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 includes addition of certain amount 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 effort has been made to determine a prediction equation through linear multiple regressions for the prediction of longitudinal stiffness of embroidered fabric in terms of flexural rigidity in warp direction of the base fabric, considering the input parameters as warp-way flexural rigidity of the base fabric, breaking load and linear density of the embroidery thread, stitch density, average stitch length and average stitch angle of the embroidery design. The final Prediction model is statistically verified taking new embroidery samples of different varieties. It is found that the model can predict with a very satisfactory level of accuracy. Also, the influences of the embroidery parameters in this context have been analyzed through the corresponding regression coefficients and the three dimensional (3D) surface curves. Stitch density has been emerged as the most influential parameter, followed by the stitch length and the stitch angle.

中文翻译：

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线性多元回归预测模型在绣花织物纵向刚度预测中的应用

通过计算机辅助半自动机器进行的刺绣是目前用于服装织物表面装饰的最广泛使用的选择之一。由于绣花过程包括根据设计图案增加一定数量的绣花线，因此很明显，织物的基本物理和功能特性会发生变化。因此，重要的是要开发一种算法或经验方程式，以正确预测绣花织物的性能，使其与服装工业中所需的最终用途有关。在这种情况下，已经努力通过线性多元回归来确定用于预测绣花织物的纵向刚度的预测方程，该预测方程式是根据在基布的经纱方向上的抗弯刚度来进行的，考虑输入参数，如基布的经向弯曲刚度，绣花线的断裂载荷和线密度，绣花设计的针迹密度，平均针迹长度和平均针迹角度。最终的预测模型经过统计验证，采用了不同品种的新绣花样本。发现该模型可以非常令人满意的精度进行预测。此外，已经通过相应的回归系数和三维（3D）表面曲线分析了绣花参数在此情况下的影响。针迹密度已成为最有影响力的参数，其次是针迹长度和针迹角度。绣花设计的平均针迹长度和平均针迹角度。最终的预测模型经过统计验证，采用了不同品种的新绣花样本。发现该模型可以非常令人满意的精度进行预测。此外，已经通过相应的回归系数和三维（3D）表面曲线分析了绣花参数在此情况下的影响。针迹密度已成为最有影响力的参数，其次是针迹长度和针迹角度。绣花设计的平均针迹长度和平均针迹角度。最终的预测模型经过统计验证，采用了不同品种的新绣花样本。发现该模型可以非常令人满意的精度进行预测。此外，已经通过相应的回归系数和三维（3D）表面曲线分析了绣花参数在此情况下的影响。针迹密度已成为最有影响力的参数，其次是针迹长度和针迹角度。通过相应的回归系数和三维（3D）表面曲线分析了绣花参数在此情况下的影响。针迹密度已成为最有影响力的参数，其次是针迹长度和针迹角度。通过相应的回归系数和三维（3D）表面曲线分析了绣花参数在此情况下的影响。针迹密度已成为最有影响力的参数，其次是针迹长度和针迹角度。