Loom Speed Research Articles

Effects of Loom Speed, Insertion Air Pressure, and Yarn Type on Fabric Air Permeability: Case Study on Air Jet Loom

The air permeability of the fabric is affected by the type of yarn used, the loom speed, and the amount of air pressure delivered by the relay nozzles. In this study, 21 Ne of ring and rotor spun yarns were used as a weft in an air jet loom. Loom speed and left- and right-side relay nozzles pressure in a range of 400–600 RPM, 2–4 bar, and 3–6.5 bar, respectively, were taken as additional factors. To develop and analyze the experiment, a full factorial design was used. It was observed that the air permeability of rotor spun weft yarn fabric’s is greater than ring spun weft yarn fabrics. Furthermore, when the speed of the loom increased and the left- and right-side relay nozzles air pressure decreased, the fabric’s air permeability increased and vice versa.

Impacts of Yarn Hairiness and Voluminous on Weft Yarn Speed and Twist Loss in Air-Jet Weaving

ABSTRACT The velocity and twist loss of weft yarns in air-jet weft insertion is affected by the type of yarn used as a weft. In this work, ring- and rotor-spun yarns of 16Ne were used as weft yarns and velocity and twist loss differences between these yarns were investigated. The constant air pressures and loom speed were used to measure the velocity difference between the two yarns. For twist loss, the speed of the loom and relay nozzle pressures were varied in the range of (300–510 rpm loom speed, 2–4 bar left side relay nozzle air pressure (LSRNP) and 3–6.5 bar right-side relay nozzle air pressure (RSRNP). A full factorial design was used to design and analyze the results of the experiment for twist loss. It is observed that the average velocity (m/s) and twist loss (TPM) of the ring-spun yarns are higher than those of the rotor-spun yarns. Additionally, it has been found that for both types of yarn, the twist loss increases when the loom’s speed falls and the air pressure in the relay nozzles rises. However, the highest twist loss difference between the two yarns is observed at the highest speed of the loom.

Effect of Cotton/Polyester Blend Ratio, Loom Speed, and Air Pressure on Yarn Twist Loss and Yarn Strength Loss: The Case of Air-Jet Loom

ABSTRACT Production of high-quality woven fabric with uniform fabric properties is an essential requirement for manufacturers. But in air-jet weaving, some quality parameters of the fabric are affected by twist loss of weft yarn during weft insertion. The aim of this work is to show the effect of polyester/cotton (PC) blend ratio, loom speed, and air pressure on weft yarn twist loss and tensile properties of the fabrics produced by air-jet weaving machines. Box-Behnken design has been used to design and analyze the experiment. 27 fabric samples were on an air-jet loom with a combination of four factors each at three levels (loom speed (A) 300rpm, 425rpm, and 550rpm), left side relay nozzle pressure (LSRNP) (B) (2.5 bar,3.25 bar, and 4 bar), Right side relay nozzle pressure (RSRNP)(C) (3 bar, 4.75 bar, and 6.5 bar), cotton/polyester blend (D) 100%/0%, 75%/25%, and 50%/50%,). The results of the experiment revealed that PC blend ratio, loom speed, and air pressure affect the twist level and the strength of the yarn significantly. It is found that relay nozzle air pressure is directly proportional to the twist losses and weft yarn strength loss. But the PC blend ratio has a more significant impact on weft yarn twist loss and mechanical properties of the yarn.

Optimization of air pressure and speed of air jet loom; impact on fabric tensile and tear strength properties using Response Surface Methodology

ABSTRACT Weaving industries that use air jet loom are always emphasized to increase production and keep up the quality of woven fabric. But due to faulty mill practices or negligence, fabric mechanical properties of the fabric made on air jet loom are impaired. Improving the fabric quality can be achieved by improving work practices and optimization. The aim of this research is to optimize the air pressure and loom speed to produce a fabric with optimum mechanical properties and twist loss of weft yarn after weaving. To perform the experiment, three independent variables (loom speed, left-side relay nozzle pressure, and right-side relay nozzle pressure) was taken. With the combination of the three independent variables at five levels each, nineteen fabric samples were produced and each tensile and tear strength of the fabric in the weft direction were tested. Central composite design (CCD) was used to design the experiment, analyze the results of the experiment, and optimize the process. The results of the experiment show that variation in loom speed and air pressure affects twist of the weft yarn and mechanical properties of the fabric significantly and loom speed had a most significant effect on yarn twist loss, fabric tensile, and tear strength.

