Drawing Frame Research Articles

Spinning of Staple Hybrid Yarn from Carbon Fiber Wastes for Lightweight Constructions

The reuse of CF-wastes (rCF) is desirable due to the energy-intensive manufacturing, high price and the disposal problem of carbon fibers. It is a challenging process to spin yarn from rCFs in a short staple spinning production line which ensures a much higher strength later in the manufacturing of CFRP (carbon fiber reinforced plastics) parts than that of the parts from rCF-nonwovens or, from short-fiber reinforced injection molded parts. This spinning technology consists of several subsequent processes such as carding, drafting and spinning on a flyer frame. It is possible to produce hybrid yarn up to 2000 tex, which fineness is similar like a roving. The machines used to produce yarn for this purpose were specially modified and adapted, so that the brittle CF can be processed smoothly. Carded and draw frame slivers with different fiber lengths and mixing ratios were produced and later the high-quality hybrid yarn has been spun with different yarn twists.

Study of drafting force variability and sliver irregularity at the break draft zone of a draw frame

To produce an evener fiber assembly, it is important to understand fiber dynamic behavior during the drafting process. Drafting force and its variability is an alternative approach to understand the fiber’s velocity–friction characteristics, representing a combined effect of multiple fiber properties. In this study, online drafting force and its variability was measured with different break draft ratios and back roller gauges to analyze its effect on sliver short-term evenness. Drafting force variability well correlated with sliver evenness with correlation coefficient R2 = 0.81. The coefficient of variation (CV%) of drafting force was highest (2.3%) at low break draft 1.1–1.2, and then reduced gradually to its minimum value (1.5%) around a break draft of 1.6–1.7. The minimum variability of drafting force well corresponds with lower irregularity of sliver at certain break draft ratios. This indicates that a stable drafting force promises better fiber distribution along the sliver length. The variability of drafting force and sliver irregularity also increased as the back gauge increased from 43 to 51 mm. Furthermore, the impact of short fiber content on the drafting force was investigated at three back gauges. The increase in short fiber content gives higher magnitude of drafting force. Drafting force was also compared with the number of neps and change in fiber length in sliver for each break draft. Better nep opening and improved fiber lengths were also found around (1.6–1.7) break draft and follow the same trend of variability of drafting force as the break draft changed.

The Parametric Design of Pulley Based on AutoCAD

This design mainly takes pulley as the research object. First collect the data of pulley, bring round the body of the reference point, design the User DCL dialog, then preparing Auto Lisp diver. The procedure involves drawing frame, title bar, shape, tolerance and coarse and so on the surface, generated by the input parameter , you can take the implementation of parts of the system

Employment of PROMETHEE approach for selecting suitable yarn for weft knitting process considering drawing frame variables

The improvement of yarn properties is an obligatory but a difficult task to get a quality product and to enhance efficiency of production processes. For this purpose it is necessary to create a close compatibility between yarn characteristics and subsequent processes requirements. A survey of the literature will reveal that, there are various researches in which statistical approaches have been employed to introduce appropriate yarn quality parameters in accordance with the requirements of next processes. But, mentioned analysis is a multi-criteria decision making where the differences between the values of the yarn parameters and preferences of the producer about yarn characteristics to get a product with defined properties should be considered. However, this goal can not be achieved by using statistical methods. Therefore, this paper makes an attempt to apply preference ranking organization method for enrichment evaluations (PROMETHEE) for the first time in the field of textile science in selecting suitable drawing frame variables for 30 Ne rotor spun yarn intended to be used for weft knitting process. The performances of three variables in a drawing frame were evaluated based on seven quality parameters of forty eight rotor spun yarns using this algorithm. Final ranking was elicited in accordance with PROMETHEE method. Consequently, sensitivity analysis was conducted to assess the stability of the proposed final ranking.

