Today’s industry gives first priority to information technology. Since understanding the structures and relationships dominated of data can help industrial managers to attend in competitive market successfully, a special mechanism must be developed to process data stored in a system. Hence, the focus on widespread use of data mining gains increasing attention. The purpose of this paper is using data-mining technique in textile industry. More than 150,000 data includes testing of raw materials, manufacturing process parameters and yarn quality parameters, during one year in worsted spinning factory were collected. Next, yarn quality was predicted by using data-mining methods containing clustering and artificial neural network (ANN). In order to evaluate the proposed method, the results obtained were compared with conventional methods based on ANN. The results showed that the performance of data-mining technique is more accurate than that of ANN.

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