Predicting Yarn Breaks in Textile Fabrics: A Machine Learning Approach

In this paper, we propose a Machine Learning (ML) approach to predict faults that may occur during the production of fabrics and that often cause production downtime delays. We worked with a textile company that produces fabrics under the Industry 4.0 concept. In particular, we deal with a client customization requisite that impacts on production planning and scheduling, where there is a crucial need of limiting machine stoppage. Thus, the prediction of machine stops enables the manufacturer to react to such situation. If a specific loom is expected to have more breaks, several measures can be taken: slower loom speed, special attention by the operator, change in the used yarn, stronger sizing recipe, etc. The goal is to model three regression tasks related with the number of weft breaks, warp breaks, and yarn bursts. To reduce the modeling effort, we adopt several Automated Machine Learning (AutoML) tools (H2O, AutoGluon, AutoKeras), allowing us to compare distinct ML approaches: using a single (one model per task) and Multi-Target Regression (MTR); and using the direct output target or a logarithm transformed one. Several experiments were held by considering Internet of Things (IoT) historical data from a Portuguese textile company. Overall, the best results for the three tasks were obtained by the single-target approach with the H2O tool using logarithm transformed data, achieving an R2 of 0.73 for weft breaks. Furthermore, a Sensitivity Analysis eXplainable Artificial Intelligence (SA XAI) approach was executed over the selected H2OAutoML model, showing its potential value to extract useful explanatory knowledge for the analyzed textile domain.

Design of Multi-Line Elastic Belt Conveying Control System for Knitting Machine Based on I2C Protocol

In order to solve the problems of fixed speed, single-way conveying, conveying speed and loom speed mismatch of knitting machine elastic belt conveying device, a design scheme of multi-line elastic band conveying control system based on I2C (Inter-Integrated Circuit) communication is proposed. The scheme realizes the real-time communication between the control host and the PWM (Pulse Width Modulation) signal output slave through the I2C protocol communication of the master-slave MCU (Microcontroller Unit). The slave machine controls the stepper motor through the subdivision circuit and the drive circuit, and uses the stepping motor to speed up and down the differential. Algorithm and speed matching algorithm to realize multi-speed variable speed elastic belt conveyor control system with good speed matching. At the same time, because I2C protocol has easy scalability, it can realize multi-channel through bus analog communication and expansion between MCU I/O ports. delivery. Finally, by setting up simulation experiments, it is verified that the speed matching between the stepping motor and the knitting machine needle is better. When the stepping motor driver (TB6600) is 32 subdivided and the duty ratio of the PWM signal is 60%, the motor speed is stable, low vibration and noise. The system can play a positive role in improving fabric tightness, improving fabric production efficiency and adjusting fabric morphology.

An Analysis on Increasing the Loom Speed

An Analysis on Increasing the Loom Speed

Effect of Loom Speed on Warp Contraction Percentage of Cotton Fabric

Effect of Loom Speed on Warp Contraction Percentage of Cotton Fabric

Statistical Model for Predicting Compressed Air Consumption on Air-Jet Looms

Compressed air is a major component of energy costs incurred in the weaving of textile fabrics on air-jet looms. The consumption of compressed air in air-jet weaving depends on different process variables. In this study, the effect of weft yarn count, reed count, fabric width and loom speed on the compressed air consumption of air-jet loom was determined using response surface methodology. Fabric width was found to be the most dominant factor affecting the air consumption followed by loom speed, reed count, and weft yarn count respectively. A statistical model for predicting the compressed air consumption on air-jet loom was developed. The prediction ability and accuracy of the developed model was assessed by the fitted line plot between the predicted and actual air consumption values. The prediction model may be used for optimizing the production planning, estimating the share of compressed air cost in weaving a particular fabric style, and in identifying any air wastages in the weaving shed by comparing the actual compressed air consumption with that predicted by the model which was developed under controlled conditions without any air leakages.

