• The Research Journal of the Costume Culture
• /
• v.21 no.6
• /
• pp.967-973
• /
• 2013

During high speed sewing, the needle thread is exposed to dynamic loading, short strike loading, inertia forces, friction, rubbing, force of check spring, bending, pressure, friction, impact, shock and thermal influence. The dynamic thread loading/tension alters throughout the stitch formation cycle and along its passage through the machine. The greatest tensile force occurs at the moment of stitch stretching, when the take up lever pulls for required thread length through the tension regulator. These stresses act on the thread repeatedly and the thread passes 50-80 times through the fabric, the needle eye and the bobbin case mechanism, before getting incorporated into the seam, which result in upto 40% loss in tensile strength of the sewing thread. This damage in the sewing thread adversely affects its processing and functional performance. In this paper, the contribution of dynamic loading, passage through needle and fabric, and bobbin thread interaction in the loss in tensile properties has been studied. It is observed that the loss in tensile properties occurs mainly due to the bobbin thread interaction. Dynamic loading due to the action of take up lever also causes substantial loss in tenacity and breaking elongation of cotton threads.

• International Journal of Control, Automation, and Systems
• /
• v.2 no.1
• /
• pp.83-91
• /
• 2004

The purpose of this paper is to obtain an accurate nonlinear system model to test various control schemes for a motion control system that requires high speed, robustness and accuracy. An industrial sewing machine equipped with a Brushless DC motor is considered. It is modeled by a neural network that is configured as an output-error dynamical system. The identified model is essentially a one step ahead prediction structure in which past inputs and outputs are used to calculate the current output. Using the model, a 2 degree-of-freedom PID controller to compensate the effects of disturbance without degrading tracking performance has been de-signed. In this experiment, it is not preferable for safety reasons to tune the controller online on the actual machinery. Experimental results confirm that the model is a good approximation of sewing machine dynamics and that the proposed control methodology is effective.