Sewing Process Research Articles

Evaluation of alternative joining methods in softshell fabric types

Parameters such as high performance, durability and comfort are very important in protective and sports clothing produced to increase the technical or functional properties of clothing products, as well as aesthetic and decorative features. Fabrics that provide comfort to the user by regulating body temperature, protect against harsh weather conditions, and are waterproof and windproof, as well as breathable, are used for these purposes. One of the most important fabrics with these features is the fabric called ‘softshell’. Softshell is a fabric specially created to release moisture and regulate body temperature. Therefore, the outer layer of the softshell is not waterproof, but water-repellent, ensuring that it remains dry and protective while a person is wearing it. Creating a three-dimensional product from a two-dimensional fabric with these features is achieved through the sewing process. As traditional methods are used in the sewing process, an alternative joining method called ‘ultrasonic joining’ can also be used. While alternative joining methods provide joining without sewing thread, these methods do not create holes in the fabric surfaces since there is no sewing needle. Joining processes with thermal, laser and ultrasound energy are based on the principle of melting, fusing and cooling the joined surfaces. In this study, it was aimed to analyze the change in the physical properties of different softshell fabrics as a result of joining them with classical and innovative sewing/joining methods. In this context, lockstitch, lockstitch & tape welding, ultrasonic welding, and ultrasonic welding & tape welding are applied to the softshell, ripstop softshell and Lycra softshell fabrics used in the market. The thickness, air permeability, seam strength and elongation at break properties of the bonded fabrics were examined. Within the scope of this study, obtaining successful results in softshell fabric types, which is one of the bulky fabrics, contributes to the idea that the usage area of ultrasonic welding will expand day by day.

Assessing the contribution of sewing threads to microfiber release during domestic laundering

Environmental science studies from the past decade have emphasized that microplastics in aquatic environments are mostly caused by domestic laundering of synthetic textiles. Although many studies have explored the microfiber release behavior of fabrics washed in laundry, attempts to witness microfiber release from sewing threads, which are an inevitable part of any finished garment, are meager. With this research gap, this study attempted to analyze the potential of sewing threads to release microfibers during washing and the extent to which they can contribute to the overall microfiber release during domestic laundering. The study's findings revealed an average release of 2.65 ± 0.70 (n = 33) microfibers/m from the sewing thread sewn on the fabric during laundering. The sewing process was noted to cause damage to the sewing thread, which led to a comparatively higher microfiber release (∼114%) compared with the sewing threads that were washed before sewing. Among the selected sewing threads, higher microfiber emissions were reported with spun threads, followed by twistless filaments, and twisted filament threads. The results showed that coarser sewing threads with higher Tex values released more microfibers than finer Tex threads. Compared to the 20 Tex spun thread, the 80 Tex spun thread showed a 22–150% increase in microfiber release. In the case of filament sewing thread, a similar impact was noted, whereas the role of twist was found to be efficient in reducing microfiber emission. Compared to the untwisted filaments, the ply twisted filaments exhibited approximately 76% lower microfiber emissions. The findings of this study showed that sewing thread contributed approximately 1.09% of the total microfiber emissions from apparel during laundry.

Rapid detection technology of sewing thread based on DeblurGAN-BSV3 defuzzification algorithm and ST-FPN detection algorithm

Stitch defect detection is an important means to ensure the quality of stitched fabrics. In order to realize the intellectualization of the sewing process, a rapid defect detection method based on machine vision was proposed. In order to solve the problem of motion blur caused by sewing speed, an image DeblurGAN-BSV3 algorithm is proposed. Firstly, different attention fusion mechanisms are introduced to achieve accurate extraction of image features. Secondly, the depth-separable convolution of the trunk network is replaced by blueprint convolution to ensure the processing speed of the detection algorithm and the clarity of the output image. In order to solve the difficulty of rapid detection of pin defects, a student–teacher feature pyramid matching method was proposed. Firstly, the abnormal region interpretation technology was used to explicitly visualize the defect area of the identified abnormal instances, and then the abnormal detection score was performed on the detected images to make a quality judgment. The experimental results show that the combination of the above two methods has a good ability for rapid defect detection. Rapid detection of common pin defects is realized.

