2013
DOI: 10.1080/00405000.2013.812552
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Application of data mining technique in predicting worsted spun yarn quality

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Cited by 17 publications
(8 citation statements)
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“…However, a decrease in crimp percentage and float length was observed. Mozafary et al proposed a combined approach, where they used K-means algorithm for data clustering and ANNs for defects detection i.e., yarn unevenness [ 31 ]. The feedforward ANN and Levenberg–Marquardt training function of back propagation were applied in this method and the effectiveness was demonstrated by a comparative analysis with standard ANN results.…”
Section: Classification Based On Textile Processesmentioning
confidence: 99%
“…However, a decrease in crimp percentage and float length was observed. Mozafary et al proposed a combined approach, where they used K-means algorithm for data clustering and ANNs for defects detection i.e., yarn unevenness [ 31 ]. The feedforward ANN and Levenberg–Marquardt training function of back propagation were applied in this method and the effectiveness was demonstrated by a comparative analysis with standard ANN results.…”
Section: Classification Based On Textile Processesmentioning
confidence: 99%
“…Automation technologies can be utilized in several parts of this productive process. In particular, a large amount of data is created and stored, such as the properties of each yarn (e.g., color, thickness), the configuration of each machine used in the creation process (e.g., spinning, weaving) (Mozafary and Payvandy, 2014), and the results of the specific tests that the company executes. All these data can be processed by Data Mining (DM) and Machine Learning (ML) methods, allowing the discovery of valuable knowledge in order to improve the textile manufacturing process (Yildirim et al, 2018).…”
Section: Introductionmentioning
confidence: 99%
“…This device is costly and therefore hardly available for small-scale companies. To reduce the quality measurement cost of businesses, Mozafary and Payvandy 12 have used artificial neural network method to predict the worsted yarn quality. Yildiz et al 13 have made breaking elongation and sewing strength modeling for yarns by using the artificial neural network method.…”
Section: Introductionmentioning
confidence: 99%