A Quality Management using Data Mining Techniques for Small and Medium Manufacturing Companies

In competition of the global economic system, only first-class products can gain competitive advantages in the global market. However, most small and medium manufacturing companies don't have systematic and formalized business, and the quality and quantity of their corporate personnel are poor. It is not easy for them to maintain stable production of quality products. In order to overcome the limitations above, it is important to improve the quality of products, identify and improve the points which need to be managed urgently and carry out the optimal manufacturing process conditions continuously. In this study, to carry out quality management effectively in small and medium manufacturing companies, we proposed a data mining techniques-based quality management system to identify points needed to be managed urgently and maintain optimal manufacturing process conditions. The proposed system can identify quality management point easily by performing data mining's association analysis and Excel's multi-dimensional analysis. First, main process variables which have an effect on appearance of inferior-quality products are identified by applying decision tree. Second, rules of process variables which are related with fair-quality products and appearance of inferior-quality products are explained and process variables' parameters which can produce fair-quality products stably are decided. At the same time, the validity of the existing process variables' parameters are verified by decision tree based on the existing standard process parameters, and the optimal process parameters are set finally. The proposed system was applied to a domestic small and medium manufacturing company which produces breathable film. The result confirmed that the efficiency of quality management business and the decrease of breathable film product's inferiority.