Dyeing Machines Research Articles

Design and optimization of annular gap in a nozzle for dyeing machines

The annular nozzle is an important part of the dyeing machine as its impact and traction performance directly affect the quality and efficiency of dyeing. The annular gap forms the core of the nozzle. In this paper, the performance differences between six nozzles with different annular gap shapes were analyzed under various conditions using numerical simulation. The results indicate that the performance of the cone straight nozzle is more stable than other nozzle shapes under various conditions. To further enhance the performance of the nozzle, a multi-objective optimization of the cone straight nozzle structure was performed using a backpropagation neural network and a non-dominated sorting genetic algorithm, thereby obtaining the optimal combination of structural parameters. Finally, the optimization results were verified via experiments and numerical simulations. The results show that the pulling force of the optimized cone straight nozzle is more than 10% higher than that before optimization.

Integration of Local Wisdom of Natural Color Sasirangan in Project-based Learning with STEAM Approach to train Science Literacy

<span lang="EN-US">Science learning should provide meaningful experiences for students to understand various scientific phenomena in life. Integrating local wisdom in learning can improve scientific literacy because the various concepts learned are witnessed directly by students in life. This research uses theoretical studies to describe the integration of local wisdom of natural color sasirangan in project-based learning with the STEAM approach to improve science literacy.</span><span lang="EN-US"> The STEAM approach is in the form of a) science in the form of the phenomenon of abundant dye water from the pot due to expansion; b) technology in the form of sasirangan fabric dyeing machines; c) engineering in the form of manipulation of the use of natural dyes and fixation; d) art in the form of making sasirangan cloth motifs; e) Mathematics in the form of temperature measurement using a thermometer and heat to increase the temperature of the dye liquid. The stage of making sasirangan cloth consists of making patterns, jalujur, sisit, dye, dedel, washing and ironing. The concept of temperature and heat found in the process of making natural color sasirangan includes; a) the concept of temperature when cooked water slowly becomes hot; b) the concept of expansion on the phenomenon of natural dye water spilling from the pot when cooked; c) the concept of heat is seen in water that has a large mass requires more heat to achieve a certain temperature increase; d) The concept of radiant heat transfer can be proven when the sasirangan cloth is dried in the sun</span>

An efficient lexicographic approach to solve multi-objective multi-port fabric dyeing machine planning problem

In this study, the fabric dyeing process in a towel manufacturing factory is investigated, focusing on the batching of towel fabric bolts with different quantities and features belonging to different orders in multi-port dyeing machines. This research differs from previous studies in several aspects. Firstly, it is considered three different objectives: total tardiness, total number of washes (sequence-dependent setups), and total machine fixed cost. These objectives have not been simultaneously optimized in previous studies, making our approach unique. Secondly, we adopt a lexicographic optimization approach to prioritize these objectives according to the company’s requirements. This allows to find solutions that are optimal in terms of one objective while satisfying the constraints imposed by the other objectives. Lastly, it is proposed a novel lexicographic multi-objective genetic algorithm, which extends the traditional single-objective genetic algorithm, to effectively solve large-sized problems. Overall, our study not only addresses a real-life problem in the textile industry but also introduces innovative techniques and approaches for optimizing multiple objectives in a scheduling context.

LEAN APPLICATIONS TO IMPROVE CHEMICAL LABORATORY PRODUCTION CAPACITY IN THE TEXTILE INDUSTRY

Lean literature suggests that the attitude of “wait and see” has not yet allowed textile professionals to adopt Lean in production, especially in the laboratory. To fill this gap, the author illustrated a case study in a chemical laboratory of a renowned knit composite industry in Bangladesh. A team of textile and industrial engineers observed all processes in the laboratory from start to end for two years to detect problems and then conducted four brainstorming sessions with Lean experts to generate solutions to those issues which are finally presented for capacity improvement through dyeing machines’ capacity optimization, lead time evaluation, lab room temperature optimization, facility layout redesign, quick worksheet preparation, and workplace organization. This study proves that Lean applies to any process improvement. Also, data obtained in this research is highly valuable for textile engineers for future research and readily available for Value Stream Mapping.

