Development of Prediction model through linear multiple regression

Embroidery through computer aided semi-automatic machines is one of the most widely used option for the surface ornamentation of apparel fabrics at present. Since the embroidery process include addition of embroidery threads depending upon the design motif, it is quite obvious that basic physical and functional properties of fabric are subject to change. It is therefore important to develop an algorithm or empirical equation for proper prediction of the properties of the embroidered fabric, relevant to its required end use in apparel industry. In this context, an efort has been made to determine a prediction equation through linear multiple re gressions for the prediction of longitudinal stifness of embroidered fabric in terms of fexural rigidity in warp direction of the base fabric, considering the input parameters as warp-way fexural rigidity of the base fabric, breaking load and linear density of the embroidery thread, stit ch density, average stitch length and average stitch angle of the embroidery design. The fnal Prediction model is statisticall verifed taking new embroidery sam-ples of diferent varieties. It is found that the model can predict with a very satisfactory level of accuracy. Also, the infuences of the embroidery parameters in this context have been analyzed through the corresponding re -gression coefcients and the three dimensional (3D) surface curves..Stitch density has been on emerged as the most infuential parameter, followed by the stitch length and the stitch angle.