Prediction model of sewing needle size based on grey relevant analysis

The prediction model of sewing needle size was developed by using gray system theory. 45 kinds of different fabrics were selected and their mechanical properties were measured by KES instrument. The size of sewing needle for each kind of apparel fabrics was chosen by the experienced technicians in a garment factory and sewing experiment was conducted for confirming its correctness. Grey relevancy between fabric mechanical property indexes and sewing needle size was analyzed and the parameters were screened and selected based on the degree of relevancy for prediction model. The precision of the model developed on the parameters with the relevant degree more than 0.90 was superior to that on all parameters. The results showed that the application of grey relevant analysis was valid. The average error was 5.61%.