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...

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 ...

A manufacturing process cannot be released to production until it has been proven to be stable. Also, we cannot begin to talk about process capability until we have demonstrated stability in our process. This means that the process variation is the result of random causes only and all assignable or special causes have been removed. In complicated manufacturing processes, such as drilling proces...

The control chart (CC) is an important tool in Statistical Process Control (SPC) to improve the quality of products and processes. An unnatural variation in control maps assumes that an assignable cause affects the process is present, and some actions need to be applied to solve the problem. Thanks to their better recognition capability, NEURO-FUZZY is a powerful tool for process control and ra...

The control chart (CC) is an important tool in Statistical Process Control (SPC) to improve the quality of products and processes. An unnatural variation in control maps assumes that an assignable cause affects the process is present, and some actions need to be applied to solve the problem. Thanks to their better recognition capability, NEURO-FUZZY is a powerful tool for process control and ra...

The control chart (CC) is an important tool in Statistical Process Control (SPC) to improve the quality of products and processes. An unnatural variation in control maps assumes that an assignable cause affects the process is present, and some actions need to be applied to solve the problem. Thanks to their better recognition capability, NEURO-FUZZY is a powerful tool for process control and ra...

c-Chart was frequently used to monitor wafer defects during IC manufacturing. The clustering degree of defect on a wafer will increase along with the area of wafer gradually enlarging. The defect clustering causes the Poisson-based c-chart to exhibit many false alarms. Although several revised control charts have been developed to reduce the number of false alarms, those control charts still ha...