Authors: Vinay Kumar Midha V K Kothari R Chattopadhyay A Mukhopadhyay
Publish Date: 2010/09/11
Volume: 11, Issue: 4, Pages: 661-668
Abstract
In this paper artificial neural network ANN model has been designed to predict the strength loss in threads during high speed industrial sewing Four different types of threads Mercerized cotton polyester staple spun polyestercotton core spun and polyesterpolyester core spun were taken for the study The other input parameters include thread linear density fabric area density number of fabric layers stitch density and needle size In order to reduce the dependency of the results on a specific partition of the data into training and testing sets a fourway cross validation tests were performed ie total data was divided into training and testing set in four different ways The predicted tenacity loss was correlated to the experimental tenacity loss and correlation coefficient between the actual and predicted tenacity loss obtained It was observed that the neural network system is able to predict the tenacity loss of threads after sewing with good correlation and less average error The relative contribution of each parameter to the overall prediction of the tenacity loss was studied by carrying out the sensitivity analysis of the test data set The results of sensitivity analysis show that thread type is the most important input parameter followed by thread linear density number of fabric layers fabric area density needle size and the stitch density
Keywords: