Schemes Selection of Yarn Tension Detection and Control Based on Fuzzy Multiple Attribute Group Decision Making

Abstract

To evaluate the yarn tension detection and control schemes in rapier looms, a fuzzy multiple-attribute group decision making problem is proposed for the schemes selection. Firstly, important degrees of every attributes from each expert are considered. The individual opinions of each expert are integrated with the similarity of the decision group. And the synthesized weights of each expert are calculated. Secondly, with the aggregation of experts opinions, the group attribute-weights matrixes are obtained. Then the fuzzy TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) is used to sequence the alternatives, and the optimal scheme is decided for yarn tension detection and control system, the decision results illustrate the feasibility and effectiveness of the developed method.