A study on the formulation of process parameters for soft finger-assisted fabric stitching

PurposeTo reduce the difficulty of the sewing process and promote the automation process of fabric sewing, a soft finger-assisted feeding method is proposed to investigate the effect of sewing process parameters on the quality of automatic sewing.Design/methodology/approachTaking cotton woven fabrics as an example, the causes of sewing deviation are firstly investigated from three aspects: fabric properties, sewing speed and sewing edge position. By simulating the sewing action of human hands, the method of reducing sewing deviation by using soft fingers to press and feed the fabric is proposed. Then, four sewing process factors, namely, robot arm end pressure, sewing machine speed, sewing needle gauge and stitch density, were selected, and three levels were set for each factor to design orthogonal sewing experiments. The sewing deviation of 1# sample under different sewing processes was measured, and the optimal parameter matching for automatic sewing of this specimen was derived.FindingsThe findings demonstrate that, while sewing cloth automatically, the sewing deviation is significantly influenced by the robotic arm's end pressure, sewing speed, and stitch density, whereas the sewing deviation is not significantly impacted by the needle number.Originality/valueThe findings offer fundamental information for the development of an automated sewing procedure using soft fingers, which has theoretical and real-world application value to speed up the intelligent modernization and transformation of the apparel industry.

Modeling and motion simulation study of a three-dimensional sewing device

Abstract In response to the sewing demands of steering wheels and their unique shapes, a multi-robot arm cooperative three-dimensional sewing device was designed to achieve efficient and precise sewing operations. Utilizing SolidWorks, a collaborative three-dimensional sewing device involving multiple robotic arms was engineered, and its mechanism model was established in ADAMS software for motion simulation analysis to evaluate the device’s performance and motion characteristics. This three-dimensional sewing device is capable of fulfilling the sewing requirements of special curved surface items such as steering wheels, enhancing production efficiency and saving labor. Taking the constructed physical prototype as the research subject, motion experiments simulating the sewing process were conducted. Combined with the simulation results, curves, and three-dimensional motion effects, the feasibility of the design was successfully verified, providing a foundation for subsequent sewing trajectory planning and motion control of the device.

A new approach for predicting seam strength

Owing to a high amount of stress, seam failure in workwear fabrics makes the fabric unsuitable although the fabric strength is high. It is therefore important to predict the seam strength to ascertain the performance of the garments during use and determine the required thread strength to match the required seam strength. An assembly is composed of a sewing thread and a fabric. The thread forming the seam undergoes several stresses during its passage from the sewing machine to the formation of the loop and when wearing the garment: these are mechanical stresses. Therefore, it is necessary to evaluate the strength of the seam. But, in the bibliography, most researchers have studied the strength of the seam concerning a single type of stitch. This work aimed to examine the seam's strength from the resistance to the loop of the thread for all types of stitches. In all of the earlier predictive equations, seam strength is predicted from thread loop strength with some multiplicative factors. The thread loop strength is measured without considering the stitch type. During the sewing process, threads loop differently from one stitch to another, therefore, the standard thread loop strength becomes unfit to predict the seam strength. In this paper, the effects of loop thread length and configuration are studied on thread loop strength and seam strength. The seam strengths predicted from the loop strength before and after considering the new loop configurations and the real seam strength are compared. So, new clamps for loop strength are configured and carried out. It is observed that there is a closer match between experimental and predicted seam strength with new loop configurations. The loop configuration has a significant effect on the thread loop strength and improves the accuracy of seam-strength prediction.

Optimization of garment sewing operation standard minute value prediction using an IPSO-BP neural network

Abstract Standard minute value serves as a pivotal metric guiding the arrangement and balancing of production cycles in clothing production lines, and plays a crucial role in cost pricing and production order arrangement for clothing products. Given the complexity of the garment sewing process, ten influencing factors including fabric weight, fabric thickness, fabric density, stitching length, stitching shapes, cut pieces numbers, notch numbers, sewing technologies, sewing machine, and auxiliary accessories were identified. Upon this foundation, a standard sewing time prediction model, Improved particle swarm optimization - Back-propagation neural network (IPSO-BP), was proposed, focusing on non-quantitative factors. The IPSO-BP model was trained using actual sewing data from a women’s clothing production company. Compared to the unoptimized BP neural network, the IPSO-BP model demonstrated significant advantages in terms of convergence speed and prediction accuracy. Therefore, the IPSO-BP model proposed in this study holds promise for predicting standard sewing hours effectively.

