Fuzzy Xbar and S Control Charts Based on Confidence Intervals

There have been changes since the companies realized important role of quality improvement in their success. If they are able to produce high products and satisfy demands, then can survive competitive global markets. Quality applications aim decrease variability, which leads less cost, production time, number defects, scrap, rework more customer satisfaction. be improved by reducing product variability. On other hand, uncertainty or subjectivity is a part many engineering real life problems. However, these problems cannot solved traditional methods. This study focuses on constructing Xbar S control charts fuzzy environment. The approach developed considering theoretical structure Shewhart charts. core depends combination parametric interval estimation statistics. Control limits samples presented numbers ensures maintain fuzziness An property that reduced A simulation was conducted for performance evaluation proposed chart sensitive process mean shifts variance changes, outperforms under variance. In addition, an example from literature shows effective way presenting characteristics, enables applicability