Abstract
Manufacturing organizations have to improve the quality of their products regularly to survive in today’s competitive production environment. This paper presents a method for identification of unknown patterns between the manufacturing process parameters and the defects of the output products and also of the relationships between the defects. Discovery of these patterns helps practitioners to achieve two main goals: first, identification of the process parameters that can be used for controlling and reducing the defects of the output products and second, identification of the defects that very probably have common roots. In this paper, a fuzzy data mining algorithm is used for discovery of the fuzzy association rules for weighted quantitative data. The application of the association rule algorithm developed in this paper is illustrated based on a net making process at a netting plant. After implementation of the proposed method, a significant reduction was observed in the number of defects in the produced nets.
Highlights
Manufacturing organizations have to improve the quality of their products regularly in order to survive in today’s competitive production environment
This paper presents a methodology for identification of unknown patterns between the manufacturing process parameters and defects of the output products
This research clearly points out the potential of association rules as a tool for industrial application especially in manufacturing processes
Summary
Manufacturing organizations have to improve the quality of their products regularly in order to survive in today’s competitive production environment. The manufacturing process parameters can be categorized based on the following: man, machine, material, method, and environment Controlling these parameters and finding their relationships with the product defects will help Quality Improvement Teams (QIT) reduce and eliminate the defects. This paper presents a methodology for identification of unknown patterns between the manufacturing process parameters and defects of the output products. It identifies the relationships between the defects. The proposed technique will obtain interesting, understandable patterns discovered among the process parameters and output defects due to use of the concept of fuzzy sets and weights.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
