Analyzing Fuzzy Probabilistic Approach to Optimize U Control Chart

Statistical process control (SPC) is an effective method for improving a producer’s quality and productivity. Control charts are the primary tools of SPC used to discriminate between assignable and common causes of variation and to improve the quality of a process. A control chart which is used to monitor the average number of non-conformities is U control chart. Uncertainty comes from the measurement system including operators and gauges, and environmental conditions. In this context, fuzzy set theory is a useful tool to handle this uncertainty. This study constructs the fuzzy U control chart. By using fuzzy U control chart, the flexibility of economic-statistical of static and variable sampling schemes for U control chart is investigated. The results of control charts based on different approaches are compared. It’s seen that fuzzy theory performs better than probability theory in monitoring the product quality.

Keywords:

Statistical process control , Fuzzy sets theory , U control chart , Cost of quality.