Yarn Strength Modelling Using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Gene Expression Programming (GEP)

This study compares capabilities of two different modelling methodologies for predicting breaking strength of rotor spun yarns. Forty eight yarn samples were produced considering variations in three drawing frame parameters namely break draft, delivery speed, and distance between back and middle rolls. Several topologies with different architectures were trained to get the best adaptive neuro-fuzzy inference system (ANFIS) and gene expression programming (GEP) models. Prediction performance of the GEP model was compared with that of ANFIS using root mean square error (RMSE) and correlation coefficient (R2-Value) parameters on the test data. Results show that, the GEP model has a significant priority over the ANFIS model in term of prediction accuracy. The correlation coefficient (R2-value) and root mean square error for the GEP model were 0.87 and 0.35 respectively, while these parameters were 0.48 and 0.53 for the ANFIS model. Also, a mathematical formula was developed with high degree of accuracy using GEP algorithm to predict the breaking strength of the yarns. This advantage is not accessible in the ANFIS model.

An Embedded Auto-leveling System based on ARM and FPGA

A kind of embedded auto-leveling control system based on ARM and FPGA is proposed in this article. According to the mechanical structure and the control requirements of high speed drawing frame, the system combines the precision and high frequency of ARM with the internal logic configuration of FPGA. The control algorithm, hardware structure and software structure are discussed in the paper. This method not only allows for quicker and easier developing work bur also enhances the flexibility of the controller. The experiments validate the feasibility of system and clearly show that the presented approach is effective to reduce the sliver unevenness. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.3741

Optimizing sliver quality using Artificial Neural Networks in ring spinning

Sliver evenness is a very important parameter affecting the quality of the yarn produced. Therefore, controlling the sliver evenness is of major importance. Auto-levelers mounted on modern Drawing Frames should be accurately adjusted to help to achieve this task. The Leveling Action Point (LAP) is one of the important auto-leveling parameters which highly influence the evenness of the slivers produced. Its adjustment is therefore of a crucial importance. In this research work, Artificial Neural Networks are applied to predict the optimum value of the LAP under different productions and material conditions. Five models are developed and tested for their ability to predict the optimum value of the LAP from the most influencing fiber and process parameters. As a final step, a statistical multiple regression model was developed to conduct a comparison between the performance of the developed Artificial Neural Network model and the currently applied statistical techniques.

Properties of Jute Blended Yarns Spun on Ring Spinning System

The chemical modified jute fibres were spun into jute/cotton blended yarns by using of two different blending methods (the fibre blending and the sliver blending) on ring spinning system. The tensile, hairiness, Uster evenness properties of two kinds of blended yarns with different blend ratios and yarn counts were investigated in this paper. It was found that the tensile, hairiness index, mass irregularity and imperfections of blended yarn depended on amount of jute fibres in blends. The draw frame blended yarns processed the better quality than that of intimate blended yarns.

Impact of Carding Parameters and Draw Frame Doubling on the Properties of Ring Spun Yarn

The impact of card cylinder speed, card production rate and draw frame doubling on cotton yarn quality parameters was investigated by using the Box-Behnken experimental design. It was found that yarn tenacity, elongation and hairiness increase by increasing the number of draw frame doubling up to a certain level and then decrease by further increase in doubling. Yarn unevenness increased by increasing card production rate and total yarn imperfections increased by decreasing card cylinder speed and increasing card production rate.

Spinning preparation parameters selection for rotor spun knitted fabric using VIKOR method of multicriteria decision-making

Selection of spinning preparation parameters which affects properties of the final yarn and subsequent process is a multicriteria decision-making problem. Different statistical methods and multicriteria approaches have been used to solve such kind of problems. This paper presents a new multicriteria decision-making technique to select the suitable drawing frame parameters for 30Ne rotor spun yarn intended to be used for weft knitting process. Three important variables in drawing frame including distance between back and middle rolls, delivery speed, and break draft were considered. Their performances were evaluated on the basis of seven quality parameters of the 48 rotor spun yarns using VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. The final ranking of the parameters was elicited in accordance with this procedure. Consequently, the stability of the proposed final ranking was verified after sensitivity analysis.

