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The apparel industry is a labor-intensive industry, which depends mainly on the performance of the worker. The purpose of this study is to present an ergonomic redesign of the sewing machine workstation, with different sewing table heights and inclination angles, based on the operator’s anthropometric data.

A flexible ergonomic sewing table has been designed, four main workstation-setting factors were studied; sewing desk inclination angles – X_1, height – X_2, sewing machine type – X_3 and operator’s body mass index (BMI) – X_4, with three levels for each factor, except sewing machine type, which only has two levels. The study was undertaken to specify the limitations and advantages of each combination tested. Different measurement techniques were used; subjective information, production rates – P, working postures (head, neck and trunk inclination angles in the kinematic stage) were measured.

Sewing operators’ sitting posture angles in the kinematic stage were affected more or less by their anthropometric measurements and the type of sewing machine. These two factors should be taken into consideration when ergonomically redesigning the sewing machine workstation.

A new ergonomically redesigned sewing machine table can be incorporated into garment factories, taking into consideration the BMI of the operators to improve their productivity and reduce musculoskeletal disorder complaints due to incorrect operators’ posture.

An important correlation was found between the sewing operator’s anthropometric body measurement – BMI and the type of sewing machine (with significant R^2 = 0.8385 and 0.9764 with both the head and neck inclination angles O_H, O_N, respectively).

Quantitative fabric‐needle‐sewing machine interactions at different speeds have been used to construct qualitative rules mapping fabric properties to optimum sewing machine settings for the next generation of “intelligent sewing machines”, using model free estimation. The inference procedures of fuzzy logic have been implemented in a neural network to allow for optimization of output membership functions and subsequently, self‐learning. The technique is successfully applied to industrial lockstitch and overlock sewing machines. Optimum settings were achieved under static and dynamic machine conditions from the properties of difficult fabrics and compensation for mishandling by the operator over the speed range of the sewing machine.

Two hypotheses concerning two variables that potentially influence the “add/drop” foreign market decisions of U.S. exporters of sewing machines are developed and empirically tested. The variables are import market potential, and a surrogate measure of import market competitiveness. A third variable, concerning a developing country’s “trade regime” – Import Substituting, Export Promoting (Bhagwati, 1978) – is employed as a control variable in the tests. The two hypotheses are confirmed, and the results shed light on how U.S. exporters of sewing machines should analyze data on the three variables en route to adjusting their respective portfolios of export markets in a context of making add/drop foreign market decisions. The results of the research potentially contribute to three different literatures: the international marketing literature, the competitiveness literature and the “trade regime” literature in international economics.

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.

Bar‐tacking is a specialized sewing stitch designed to provide immense tensile strength to the garment which requires a high‐speed precision bar‐tacking sewing machine. This paper aims to present an event‐driven multi‐axis cooperative control method for a bar‐tacking sewing machine.

The control method consists of two parts: the multi‐axis cooperative control and the needle stop positioning control. The challenges include the high speed and the precision. For example, the needle must stop at a set position in milliseconds.

The presented multi‐axis cooperative control can ensure the high speed response and the precision of the cooperative control. The needle stop positioning control is based on a combination of the velocity control and the position control with velocity feed‐forward and limitation.

The bar‐tacking sewing machine requires high‐speed start and stop response and coordination of displacement and velocity only at some given points. Therefore, the conventional multi‐axis cooperative control methods are not suitable. In addition, it requires high‐speed precision control under varying loading conditions.

While there are a number of commercial textile machines available in the market, designing a smart bar‐tacking sewing machine with good speed and precision performance remains a challenge.

The bar‐tacking sewing machine requires highly accurate multi‐axes cooperative control. The presented event‐driven multi‐axis control method is effective. It has not only the required high accuracy but also the fast time response.

A neuro‐fuzzy control model has been devised for the next generation of so‐called “intelligent sewing machines”. The model incorporates discrimination of material characteristics to be stitched by automatic determination of their properties. The fabric/machine interactions at different speeds have been computed in the form of linguistic rules of a fuzzy model and implemented in a neural network to allow for optimization of fuzzy membership functions and, subsequently, self‐learning. The model is successfully applied to an instrumented industrial sewing machine.

