Abstract: Today's society is characterized by consumers becoming more educated and demanding for products and services they use. Wherever, organizations are structured to respond the explicit or implicit needs of consumers, which lead to increased competitiveness of organizations. This competitiveness is reflected in the ongoing quest to provide high quality products and excellence process deve...

A few years ago, I was provided data on Hallsville ISD’s Texas Assessment of Academic Skills (TAAS) test results by Dr. Elizabeth Clark, Assistant Superintendent for Educational Operations. Elizabeth requested that I use statistical process control (SPC) charts to analyze the test scores and then submit recommendations for improvement. The reading and math charts are shown on Figures A and B, r...

Process shift is an important input parameter in the economic design of control charts. Earlier x control chart designs considered constant shifts to occur in the mean of the process for a given assignable cause. This assumption has been criticized by many researchers since it may not be realistic to produce a constant shift whenever an assignable cause occurs. To overcome this difficulty...

Shewhart, exponentially weighted moving average (EWMA), and cumulative sum (CUSUM) charts are famous statistical tools, to handle special causes and to bring the process back in statistical control. Shewhart charts are useful to detect large shifts, whereas EWMA and CUSUM are more sensitive for small to moderate shifts. In this study, we propose a new control chart, named mixed CUSUM-EWMA chart...

Statistical Quality Control (SQC) is a branch of Total Quality Management (TQM) that defines a quality philosophy and set the guiding principles that represent the foundation for a continuously improving organisation. Statistical Process Control (SPC) and Acceptance Sampling are the two major parts of SQC. SPC is an effective tool that aims to get and keep processes under control and ensure tha...

there are many situations for statistical process in which we have both random and vagueinformation. when uncertainty is due to fuzziness of information, fuzzy statistical control charts play animportant role in the monitoring process, because they simultaneously deal with both kinds of uncertainty.dealing with fuzzy characteristics using classical methods may cause the loss of information and ...

Conventional statistical process control (SPC) charts require the normality assumption on the process response distribution. In reality, this assumption is often invalid. In such cases, it has been well demonstrated in the literature that results from control charts using the normality assumption may not be reliable in the sense that their actual false alarm rates could be substantially larger ...