Investigation of the bias tape roll change time efficiency in garment factories

Abstract In the ready-to-wear industry, bias tape is one of the many factors that affect the efficiency of the manufacturing process. In particular, the bias tape change period slows down production. The purpose of this study is to identify the effect of fabric length on the time of changing bias tape rolls. At most manufacturers, the bias tape is made by cutting an average of 1 m from the product’s own fabric. In this study, the effect of bias tape fabrics cut into three different lengths on the manufacturing process was compared with three models. By producing bias tape for each model, the time spent on cutting the fabric, sewing, and changing the roll in the bias holder that feeds the lockstitch machine was calculated. It was revealed that the difference in fabric length affects the efficiency of the sewing process. Namely, it was found that the time spent on changing the bias tape roll decreased between 4.31 and 8.98%. Based on these findings, it can be said that the time efficiency can be increased by increasing the length of the fabric of the bias tape roll to be produced, and thus the production process could be accelerated.

The effects of dyeing and finishing processes on seam efficiency of cotton fabrics

The sewing process is a very important step in terms of fabric quality. Seam strength is affected by fabric-related properties as well as stitch-related parameters, and seam efficiency is found by the ratio of seam strength to fabric tensile strength. Therefore, processes that affect fabric tensile strength also affect seam strength. The effects of finishing and laundering processes on the physical properties of fabrics are extremely important as well as on the fastness properties. While reorganizing finishing processes in order to contribute to sustainability, the effects of the process on the physical properties of the fabrics may help make a decision. In this study, the effects of bleaching, dyeing, finishing and laundering processes on thickness, air permeability, tensile strength and elongation, seam strength and seam efficiency properties have been investigated. According to the results, it is observed that the mentioned processes are effective on the seam efficiency in different ways.

How porosity of the middle layer can affect the comfort properties of multi-layer sportswear

Protection of the body against heat loss is vital to provide appropriate conditions for athletes of outdoor winter sports. Besides, considering the breathability of sportswear and its air permeability that can affect clothing ventilation should be noticed to provide athlete comfort. The application of multi-layered sportswear is a method to improve protection against cold and mobility of the person instead of wearing thick and heavy single-layer clothing, which has been under focus in winter sports. However, the properties of the constituent’s layers can determine the comfort properties of multi-layer sportswear. In this study, the influence of the middle layer porosity on the comfort properties of three-layer samples was investigated. The outer and inner layers remained unchanged for all samples and the middle layers were nonwoven samples with various needle punching densities including 15, 45, 70, 95, and 108 needles/cm2. The comfort properties of single layers and three-layer samples were evaluated before and after joining them by sewing. The obtained outcomes reveal that increasing the number of needle punching densities from 15 to 108 needles per square centimeter leads to the reduction of layer porosity by 35.43% which leads to the reduction of air and water vapour permeability and also thermal insulation of samples. After assembling layers, the comfort properties of three-layer samples are affected by the properties of various constituent layers and also the sewing process.

Use of MTM, RAV and ZAK Methods in Determining Working Methods and Time Norms in Technological Operations of Sewing Clothes

The paper presents the application of MTM, RAV and ZAK methods in the determination of working methods and time norms for the technological process of sewing. The technological operation of sewing the back sleeve seam on a men’s jacket is used for the study. The paper presents the designed workplace in a real production process. In addition, the appropriate working method and the time norm are determined using the MTM (Method Time Measurement), RAV (determination of sewing time for straight seams) and ZAK (determination of sewing time for curved seams) methods. The aim of the study was to combine the methods for determining different types of time (manual, machine-hand and machine) for performing technological operations and precisely calculate the time norms. For the described methods of determining the production time, computer programs were developed that speed up the calculation of the time norm. If the working method is defined in advance and the characteristics of the sewing machine are known, the time norm for each technological operation can be determined in advance. Based on these calculations, it is possible to determine the total time for the production of clothing in advance and thus to plan and schedule the production process and plan the delivery dates to customers. The results show that the technical equipment of the sewing machine and the working method have an influence on the structure of the technological sewing process. By choosing an appropriate working method, the workload and fatigue of the workers is reduced, as an appropriate number of auxiliary hand sub-operations are used. In this way, the appropriate time required to perform the technological operation is achieved.