Comparison of regression and adaptive neuro-fuzzy models for predicting the compressed air consumption in air-jet weaving

The aim of this study was to compare the response surface regression and adaptive neuro-fuzzy models for predicting the compressed air consumption in air jet weaving. The prediction models are based on the experimental data of 100 samples comprising weft yarn count, fabric width, loom speed and reed count as input variables and compressed air consumption as output/response variable. The models quantitatively characterize the linear and quadratic relationships as well as interactions between the input and output variables exhibiting very good prediction ability and accuracy, with ANFIS model being slightly better in performance than the regression model. The models could be used for estimating the compressed air consumption, identifying air leakages and production planning in a weaving mill.

Abrasion evaluation of spliced and parent yarns with a new simulator abrader tester

In order to evaluate the abrasion effect on both spliced and parent yarn performances, a newly developed abrader tester simulating the real cumulative weaving stresses is used. Three weaving parameters: loom speed, splice positions during weaving and yarn tension are tested to simulate the mechanical behaviour of spliced and parent thread yarns. The results show that the spliced yarn’s abrasion resistance, expressed by lifetime cycle numbers, is more affected by the weaving parameters used in our developed abrader simulator tester than by others. In this work, the results obtained by our simulator abrader tester and the cyclical tensioning ones are compared to regression analysis models. According to the highest coefficients of determination ranging from 0.955 to 0.999, it is found that a good prediction of spliced and parent yarn breakages is possible. Comparing two interesting splice positions on the loom: the splice beat-up position and the splice shedding one, we conclude that the splice shedding position increases breakage rate.

Fiber Fly Generation of 100% Acrylic Yarns during Weaving

At textile mills, the fiber fly generation is a big concern almost at every stages of the production including knitting and weaving operations. Therefore, it is not a surprise that the fiber fly generation is still getting the attention of many workers for decades for either production efficiencies or for health reasons. In this study, the fiber fly generation during the blanket weaving has been studied. Among all of fiber properties, the fiber mean length has the greatest effects on the amount of the fiber fly generated during the weaving processes. Additionally, loom speed and package conicity have also a significant effect on the fiber fly generations during the weaving of blanket fabrics. It was found that the open end yarns with high twist coefficients were generating the minimum amount of the fiber fly during the weaving while the woolen yarns were giving the higher fiber fly generation during the blanket weaving processes.

Fatigue Behavior of Filament Warp Yarns under Cyclic Loads during Weaving Process

Warp yarns in their different applications during weaving processes are often required to support loads, either in a static manner (simple tensile) or in a dynamic one (fatigue). For this reason, the investigation into the variations of the mechanical behavior of warp yarns during weaving condition is important. The purpose of this investigation was to simulate the cyclic loading of weaving process on filament warp yarns and report their fatigue behavior. In this study, the general characterization analysis of three types of the most ordinary filament yarns, polyester, polypropylene and nylon, was performed and then their fatigue behavior was simulated as warp yarns under cyclic loading by using the dynamic mechanical analyzer (DMA 2980). For this simulation, by looking at the conditions of the most common weaving looms, two sets of frequencies as loom speed and two sets of strains as loom geometry were chosen. The relevant variations of the yarn elongation, yarn stress, yarn storage modulus, yarn loss modulus and the damping factor of the yarns were measured and studied. Our test results revealed that the polypropylene yarns had the minimum change in their mechanical behavior and the nylon yarns had the minimum amount of characteristics under different loading conditions. It was found that the resistance of nylon to cyclic loads was higher than polyester and polypropylene. Also, polyester was the weakest yarn because of high change range in its mechanical and physical properties. We also demonstrated that only the polyester yarn revealed immediate failure at 2 % strain.

