A KDD-based spinning process decision system

Abstract

Although automated equipments are widely employed within yarn production, it has taken more interests to reconfigure the product development way with the KDD and AI technologies in order to improve the yarn quality and to minimize production cost. The existing process data which were recorded in large quantities to ensure the ability to trace production steps can be used to improve the quality itself. This paper investigates knowledge discovery methods from the yarn production database, and presents a novel KDD-based intelligent decision model (IDM) for process optimization. The applied cases are demonstrated that the intelligent model to control the yarn quality is promising. © Springer-Verlag Berlin Heidelberg 2012.