Predictive Modeling of Yarn Quality at Ring Spinning Machine using Resilient Back Propagation Neural Networks

Abstract

The final attenuation and twisting of fiber take place at ring spinning machine and hence its optimized performance is very crucial in terms of yarn quality. Drafting at ring spinning machine has a decisive effect on quality. There exist many influencing parameters in the spinning geometry that have to be optimized for manufacturing of quality yarn. The present research work was carried out to develop the Artificial neural networks (ANN) based prediction model for the polyester/cotton blended ring spun yarns by using these influencing parameters as inputs. ANN prediction model was developed using resilient backpropogation algorithm. Yarn quality parameters like yarn evenness, hairiness and tensile parameters were predicted. The low mean absolute error values for the yarn quality parameters proved that it is possible to predict the yarn quality on the basis of spinning geometry for cotton/polyester blended ring spun yarns using Resilient Back Propogation Neural Networks.

Assessing the Impact of Spacer Size Variations on the Ring-Spun Yarn Quality Ranking

“…All nodes and arrows compose this arrangement. These nodes denote the elements or variables within investigations, whereas indicators demonstrate how a particular factor influences another [30].…”

“…Second, it may not represent complicated systems with interactions that are not linear or fluctuating behaviours. Finally, this technique lacks quantifiable measurements, which may limit its utility in statistical evaluation or accurate quantity assessment [30].…”

“…Among this topic, the study on the drafting zones and its various aspects, such as spacer size and additional drafting pressure-related topics, are also on their favourite list. Those studies include finding out the effect of spacer size by predictive modelling, the impact of dynamic pressure exerted by the optimum choice of the spacer on the quality of 17.8 tex blended yarn, study on the effect of knitted fabric-produced yarn in case of pin type spacer and impact of pressure variation due to spacer size for the production of 100% cotton carded yarn [24,28,29]. Some other studies are performed using ISM methodologies, such as predicting the ranking of the yarn quality parameters by using varied bottom apron tension positions; some other related fields, like ISM, for identifying the influential factors for a sustainable panorama, identification of significant barriers for the implementation of the sustainable supply chain, ISM for identifying CSR factors in the Indian construction industry [35][36][37][38].…”

Study of sliver irregularity caused by fiber acceleration motion during the drafting process

“…As an indispensable procedure during the yarn manufacturing process, the drafting process has an appreciable effect on sliver unevenness. [1][2][3][4][5][6] Currently, considerable efforts had been committed to study the influence of the drafting process on sliver irregularity. Balasubramanian and Bhatnagar, 7 Graham and Bragg, 8 Siddiqui et al 9 and Qian and Yu 10 studied the effect of the drafting parameters on the drafting efficiency by analyzing the influence of the drafting force experimentally.…”

“…As an indispensable procedure during the yarn manufacturing process, the drafting process has an appreciable effect on sliver unevenness. 1–6 Currently, considerable efforts had been committed to study the influence of the drafting process on sliver irregularity. Balasubramanian and Bhatnagar, 7 Graham and Bragg, 8 Siddiqui et al.…”