Detecting dyeing machine entanglement anomalies by using time series image analysis and deep learning techniques for dyeing-finishing process

Tangle anomalies represent a critical quality bottleneck in the dyeing and finishing process. The key problem is that most dyeing and finishing factories in Taiwan are small and medium-sized enterprises. The operating dyeing machines can only detect entanglement through the shutdown alarm or experienced craftsmen. In this study, machine data of operating dyeing machines are collected. The time-series data image technology of the Gramian Angular Summation Field, Gramian Angular Difference Field, and Markov Transition Field is combined with a convolutional neural network to develop an entanglement detection model. Industry manufacturers cooperating with universities collected 1,750,977 pieces of production data from 1,848 batches for verification and study. The results show that the optimal detection time for entanglement detection is 220 s, using the MTF conversion method with a moving window of 20, a parameter learning rate of 0.00005, and a batch size of 200. The results are systematically introduced into the field. It has been verified that when signs of entanglement occur, an alarm can be sent to the relevant personnel to solve the problem in the shortest time. As a result, manufacturers can greatly reduce the cost of quality loss and scheduling bottlenecks caused by downtime caused by entanglement.

Cotton Dyeing with Cochineal by Just in Time Extraction, Mordanting, Dyeing, and Fixing Method in the Textile Industry

ABSTRACT Cochineal is employed in the field of cosmetics, food, textile, and flavors. The use of cochineal in textile goes back an ancient times in Mexico. These dyes have been used in different natural fibers. After the first quarter of the sixteenth century, cochineal was brought from Mexico to Europe and Asia. Since this date, it has been used very quickly and widely in Europe and Asia. The dye is used as a natural dye all over the world nowadays. Today, the dye is usually dyed with traditional methods. Cochineal is an important natural dye resource for red colors. The use of cochineal has come to importance in the textile industry for the red color in recent years. Cochineal has not been used as an economical, sustainable, and mass production in the textile industry up to now. This study has provided economical, sustainable, and industrial-scale production in the cotton textile industries. Cochineal dyeing recipes were created on industrial-scale samples by the jet dyeing machines. Color change, washing, rubbing fastness 4–5, and lightfastness found 4–5. The optimum conditions were determined for dyeing by the jet dyeing machine. According to the optimum dyeing recipe, cotton fabric was dyed with cochineal.

Machine-Learning-Based System for the Detection of Entanglement in Dyeing and Finishing Processes

Many dyeing and finishing factories generally use old-fashioned dyeing machines. A key issue when using these machines is that the dyeing tank cannot detect entanglement problems, which may result in a lower dyeing quality. In this paper, imbalanced data with ensemble machine learning, such as Extreme Gradient Boosting (XGBoost) and random forest (RF), are integrated to predict the possible states of a dyeing machine, including normal operation, entanglement warning, and entanglement occurrence. To verify the results obtained using the proposed method, we worked with industry−academia collaborators. We collected 1,750,977 pieces of data from 1848 batches. The results obtained from the analysis show that after employing the Borderline synthetic minority oversampling technique and the Tomek link to deal with the data imbalance, combined with the model established by XGBoost, the prediction accuracy of the normal operation states, entanglement warning, and entanglement occurrence were 100%, 94%, and 96%, respectively. Finally, the proposed entanglement detection system was connected with the factory’s central control system using a web application programming interface and machine real-time operational parameter data. Thus, a real-time tangle anomaly warning and monitoring system was developed for the actual operating conditions.

Investigation of Pretreatment of Textile Wastewater for Membrane Processes and Reuse for Washing Dyeing Machines.

