Seyed Ali Asghar Mostafavi Sabet - Islamic Azad University, Science and Research Branch
Hossein Sabbari - Msc, Industrial engineering
Mohamad reza Salehi rad - Assistant professor, Statistics

Manufacturing organizations have to improve their products quality continuously to remain in today‟s competitive production environment. The work in this paper has presented a method to identify unknown patterns between manufacturing process parameters and the defects of output products, and also identify the relationships among the defects. Discovery of these patterns helps practitioners to achieve two main goals: first, identification of those process parameters that can be used to control and reduce output product‟s defects; and second, identification of those defects that have very probably common roots. In this paper, a fuzzy data mining algorithm is used to discover fuzzy association rules for weighted quantitative data. Application of the association rules algorithm developed in this paper is illustrated with a net making process in a netting plant. After implementing this proposed method, a significant reduction in the rate of the defects in produced nets was observed.

Data mining, Association rules, Defect, Fuzzy sets, Root cause analysis