Analysis of Beat-up Force During Weaving

Instrumentation used by Bullerwell and Mohamed has been employed to measure the beat-up force on the Müller CKM 1 / 220 needle loom. An additional measuring system using strain gauges verifies the accuracy of the load washer. Both systems show close agreement in measuring beat-up force. The effects of different weaving parameters on beat-up force are also investigated. Experimental results reveal that when the har nesses are level, beat-up force shows a linear relationship with warp tension and with filling linear density, but an inverse relationship with pick spacing. Early shed timing causes an increase in beat-up force. An earlier theoretical model for the beat-up dy namics is verified. Both theoretical and experimental results show good agreement in relation to warp tension, pick spacing, shed timing, and loom speed.

Dynamic Analysis of the Beat-Up Process

This paper develops a dynamic analysis method for the beat-up process. Theoretical predictions of beat-up force and warp tension response during beat-up are made by setting up a weaving model under dynamic conditions. Weaving machine and fabric parameters, static and kinematic coefficient and index of friction between the warp and filling yams, total harness lift, shedding timing, back rest position, basic warp tension, and loom speed have been taken into account in predicting beat-up force and warp tension.

Measuring Beat-up Force on a Water Jet Loom

Methods are described for measuring the beat-up force on a water jet loom and the dynamic calibration of the force transducer. Experimental results show that the warm- up time, loom speed, and shed timing have no effect on beat-up force, while the pick spacing and linear density of the filling yam have a considerable effect on the maximum beat-up force and the shape of the beat-up pulse.

Theoretical Investigations of Beat-Up

A theoretical prediction of beat-up force and the filling yarn response to the beat- up motion taking place during weaving are made by setting up a weaving model under static and dynamic conditions. Pick-spacing, the coefficient of friction between the warp and the filling, the basic warp tensions and the ratio of tension in the warp sheets, loom speed, and shed timing are the key factors affecting the beat-up force and filling motion during beat-up.

Filling Insertion by Rapier: A Kinematic Model

A model of rapier filling insertion, using two half-width rapiers and end transfer, is proposed and its implications analyzed. Normalized forms of the critical characteristics that impose constraints on the system are evaluated. In particular, filling pickup velocity and the maximum velocity and maximum acceleration of the rapier are considered. The effects are examined of the parameters of the model, and of the form of generating function used to specify the rapier motion, on these normalized characteristics. The influence of the critical characteristics on the relation between working width and loom speed is then considered. The forms of width-speed relation implied by the limiting values of the critical characteristics are determined and compared with the form of this relation in practice.

Variation of Shuttle-flight Conditions with Loom Speeds

The flight conditions of the shuttle have a considerable effect on the loom efficiency and the quality of the fabric woven. Hence the shuttle oust be adjusted to fly smoothly as well as precisely in its passage through the loom. In this paper, the flight conditions of the shuttle are discussed in relation to an increased loom speed.

Composition of Weave-Room Dust

Total-dust samples were collected at four weave-room sites and one card room site in each of twelve southeastern U.S. cotton mills. The cotton content of the fabrics being produced ranged from 35% to 100%. Sizings were starch, polyvinyl alcohol (PVA), carboxymethylcellulose (CMC), and mixtures of starch PVA, starch CMC, and PVA CMC. A serial solvent extraction-gravimetric technique was developed for proximate analysis of samples. Sizing was extracted with boiling water. Iodometric methods were used to determine the extracted starch and PVA, and CMC was determined by titration of the free acid with NaOH. Weaving dust averaged 20-50% sizing, 10-30% cellulose, 0.4% synthetic fiber, and 1-4% protein. Higher total dust levels were'associated with starch sizing, increased loom speeds, and higher yarn counts. Fine dust levels increased with loom speed percentage of cotton in the product, and the use of starch as sizing. The major differences between carding and weaving dusts were the presence of sizing and the much higher average water solubility of weaving dust, 47% vs. 10%. The carding dust also contained small amounts of starch (1-2%) and protein (9-16%), plus traces of polyester in dust from card rooms in which synthetic was carded or blended simultaneously.