The aim of this study was to investigate the best pretreatment of textile wastewater (TWW) for membrane separation processes and the previously unexplored reuse of treated TWW for washing dyeing machines. Sand filtration (SF), coagulation, coagulation/flocculation, and ultrafiltration (UF) with hollow fiber membrane (ZW1) were used for pretreatment. Pretreatment selection was based on turbidity, total organic carbon (TOC), and color. SF and ZW1 were found to be the best pretreatments. In addition, the SF and ZW1 effluents were subjected to the 5 (PT) and 50 (MW) kDa UF flat sheet membranes to test removal efficiency. ZW1-PT was better in terms of removal results and fouling. To reduce the use of drinking water for washing dyeing machines, the characteristics of ZW1-PT effluent were compared with drinking water from a textile factory. TWW treated with this hybrid process fulfils the purpose of reuse for washing dyeing machines and can be used in Galeb d.d., Croatia, or in any other textile factory, saving up to 26,000 m3 of drinking water per year. This contributes to both sustainable production and the conservation of water resources.

Design and Development of Hank Dyeing Machine and in-house field trials for Khadi Cluster

Abstract: In India Textile product processing industry is the only way which can help to boost the rural economy and the development of rural sector in India. Today’s customers are seeking for reduced prices, high quality product and the excellent durability of textiles. As increasing population directly increases the demand of textile in market. To meet that demand there is a necessity to replace the manual operation method by machine operation. Nowadays there are many automatic hank dyeing machines are available in the market but they are too costly and most of the rural based khadi industries or NGOs are unable to afford and maintain that machine. On the request of KVIC, MGIRI WARDHA has designed and developed the hank dyeing machine which is user friendly and cheap in cost as well as in less maintenance and also operated by unskilled operator. The developed hank dyeing machine can dye 7 kg of dry hanks in 30 minutes. This machine dyes single batch in just 30 minutes. This is cost effective, energy efficient, electric driven machine suitable for rural based small scale textile industry. Keywords: Hank: Dyeing: Coloring: Machine: Textile.

Sustainable and Mass Production of Cotton Dyeing with Natural Dye (Weld) in the Textile Industry

ABSTRACT The use of natural dyes in textile fibers goes back an ancient times. These dyes have been used in traditional methods until now. The use of natural dyes has come to importance in the textile industry in recent years. This situation desired sustainable, mass, and large-scale productions by the textile industries. Many dye plants used in natural dyeing have been very successful in laboratory studies. However, there are significant problems in using these dyeings in industrial-scale production, and they cannot be applied on an industrial scale in a sustainable way. In this work, weld dyeing recipes were created on industrial scale samples by the jet dyeing machines. Color change, washing, perspiration, rubbing fastness 4–5, and lightfastness found 3–4. The optimum conditions were determined for dyeing by the dyeing machine. According to the optimum dyeing recipe, cotton fabric was dyed with weld by the large-scale dyeing machine. The main coloring compounds are luteolin and apigenin in the weld. The main coloring compounds (luteolin and apigenin), mordant metal (aluminum), fastness tests, color coordinates, and fastness values were investigated in the dyed fabrics by different methods.

Energy efficiency analyses in a Turkish fabric dyeing factory

ABSTRACT In this study, energy efficiency applications and corresponding energy saving results were evaluated in a Turkish fabric dyeing factory. The relationship between energy consumption and the production were evaluated by regression analysis. They were detailed with energy intensity index (EII), cumulative sum values (CUSUM), specific energy consumption (SEC), and radar chart. The energy efficiency efforts should be initiated from heat and electrical energy, which are the main energy types extensively used in the textile industry. Average energy consumption value of the last four years (2015–2018), which is 7134 TOE is reduced 49% including waste heat, flash steam and cooling water recovery, and insulation in dyeing machines, in the factory due to the implementation of the energy saving actions. Accordingly, a reduction of 25% SEC value is possible. Moreover, production planning has a significant impact on the total energy consumption in terms of full load capacity operation of the dyeing machines, which may cause 23% energy saving that is of great importance.