The Effect of the Sliver Fiber Configuration on the Cotton Inter-fiber Frictional Forces

Fiber surface properties have a significant effect on yarn spinning. The frictional behavior of fibers greatly influences their processing, their performance and the performance of the final product. In order to investigate the effect of fiber surface properties and inter-fiber friction during spinning process, card slivers are taken and subjected to three drawing passages. Card and drawing frame slivers are then tested by the Static Friction Tester (SFT), which has been developed earlier. Fiber fineness, maturity and fiber length are measured by using different testing instruments. Hook content is calculated by utilizing fiber length data. The statistical analysis of results shows the same trend for the different cotton fibers tested.

An Intelligent Model to Predict Breaking Strength of Rotor Spun Yarns Using Gene Expression Programming

Exploring relationships between characteristics of a yarn and influencing factors is momentous subject to optimize the selection of the variables. Different modelling methodologies have been used to predict spun yarn properties. Developing a prediction approach with higher degree of precision is a subject that has received attention by the researchers. In the last decade, Artificial Neural Network (ANN) has been developed successfully for textile nonlinear processes. In spite of the precision, ANN is a black box and does not indicate inter-relationship between input and output parameters. Hence, Gene Expression Programming (GEP) is presented here as an intelligent algorithm to predict breaking strength of rotor spun yarns based on draw frame parameters as one of the most important stages in spinning line. Forty eight samples were produced and different models were evaluated. Prediction performance of the GEP was compared with that of ANN using Mean Square Error (MSE) and correlation coefficient (R2-Value) parameters on test data. The results showed a better capability of the GEP model in comparison to the ANN model. The R2-value and MSE were 97% and 0.071 respectively which means desirable predictive power of GEP algorithm. Finally, an equation was extracted to predict breaking strength of the yarns with a high degree of accuracy using GEP algorithm.

The Method and Technique of 2D Drawing Creation Based on NX7.5

The method and technique of the 3D model transformation for 2D engineering drawing using NX7.5 was studied. The key points of GC china toolkits, method of master model and pattern were introduced. The GC china toolkits produced convenient way to custom drawing standard to match China standard through some simple operation. The method of master model realized the relativity between 3D model and 2D drawing. The pattern was an effective method to add drawing frame and title bar to sheets. In the end, the process of 2D engineering graphics creation was expatiated. The practice case proves that the drawing efficiency is improved greatly by NX7.5 application.

Development of prediction system using artificial neural networks for the optimization of spinning process

This article correlates draw frame settings with quality characteristics of sliver and ring spun yarn using artificial neural networks. Considering the importance of draw frame as the last quality improvement machine in the spinning process, the quality influencing parameters of the draw frame were used as input for artificial neural networks. The neural networks were trained using a combination of Levenberg-Marquardt algorithm and Bayesian regularization for better generalization of the networks. Cross validation was performed for each trained network to test the performance of networks. The promising results achieved by this research work emphasize the ability of neural networks to predict the quality characteristics of sliver and yarn using the artificial neural networks. Therefore, draw frame parameters can be adjusted on the basis of required sliver and yarn quality. Furthermore, machines can be involved in the decision making process in spinning mills.

The influence of processing parameters on the structural and mechanical properties of drawn polypropylene fibres: A factorial design approach

AbstractThis article reports a study of multi‐stage polypropylene fiber drawing (stretching) as a continuous, but independent stage of the overall fiber‐forming process. The fibers were drawn according to a factorial experimental design, once appropriate spinning conditions had been devised. The structures of the drawn fibers were studied using wide‐angle X‐ray diffraction and birefringence measurements. In addition, the fibers were characterized with respect to filament tenacity, elongation to break, specific secant modulus, and extent of shrinkage at 130°C. All these properties were quantitatively assessed as responses to nine specially selected process control parameters in the drawing equipment. For every property analyzed, the temperatures of the hot plates in the draw frame were found to exert no significant influence, whereas the temperatures of the initial rollers were in most cases significant. Furthermore, the speed of the final roller also played an influential role, and a number of interactions between process parameters were identified as significant. Explanations are advanced for the parts played by significant process parameters on the properties of the drawn fibers. The article also demonstrates the advantages of factorial experimental design in determining correct settings for process parameters to give drawn fibers with the properties desired. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012

