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An investigation is presented of the impact of mechanical auxiliary devices on sewing‐machines upon the processing parameters of sewing operations. Processing parameters are investigated at an ergonomically designed workplace, on a modern sewing‐machine, equipped with a processing microcomputer. Measuring samples are 300 to 1,000mm long, and stitching speeds are pre‐programmed – 1,500 to 4,700rpm. Values for sewing operation processing parameters are measured and stored using the measuring system for processing parameters MMPP, developed especially for the purpose of research in the field of garment engineering. The results obtained indicate that using a tape piper the basic time needed to perform the sewing operation is reduced by up to 61.2 per cent, while the use of a hemmer reduces it by 38.3 per cent. Specific time for sewing 1m of seam is reduced using the above auxiliary devices as follows: by 64.5 per cent using a tape piper and by 41.8 per cent using a hemmer. The degree of sewing‐machine utilisation is increased by 110.6 per cent using a tape piper, and by 59.8 per cent using a hemmer. Average stitching in machine‐hand sub‐operations is increased with a tape piper from 1,041 to 3,914rpm, and from 1,176 to 3,959rpm with a hemmer. The operation structure is altered by using auxiliary devices, achieving rationalisation of the movements constituting auxiliary‐hand sub‐operations, which has a considerable impact on the processing parameters involved.

The conversion of fabric into a garment involves many interactions such as the selection of suitable sewing thread, optimization of sewing parameters, ease of conversion of fabric into the garment and actual performance of the sewn fabric during wear of the garment. The adjustment of all sewing parameters is necessary to ensure quality. The purpose of this paper is to define the parameters that affect seam quality comprehensively.

This study primarily focuses on the studies dealing with the effect of various parameters on-seam quality in detail. A systematic literature review was conducted.

The interactions between parameters may lead to different results than the effect of a single parameter. In addition, changing some parameters may have a positive effect on one element of seam quality while having a negative effect on another. For this reason, it is very important to properly select the parameters according to the specific end use of the garment products and also to consider the interactions.

The knowledge of various factors that affect seam quality will be helpful for manufacturers to improve production performance and to be able to produce high-quality seam.

This work highlights the optimization of the consumed amount of sewing thread required to make up a pair of jeans using three different metaheuristic methods; particular swarm optimization (PSO), ant colony optimization (ACO) and genetic algorithm (GA) techniques. Indeed, using metaheuristic optimization techniques enable industrialists to reach the lowest sewing thread quantities in terms of bobbins per garments. Besides, the compared results of this research can obviously prove the impact of each input parameter on the optimization of the sewing thread consumption per pair of jeans.

To assess objectively the sewing thread consumption, the optimized sewing conditions such as thread composition, needle size and fabric composition are investigated and discussed. Hence, a Taguchi design was elaborated to evaluate and optimize objectively the linear model consumption. Thanks to its principal characteristics and popularity, denim fabric is selected to analyze objectively the effects of studied input parameters. In addition, having workers with same skills and qualifications to repeat each time the same sewing process will involve having the same sewing thread consumption values. This can occur in some levels such as end of sewing, the number of machine failures, the kind of failure and its complexity, the competency of the mechanic and his way to repair failure, the loss of thread caused by threading and its frequency. Seam repetition due to operator lack of skill will obviously affect clothing appearance and hence quality decision. Interesting findings and significant relationship between input parameters and the amount of sewing thread consumption are established.

According to the comparative results obtained using metaheuristic methods, the PSO and ACO technique gives the lowest values of the consumption within the best combination of input parameters. The results show the accuracy of the applied metaheuristic methods to optimize the consumed amount needed to sew a pair of jeans with a notable superiority of both PSO and ACO methods compared to experimental ones. However, compared to GA method, ACO and PSO algorithms remained the most accurate techniques allowing industrials to minimize the consumed thread used to sew jeans. They can also widely optimize and predict the consumed thread in the investigated experimental design of interest. Consequently, compared to experimental results and regarding the low error values obtained, it may be concluded that the metaheuristic methods can optimize and evaluate both studied input and output parameters accurately.