Analysis of Maintenance Systems in Jet Dyeing Machine Components Using the Age Replacement Method

Purpose: The purpose of this study was to determine the maintenance intervals of critical components of jet dyeing machines in an effort to minimize downtime and calculate maintenance costs for engine damage to the jet dyeing. Design/ methodology/ approach: In this study an optimization method was developed to determine the replacement interval of a critical component, namely the Age Replacement Method. Findings: Based on the results of the calculation interval obtained preventive care critical components of jet engines during dyeing 1549 hours. It means that the component must be replaced before operation for 1549 hours or there is 6 times the turnover of prevention under taken in the interval of one year and the resulting decrease in the total cost of 82%. Research limitations/ implications: A review conducted in this paper against one component only, and then it can be developed for this type of component production machines. Practical implications: If the company is implementing a policy of replacement of critical components of the engine on the jet dyeing machine with a method of age replacement, then it will occur treatment cost savings amounting to Rp. 6,752,886 lower when compared with the initial conditions the company previously Rp 37,441,132. Originality/ value: This study combines the Pareto Diagram method and the Age Replacement Method to obtain optimum maintenance scheduling.

Improvement in the light fastness of dyed meta‐aramid fabric using titanium dioxide nanoparticles

Meta‐aramid fibre is very difficult to dye because of its very high crystallinity. The major issues with dyeing meta‐aramid fibre are its selective dyeability with a particular class of dye and poor light fastness, especially with basic dyes, which is not acceptable. In this work, various dyeing trials of meta‐aramid fabric with two commercial basic dyes, Bezacryl Golden Yellow GL 200 and Bezacryl Blue FBS, were conducted on high temperature–high pressure and infrared dyeing machines. To improve the light fastness of dyed samples, titanium dioxode nanoparticles were applied on dyed fabric using a layer‐by‐layer technique. Fastness properties such as light, wash and rubbing were checked for untreated and titanium dioxode‐treated samples. Titanium dioxode application on dyed material improved the light fastness of Bezacryl Golden Yellow‐dyed samples significantly, and Bezacryl Blue FBS also showed an improved rating compared with that previously reported. Improvement in light fastness is selective but it is still a novel and viable route to improve the light fastness of dyed meta‐aramid fabrics.

Controlling fibrillation – experiences of the dyeing and finishing of lyocell fibres

This review centres on the development of dyeing and finishing technologies for lyocell (TENCEL®) fibres since they were introduced onto the market in 1992. Initially, it will look at the reason for starting manufacture of the fibre and its manufacturing technology. An overview of basic dyeing performance is followed by a critical assessment of the fibre's introduction into the commercial world and the problems that ensued from its fibrillation property. The review then outlines the pioneering process development efforts made in Japan. Dye machinery manufacturers also played an important role in developing processing routes, particularly, but not exclusively, Then, Thies, and Krantz. Courtaulds Tencel formed an alliance with Sir T & A Wardles of Courtaulds Textiles, setting up a project to demonstrate successful jet processing of lyocell fabrics. Investment in jet dyeing machines and personnel was critical: the review explains how it was done and results that were achieved. It also considers how to control fabric behaviour in relation to creasing and fibrillation. The latter phenomenon held the fibre back from knitted applications. Both Courtaulds and Lenzing developed non‐fibrillating versions of the fibres. This review covers these advances, as well as how new markets have been developed for the fibre, such as workwear and bed sheeting. It concludes by looking at the key market segments today and how Lenzing sees the lyocell market evolving.

Practical realisation of ozone clearing after disperse dyeing of polyester

In this study, a novel system utilising ozone in jet dyeing machines is introduced, and the results of ozone‐clearing treatments of disperse dyed polyester on the prototype modified machine are reported. A Venturi injector was mounted on the liquor circulation pipe of the jet dyeing machine to feed ozone gas into the machine. Ozone was generated via an ozone generator by feeding conditioned air into the generator. The ozone gas entering the pipe partly dissolved in the treatment liquor; the dissolved portion and the gaseous ozone interacted via the fabric in the pipe, especially in the nozzle and also at the bottom of the autoclave (machine body). Disperse dyed polyester fabrics of textile‐company mass production were ozone cleared in this prototype. Ozone clearing was achieved in cold water (room temperature), and no other chemicals were used. The colour of the samples, wet fastness properties, and the chemical oxygen demand of the effluent were investigated, and costs were compared with those of conventional reduction clearing of ozone. Results were outstanding: an 83% cost reduction, 67% timesaving, and an 88% COD reduction were achieved.