Studying on improving sewing process of the back pocket, the waistband of the basic Jeans

Based on the codes of the MTM time measurement method and the GSD predictability time system, the study also gave some codes to build the time standard for assembling the back pocket and the waistband according to the traditional sewing processes (TSP). Then, combined with information about modern sewing equipment and time study, the research came up with several modern sewing processes (MSP) to replace TSP. The research results showed that when processing the back pocket using the back pocket hemming machine and the automatic back pocket setter machine, the ironing stage was eliminated, time-saving up to 73.5% and decreased to 66.66% of the number of operations compared to TSP; using the Kansai waistband sewing machine in combination with the folder saved time up to 65.15%; using the belt loop attaching machine saved time up to 66.7%; using the programming machine (to attach the leather label to Jeans) saved time up to 22.7% compared to TSP.

Integrating Digitalized Data and Optimization Method for Automated Production Planning in Sewing Lines

The current global landscape is undergoing a dynamic evolution marked by the onset of the 4th Industrial Revolution. This epochal transformation emphasizes digital transformation as a revolutionary catalyst, fundamentally reshaping businesses. The research presents the digital transformation in industrial sewing manufacturing by applying the Internet of Things (IoT) devices for comprehensive production data collection from sewing lines, alongside integrating data digitization techniques in the industrial sewing process. Moreover, from the data collected, the article proposes an automatic production planning method based on applying a scheduling problem combined with optimization algorithms. Based on that method, it will improve production management efficiency, competitiveness, and labor productivity, creating conditions for sustainable development and promoting global integration.

The impact of large volume atmospheric pressure air glow discharge plasma on enhancing denim fabric (textile) sewing process

A direct-current large-volume atmospheric pressure air glow discharge plasma (APAGDP) was developed to enhance the sewing process of denim fabric. The generated plasma was characterized optically, electrically, and spectroscopically. The generated plasma presents a positive electric resistance behaviour. The plasma emission spectra are dominated by the nitrogen second positive system. Its intensity increases with the applied voltage. The generated plasma was used as a pre-treatment to enhance the sewing of the denim fabric at different exposure times, from 5 to 600 s. The scanning electron microscopy images showed no damage to the surface morphology of the denim fabric after plasma treatment. The sound pressure level (SPL) was used to verify the plasma effect on the denim fabric as compared to the untreated fabric. The SPL decreases with plasma exposure time. This result indicates that the plasma improves the sewing performance of the denim fabric.

Encoded sewing soft textile robots.

Incorporating soft actuation with soft yet durable textiles could effectively endow the latter with active and flexible shape morphing and motion like mollusks and plants. However, creating highly programmable and customizable soft robots based on textiles faces a longstanding design and manufacturing challenge. Here, we report a methodology of encoded sewing constraints for efficiently constructing three-dimensional (3D) soft textile robots through a simple 2D sewing process. By encoding heterogeneous stretching properties into three spatial seams of the sewed 3D textile shells, nonlinear inflation of the inner bladder can be guided to follow the predefined spatial shape and actuation sequence, for example, tendril-like shape morphing, tentacle-like sequential manipulation, and bioinspired locomotion only controlled by single pressure source. Such flexible, efficient, scalable, and low-cost design and formation methodology will accelerate the development and iteration of soft robots and also open up more opportunities for safe human-robot interactions, tailored wearable devices, and health care.