This study is most useful for denim industrial applications, which makes it possible to anticipate, calculate and minimize the high consumption of sewing threads. This paper has not only practical implications for clothing appearance and quality but also for reduction in thread wastage occurring during shop floor conditions like machine running, thread breakage, repairs, etc. (Kawabata and Niwa, 1991). Unless the used sewing machine is equipped within a thread trimmer improvement in garment seam appearance cannot be achieved. By comparing and analyzing the operating activities of the regular lock stitch 301 machine with and without a thread trimmer, a difference in time processing can be grasped (Magazine JUKI Corporation, 2008). Time consumed in trimming by a lockstitch machine without a thread trimmer equals 3.1 s compared to 2.6 s by a thread trimming one. Hence, the reduction rate in the time processing equals 16.30%. This paper aimed to implement the optimal consumption (thread waste outstanding number of trials). Unless highly skilled workers are selected and well-motivated, the previous recommended changes will not be applied. The saved cost of the sewing thread reduction can be used to buy a better quality of fabric and/or thread. However, these factors are not always the same as they can vary according to customer's requirements because thread consumption is never a standard for sewn product categories such as trousers, shirts and footwear (Khedher and Jaouachi, 2015).

Until now, there is no work dealing with the investigation of the metaheuristic optimization of the consumed thread per pair of jeans to minimize accurately the amount of sewing thread as well as the sewing thread wastage. Even though these techniques of optimization are currently in full development due to some advantages such as generality and possible application to a large class of combinatorial and constrained assignment problems, efficiency for many problems in providing good quality approximate solutions for a large number of classical optimization problems and large-scale real applications, etc., are not applied yet to decrease sewing thread consumption. Some recent published works used statistical techniques (Taguchi, factorial, etc.), to evaluate approximate consumptions; conversely, other geometrical and mathematical approaches, considering some assumptions, used stitch geometry and remained insufficient to give the industrialists an implemented application generating the exact value of the consumed amount of sewing thread. Generally, in the clothing field 10–15% of sewing thread wastage should be added to the experimental approximate consumption value. Moreover, all investigations are focused on the approximative evaluations and theoretical modeling of sewing thread consumption as function of some input parameters. Practically, the obtained results are successfully applied and the ACO method gives the most accurate results. On the other hand, in the point of view of industrialists the applied metaheuristic methods (based on algorithms) used to decrease the amount of consumed thread remained an easy and fruitful solution that can allow them to control the number of sewing thread bobbin per garments.

The equipment for computerised measuring of electrical power and energy is presented, adapted to the needs of investigating processing parameters of garment sewing operations.

The method of measuring the energy necessary to run the sewing‐machine driving electrical motor is also presented, correlated to the stitching speed in joining a straight seam in a single, two, or three, segments. Electrical energy consumption is analysed as dependent on the stitching speed, varying the number of stitches in the seam.

The investigations described have shown the impact of the method of work applied and the effect of the changes in garment sewing operation in processing parameters on the level of electrical energy consumed by the sewing‐machine drive electrical motor. A new measuring method has been introduced in garment engineering, aimed at predicting electrical energy consumption in garment sewing operations, thus opening a completely new field of investigation in the area of garment technologies.

A method of calculating the energy processing parameters of sewing operations.

The purpose of this review paper is to define the dominating factors (such as fiber, yarn, fabric structure, sewing thread, sewing needle and machine parameters) that affect the seam damages and causing defects. It also describes the various explanations of sewing defects in garment production and critically analyzes them for optimum selection of parameters and speeds for minimizing such faults. Hence, the knowledge of various factors which affect the sewing damages/defects will be helpful for garment manufacturers/researchers to know influence of the parameters and control the quality of producing seam.

This section is not applicable for a review paper.

Sewing damages such as needle cut and other sewing damages/defects are studied mostly in woven fabric. There are very few studies conducted on knitted fabric sewing damages/defects. The sewing damage problems do not have single solution that is capable of removing these damages in fabric. All the determined and affecting parameters related to fiber, yarn, fabric construction, sewing thread and sewing machine must be examined to design appropriate remedial measurement related to machine design, fabric parameters and sewing thread. This could help in minimizing or eliminating the needle cut and other sewing damage problems.

It is an original review work and is helpful for garment manufacturers/researchers to reduce the defects and be able to produce good quality seam.

The aim of the present study is to consider the influence of the tensile behavior of fabric and sewing thread on the seam appearance.

In this study, the formation of seam puckering on two elastic and normal woven fabrics was explored. In order to prepare samples, various sewing threads were applied. Test specimens were sewn under five different thread tension levels. Then the appearance of samples was evaluated subjectively to determine their seam puckering grade before and after the laundering process.

The obtained outcomes of this study present that although sewing thread tension increment decreases the seam pucker ranking in the similar sewing condition, elastic fabrics have a greater seam pucker grade compared to the normal fabric due to the fabric extension and contraction during sewing and after sewing process, respectively. In addition, the elastic strain of the sewing thread is the key factor that determined sewing thread's tendency to make seam puckering. Moreover, the laundry process due to the relaxation of the sewing thread decreases the seam pucker grade.

