in statistical quality control a very widely used measure is average run length (arl) which may be worked out by different methods like integral equation, approximations, and monte carlo simulations. the arl measure and the other related measures are of major significance in every type of production process. an omission in its computation (and hence its related measures such as extra quadratic ...

Two independent methods for improving quality are engineering process control (EPC) and statistical process control (SPC). The first method tries to minimize variability by handling process variables so as to keep the outputs of the process on target. While the latter method, SPC does the same basic task of minimizing variability by supervising and eradicating the assignable causes of variation...

identification of a real time of a change in a process, when an out-of-control signal is present is significant. this may reduce costs of defective products as well as the time of exploring and fixing the cause of defects. another popular topic in the statistical process control (spc) is profile monitoring, where knowing the distribution of one or more quality characteristics may not be appropr...

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 ...

Control Chart Patterns (CCPs) recognition is one the most important concepts in control chart application. Relating the patterns exhibited on the control chart to assignable causes is an ambiguous and vague task especially when multiple patterns co-exist. In this study, a fuzzy rule-based system is developed for X ̅ control charts to prioritize the control chart causes based on the accumulated e...