An intelligent approach to integration of textile processes

This paper introduces a methodology to integrate effectively major plant processes with strong couplings between them. The proposed integration philosophy decides upon control setpoints for the individual processes by optimizing a global objective function which aims at improving process yield. A neuro-fuzzy model and a fuzzy objective function are employed to address the integration task. Such models and objective functions are defined and developed using experimental data or an operator's experience. The objective is to maximize productivity and, at the same time, reduce defects in each of the subsequent operations. A textile plant is considered as a testbed and three processes-warping, slashing and weaving-are employed to illustrate the feasibility of the approach. The supervisory level of the control architecture is intended to continuously improve the control set points depending upon feedback information from the weave room, slasher operator and warping data.