The Flexible Job Shop Scheduling Problem with Setups and Operator Skills: an application in the textile industry

The Flexible Job Shop Scheduling Problem (FJSSP) is one of the most studied problems in the literature thanks to its practical relevance. Many industrial production scheduling problems can be seen as a FJSSP with different constraints and objectives. The studied problem arises in a textile factory, precisely in the sewing process. Multiple real-world constraints are tackled. Individual skills of operators and different types of setup times are considered: machine-change setup time for operators, colour-change setup times and configuration-change setup times. The objective is to minimize the total tardiness. To the best of the authors’ knowledge, this is the first study that tackles this variant of the problem. This paper presents a preliminary study to validate the approach and evaluate the tractability of the industrial problem. A mixed-integer linear programming (MILP) model is proposed and solved using a commercial solver. Real-world data are used to generate more than 1000 problems that are clustered in 4 groups based on the number of jobs to be scheduled, the number of operators and flexibility of their skills. The results show that the proposed MILP model can reach optimality for the small size instances but it is intractable for most large-sized instances. Moreover, the results highlight how diversifying the operators’ skills can help find better solutions.

LEAN SIX SIGMA APPROACH TO IMPROVE THE PRODUCTION PROCESS IN THE GARMENT COMPANY: A CASE STUDY

PT “X” is a company engaged in the garment industry. The company is facing problems that inhibit the production process. These problems comprise an excess of product defects beyond the specified limits, a considerable rate of product returns, delays in product shipment, and disorderly arrangements in storing raw material. This study aims to determine the root causes of problems in the PT “X” and provide recommendations for improvement using the concept of lean six sigma. The waste assessment model is used to identify the dominant waste, while the value stream analysis tools is a method used to analyze the causes of the dominant waste. From the research results, four dominant wastes are identified, namely waste defects, unnecessary inventory, waiting and unnecessary motion, with percentages of 27.02%, 15.92%, 14.32% and 14.0% respectively. The results of the analysis using mapping tools show the details of waste in each dominant waste. Proposed recommendations for improvement are made using the failure mode and effect analysis based on the highest risk priority number for each dominant waste. The recommendations proposed by the researchers include implementing a standard operating procedure and work instruction for the sewing process; scheduling machine maintenance using reliability centered maintenance II; planning and scheduling materials using material requirement planning; implementing line balancing; and designing name tags, visual displays, and storage rack layout.

Utilization of Blacu Fabric Material Waste as an Alternative Material for Fast Fashion Products

In today's fast fashion era, the fashion industry has experienced many developments supported by technological advances in the current digital era accelerating the development process in the fashion industry. In addition, the fast fashion trend is also bad for the environment, continuous product production even tends to increase the fast fashion trend produces large textile waste and requires a long time in the decomposition process. Therefore, the purpose of this study is to find out what the utilization of Blacu fabric waste produced by the fashion industry looks like. This research uses qualitative research methods with an exploratory study approach which is a good method to collect information about the perception of entrepreneurial intentions. The result of this study is that Blacu fabric waste can be reused and become an alternative material for making fast fashion in the form of bag bags or tote bags, the utilization is done using the upcycling method and patchwork processing method, this is because the production costs are economical when compared to other fabric waste processing techniques and produce product textures that have distinctive characteristics because they go through the process of preparation and sewing between fabrics

Lean Six Sigma Implementation For Improving Sewing Process in Apparel Industry

Lean Six Sigma Implementation For Improving Sewing Process in Apparel Industry

Automatic Thread Insertion Kit Sewing (ATIKs) Device for Vocational Fashion Design Student: Practical Sewing Application

The incorporation of technology is a consistent aspect of education, which is widely advanced through teaching and learning (T&L) in the industrial revolution 4.0 (IR 4.0) education technology. In this study, an automatic thread insertion set for sewing (ATIKs) was developed. The ATIKs device improves students' understanding and facilitates the process of sewing in fashion design subjects for high school curriculum. The device was programmed using an Arduino microcontroller board and open source Arduino software (IDE). The CDIO model is used as the basis for product development, which includes the steps from conception to design, implementation, and operation. The development for this product consists of the main components standard needle size, automatic thread, Arduino UNO R3, stepper motor, coil, and Arduino coding to control the movement. In addition, this product is relatively portable with its dimensions of 7 x 7 x 10 cm. A qualitative research method was applied using a list of interview protocols validated by five professional experts in the field. Based on the open-ended questions, the experts indicated that this product facilitates the criteria of the T&L process, improves understanding of the use of the thread needle, and increases student confidence in the sewing process. In the future, this kit could be integrated into an automated control system. This research development can help develop teaching tools that further increase student safety and improve student skills and cleanliness in handling sewing tools during hands-on work.