Processing parameters optimization of draw frame for rotor spun yarn strength using gene expression programming (GEP)

Breaking strength is one of the most important mechanical property of a yarn as it is the main parameter for quality control. This property depends on many different factors namely, raw material factors, process variables and machine parameters. Since, there is a high degree of interaction between yarn properties and influencing factors therefore, optimal processing conditions can not be determined easily. This article proposes prediction approach for the determination of the breaking strength of the yarn using gene expression programming (GEP) and optimization technique using MATLAB software. A nonlinear mathematical function was derived on the basis of draw frame variables that were distance between back and middle rolls, delivery speed and break draft by GEP. Afterward, optimal conditions were found in such a way that breaking strength to be maximized. Study showed that, optimal processing parameters including distance between back and middle rolls, break draft and delivery speed were respectively, 10.70 mm, 1.90 and 541.51 m/min (687.95 or 721.32 based on the optimization procedure).

Study on New Drafting Form of Comber

With analysis of development tendency of domestic and abroad high-speed combers, in this paper we proposed a new drafting form to comber--three over three curvilinear draft under pressure bar combining with development and successful experience for high-speed drawing frame. Moreover, combing experiment in this new drafting form was performed on basis of theoretical analysis and calculation. The results showed that this new type of drafting form satisfied the users’ demand for high-speed as well as the comber’s qualification.

Intelligent Settings Using Artificial Intelligence at Auto-leveling Drawing Frame

The optimization of a process requires exact knowledge of the process, which is knowledge of correlations and inter-dependence between the process-determining variables and the knowledge over the actual condition of the process. In a data rich knowledge poor process like spinning, where the exact relationships between machine, material, climate and quality are yet to be concluded objectively, this research focuses on the use of artificial neural networks as a tool to find out the correlations between decisive variables and to determine the optimum settings. Drawing frame is considered to be the last fault correction point in spinning preparation chain, therefore, its settings has a vital role to play towards yarn quality. Leveling action point is one of the important auto-leveling settings involving an automatic search function at Rieter drawing frame RSB-D40 and requiring a large amount of sliver. In this study, attempts were made to optimize the leveling action point. Optimization of draft settings is also within the scope of this article. The ANNs were used to achieve such objectives and they were found to be very helpful in identifying the optimum settings and hence decreasing material loss and improving sliver quality.

Study on drafting force and sliver irregularity on drawing frame

A new device was designed and constructed on drafting frame to measure the dynamic force during roller drafting. The effects of draft ratio, number of input slivers, and roller velocity on drafting force, coefficient of variation (CV) of drafting force, and the irregularity of output slivers were all analyzed. Rayon and cotton slivers were used in the experiments, respectively, the results showed that the number of input slivers had a significant linear relation with the mean drafting force; the draft ratio had an obvious effect on mean drafting force and CV of drafting force; the lower CV of drafting force promised better output sliver evenness.

Drawing Graphs via Kaleidoscopes

Graph drawing problems can be applied to many reality places, which also deduce to some important graph drawing problems. Such as aesthetics criteria whose optimization can lead to acceptable drawings. This paper gives an algorithm for optimizing these criteria. We propose a new force-directed model to solve the graph drawing problems in 2-D frames and modify this hybrid force model to promote to normal drawing frame shape, especially regular triangle and circle drawing frames. For the regular triangle drawing frame, it can be applied to tree drawing problems and for the circle drawing frame shape we use it to suit the normal graph drawing problems. © 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of ESEP 2011