Evaluation of Integrated Pollution Prevention Control in a textile fiber production and dyeing mill

Abstract Cleaner production assessment studies were conducted in a textile mill employing wool and acrylic fiber production and subsequent dyeing. A company-wide mass-balance analysis was performed. Various specific consumptions, emissions and waste generations were determined. The performance of the mill was evaluated based on BREF Documents. Water quality analysis indicated that process wastewaters from wool yarn softening, LP-VP printing machines and acrylic yarn washing could be reused in these processes, even without further treatment. Process wastewaters from wool yarn washing and softening in hank dyeing machines could be directly reused in tank washings and/or blended with process waters for direct reuse in the same or other processes. By the application of suggested BAT including wastewater reuse, machinery modifications, reuse of steam condensate, and good management practices, total water consumption may be reduced 35–65%. Substitution of 12 chemicals with more biodegradable and less toxic ones and installation of automatic chemical dosage systems may decrease COD loads about 25–50%. Furthermore, chemical and dyestuff consumptions could be reduced 31%. Energy consumption could be reduced by BAT suggestions including implementation of energy recovery systems for high temperature wastewater flows and flue gas emissions; process monitoring-control and various machinery optimization. Thus, potential reductions in total energy consumption in the mill may be up to 70%. Waste gas emissions could be reduced 25–65%. Waste generations may be decreased 5–10% with good management practices and reuse of especially textile wastes. Pay-back period of the suggested BAT options was found to be generally up to 4 years.

A General Decision Support Systems Approach to the Port Scheduling Problem for Pressure Beck Operations

With the current proliferation of computer-based decision support systems across all types of manufacturing applications, computer-based agents for management support of textile process decisions are receiving increasing attention. One of the most potentially rewarding of these textile applications is in the area of scheduling and machine loading for the dyeing of piece goods with multi-port dyeing machines. The range of industry practices in dealing with this problem is diverse, often requiring tedious manual calculations that result in non-optimal machine loads, quality problems and a high turnover of scheduling operators. In this paper the authors report on their development of a potentially comprehensive decision support system solution to the problem. Their solution involves a two-phase approach where linear programming is used to develop optimal machine loads and a computer-based heuristic is used to schedule the activities required to load specific dyeing machines.

A decision support system for scheduling jobs on multi‐port dyeing machines

In this paper we report the development and implementation of a decision support system to solve a complex scheduling system for a major apparel fabric company with annual sales of more than $2.5 billion. For the first phase of the problem, we developed a linear programming model to generate optimal machine loads. For the second phase, we designed a heuristic to minimize the delays that occur during the subsequent fabric roll selection and sequencing operations. Our system completely replaced tedious manual calculations with optimal machine loads, greatly improved the overall quality of their products, and produced unexpected benefits such as practically eliminating the high turnover of scheduling operators.

Environmental profile of textile wet processing in Finland

This study was carried out in major Finnish textile companies in order to create an environmental impact profile for wet processing in Finland as a part of drafting the Best Available Technique (BAT) Reference documents for the European IPPC Bureau. System boundaries were defined for alternative process technologies to be used in BAT definitions. The use of resources and process emissions is, however, monitored for the whole wet processing only in the companies under study. No remarkable differences in energy and water consumption between continuous and batch wet processing could be measured; the lowest dyeing liquor ratios were reported on jet machines and the highest on winch dyeing machines. Dyestuff consumption depends on the colour shade required; some dyes have, however, low fixation rates, such as reactive and sulphur dyes, only 60% on average. About 20% of the process liquor containing unfixed dyestuffs and auxiliaries end up in sewage treatment plants. These chemicals are not recovered and reused in the companies under study. All industrial plants in Finland discharge their wastewater to municipal sewage treatment plants, which carry out wastewater analysis and control. All textile plants, which use more than 50 tonnes of organic solvents per year, are under official off-gas control in Finland.

New control strategies for batch dyeing operations using mathematical modelling and simulation

Around 60% of all dyed fibre and yarn is produced in package dyeing machines. It is therefore important to look at their design and operation in the light of the experience of similar processes in the chemical and process industries. This article tries to merge current research ideas on the dynamic on‐line control of package dyeing machinery with practical observations and industrial experience.