The consistency of the tensile property of fabric and sewing thread is a crucial parameter in improving the seam appearance and obtaining a smooth seam.

Simulating the behavior of clothing has always been of interest in the apparel, fashion and computer game industries. With the development of these industries, there is a need to increase the accuracy of clothing simulation techniques. A garment contains many seams whose behavior affects its final appearance. In this study, a numerical model is presented to simulate seam puckers in single- and double-layer fabrics.

A yarn-level simulation technique has been used for this purpose. Based on this technique, the individual threads in the fabric structure and the sewing threads are modeled separately. Then, their behavior and interaction with each other are considered in the seam pucker model.

The model is used to simulate the real samples. The results show that the proposed model is able to simulate the degree of seam puckering for a single-layer fabric with an average error of 7.9% and for a double-layer fabric with an average error of 8.5%.

The behavior of the seam is affected by the properties, behavior and interaction of the sewing threads and yarns in the fabric structure. In previous studies, the parameters related to seams and fabrics were not fully considered. In this study, a new yarn-level model is presented to simulate seam puckering in woven fabrics. The most important advantage of this type of simulation is the ability to examine the interaction of fabric threads as well as the interaction of sewing threads with each other and with the threads of the fabric structure.

This paper suggests a new method for determining the sewing damage that occurs in single jersey fabrics based on the calculation of the needle hole area. This paper also aims to investigate the effects of material type, sewing parameters, and repeated washing cycles on sewing damage by using this method.

Six knitted fabrics, differing in structure and raw material, were produced. Samples were sewn using different sewing parameters, and they were subjected to ten washing cycles. Values of average needle hole area, an objective indicator of sewing damage, were calculated before and after repeated washing cycles using image analysis software and were evaluated statistically.

The results showed that the average needle hole area calculated via the image analysis software effectively estimates sewing damage as the results obtained were compatible with those stated in the literature. Furthermore, fabric type, sewing direction, sewing thread type, and needle size significantly affected the sewing damage. However, stitch density did not affect the sewing damage. When the effect of washing cycles was compared, it was seen that washing leads to an increase in sewing damage.

A review of the existing literature shows that no previous study has evaluated sewing damage using image analysis software. This study proposes a novel objective method to determine the sewing damage that occurs in knitted fabrics.

Sewing is one of the most commonly used manufacturing processes in the world. Millions of parts are sewn every day ranging from cloths, shoes, furniture, to automobile seat covers. However, it is also one of the least understood processes. In fact, according to literature survey, few know how to calculate the sewing force or the fabric deformation during the sewing. This paper presents our research on using finite element model (FEM) to study the sewing process. The model is developed using ANSYS software system. In the model, the fabric is approximated by a number of perpendicular beam elements with elastic and plastic capabilities. On the other hand, the needle is modeled by a simple elastic beam. The contact between the two parts is modeled by contact elements. The variations of the needle geometry and the fabric material properties as well as the sewing conditions are also included in the model. The model can simulate the needle piercing through a material, and calculates the sewing forces as well as the fabric deformation forming a hole. It has been verified experimentally and can be used to study the effects of the key sewing parameters such as the fabric material properties and the needle geometry.

This paper aims to investigate the use of artificial neural networks (ANN) to predict the sewing performance of fabrics. The purpose of this study is to verify the ANN techniques that could be emulated as human decision in the prediction of sewing performance of fabrics.

In order to verify the ANN techniques that could be emulated as human decision in the prediction of sewing performance of fabrics, 109 data sets of fabrics were tested by using fabric assurance by simple testing system and the sewing performance of each fabric's specimen was assessed by the domain experts. Of these 109 input‐output data pairs, 94 were used to train the proposed backpropagation (BP) neural network for the prediction of the unknown sewing performance of a given fabric, and 15 were used to test the proposed BP neural network.

After 10,000 iterations of training of BP neural network, the neural network converged to the minimum error level. The experimental results reveal the great potential of the proposed approach in predicting the sewing performance of fabrics for apparel production.

Generally, the fabric's performance in the manufacturing process is judged subjectively by the operators and/or their supervisors. Current methodologies of acquiring fabric property information and predicting fabric sewing performance are still incapable of providing a means for efficient planning and control for the sewing operation. Further, development of techniques to predict the sewing performance of fabric is essential for the current apparel production environment. In this paper, the use of ANN to predict the sewing performance of fabrics in garment manufacturing is investigated.