for monitoring the standard deviation when ...

The Pareto chart is a bar chart of frequencies sorted by frequency. The most popular incarnation of the chart puts the highest bars on the left and includes a line showing the scores produced by adding the heights in order from left to right. This chart is used widely in quality control settings to identify critical factors leading to failure or defects in a process. This article presents revis...

In this research, we propose a bi-objective model for the economic-statistical design of the X-bar and S control charts. The model minimizes out-of-control average time to signal as well as minimizing mean hourly loss-cost where it incorporates the Taguchi loss function. Statistical constraint is considered in the model to achieve desired in-control time to signal. A non-dominated sort...

In this article, utilizing Delphi 7.0 as the development platform, we design the system to collect or record measurement data through electronic digital caliper and digital table, compute control parameters of quality control chart, draw the process control chart of controlled objectives and read, analyze and manage the measurement data.

For signalling alarms sooner when the dispersion of a multivariate process is “increased”, a multivariate control chart for Phase II process monitoring is proposed as a supplementary tool to the usual monitoring schemes designed for detecting general changes in the covariance matrix. The proposed chart is constructed based on the one-sided likelihood ratio test (LRT) for testing the hypothesis ...

Control chart is the most important Statistical Process Control tool used to monitor reliability and performance of industrial processes. For monitoring changes in process dispersion, the R and S charts are widely used. These control charts perform better under the ideal assumption of normality but are well known to be very inefficient in presence of outliers or departures from normality. In th...