Design of demerit control charts with fuzzy c-means clustering and an application in textile sector

Companies use process control to detect and prevent defects in production. One of the most commonly used technique is the control charts. To control multiple dimensions of quality on one control chart, multivariable control charts, control charts for attributes and demerit control charts are widely used. In this study, we use demerit control charts to monitor multiple defect types and propose to employ the fuzzy c-means method to cluster the defect types based on pre-specified criteria. The criteria are chosen to represent the severity of defect types and specified as (i) number of scraps, (ii) number of reworks and (iii) time of the rework. In order to test the proposed method, u and c attribute control charts and demerit control charts for six instances in a textile company are used and compared. It is observed that both the scrap and the repair rates are decreased when the proposed method of the demerit control chart is used.