JOURNAL OF TEXTILE RESEARCH ›› 2018, Vol. 39 ›› Issue (06): 149-154.doi: 10.13475/j.fzxb.20170601706

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Application of decision tree algorithm in quality management of knitting products

  

  • Received:2017-06-05 Revised:2018-03-05 Online:2018-06-15 Published:2018-06-15

Abstract:

In order to solve the problem of the conventional product quality management methods of knitting enterprise of only focusing on post-processing, lack of scientific pre-management measures. Using the decision tree C5.0 algorithm, a variety of dey factors influencing quality,such as raw materials, raw material quality level, products, equipment types, environment temperature and humidity, blockers, shifts, were discussed. The knitting product quality data mining model was established. By using this model, the data mining of 8 157 quality data of a company after filtering processing was carried out, the results show that the order of influence on the quality of the grey fabric is (from high to low):raw materials, raw material quality level, equipment models, environment temperature and huimidity, shifts, blockers and products. Based on this result, the exact distribution of production factors is given to hilp knitting enterprises optimize the resources allocation to improve the product quality.

Key words: knitted product, quality management, decision tree algorithm, production factor

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