Quality is one of the important criteria to determine the success of product. So quality control is required for all stages of production to ensure a good final product with lowest possible losses. Control charts are the most important means used to monitor the quality and its accuracy is measured by quickly detecting unusual changes in the quality to maintain the product and reduce the costs and losses that may result from the defective items. There are different types of quality control charts and new types appeases involving the concept of fuzziness named multinomial fuzzy quality control chart (FM) , dividing the product to accepted and not may not be accurate therefore adding fuzziness concept to quality charts confirm and add a new perspective. In this study, we will compare between the sensitivity of traditional quality control chart (fraction defective chart – P chart ) and multinomial fuzzy quality control chart (FM) to monitor the yarn gauge applied study using data (101 ) samples from Nineveh textile factory, sample size (20 ), we notice that (FM) control chart was more sensitive to detect the changes in the quality because it take in the consideration all the levels of the product not only accepted or not .So we have to take in consideration these kind of control charts to monitor the quality but dividing the product to accurate levels depending on experts.