Despite the globalization and internalization of competition and surplus of apparel production, high labour costs and other economic pressures, apparel products are still being produced using traditional methods and machinery, the mechanics of which have not fundamentally changed since the seventeenth century, even nowadays when the materials produced are very flexible and diverse in texture and properties. In developing the industry further, the nature of interaction between machinery, fabric and operatives has to be taken into account, and this poses some real problems if one has to put forward realistic solutions for future industrial development. It is therefore important to be able to take into consideration fabric/machine/human interactions during the manufacturing process in order to propose the next generation of manufacturing systems which is much needed in the current apparel industry. Reports on findings in the area of intelligent garment manufacture which is a means of introducing flexibility, quality, production efficiency and maximization of resources to the apparel industry. Primarily emphasizes the importance of fabric properties and their interaction with the whole manufacturing process, the labour force and especially with sewing. In order to achieve this, applies computational intelligence and engineering to research, develop and implement intelligent textile and apparel environments, and introduce desired flexibility into the whole area of textile and apparel processes, especially in terms of quick response (QR) and just in time (JIT).

The purpose of this paper is to present, an optimization problem based on the imperialistic competitive algorithm (ICA) approach for optimizing the needle velocity and variation of needle acceleration in a link drive mechanism of a sewing machine. The optimal geometry of the link drive has been achieved using a non-linear optimization procedure.

As an important study in this case, the authors might refer to a previous work in which they introduced the possibility of replacing the slider-crank mechanism, that is typically used in sewing machines, with a link drive mechanism. The authors regenerate the optimization problem by modifying the objective function and follow a novel optimization method based on the ICA to overcome the drawbacks of that work. In addition, further modification of the objective function with respect to the variation of needle acceleration is applied to assure smooth movement of the needle during sewing process.

The results showed a significant improvement with respect to the optimization of needle velocity and variation of needle acceleration in comparison to that previous work. This clearly justifies the efficiency and reliability of the optimization formulation based on the ICA approach.

Needle temperature is considered as an effective parameter on sewing process efficiency and stitch quality. Needle heat generated during sewing process is directly related to needle velocity in penetration zone which in turn depends on the needle driver mechanism of sewing machine. According to literature survey, few researches have focussed to design a driver mechanism of the sewing machine to reduce the generated needle heat. This mechanism has the ability of reducing the penetration velocity of the needle without affecting sewing speed which consequently can reduce the needle heat generated during needle penetration. The work here is novel regarding implementation of optimization algorithm for this mechanism.

The purpose of this paper is to investigate the effect of joint clearance on the behavior of a needle driver mechanism (a slider-crank linkage) of a typical sewing machine with an imperfect joint between the coupler and the slider (including needle).

In order to model the clearance, the momentum exchange approach is used. The Lankarani and Nikravesh’s continuous contact force model is used to model the contact force, and the modified Coulomb’s friction law represents the friction between sliding members. The penetration force applied on the needle by fabric is chosen based on an experimental data in the literature. The dynamic response is validated for the existing properties in the literature without considering the penetration force.

It is shown that the clearance joint made considerable effect on the dynamic response of the system. The rough changes of the needle acceleration and jerk are obvious. The base reaction force changed roughly and did not vary as smooth as that of the mechanism with ideal joint. So, clearance joint in the mechanism could lead to an undesirable vibration in the system. Furthermore, the crank driver must provide a non-smooth moment on the crank to keep the crank rotational velocity constant. Moreover, reducing the clearance size sufficiently could make the dynamic response closer to that of the mechanism with ideal joint. In addition, smoother crank moment could be required if the clearance size is reduced sufficiently. Furthermore, the rough change of the base reaction force which can represent the vibration caused by the mechanism on the fixed frame could be reduced if the clearance size is small enough.

Lockstitch sewing machine is one of the most common apparel industrial machines. The needle driver mechanism of a sewing machine could have an important role for proper stitch forming. On the other hand, clearances are inevitable in assemblage of mechanisms to allow the relative motion between the members. This clearance is due to machining tolerances, wear, material deformations, and imperfections, and it can worsen mechanism performance such as precision, dynamic behavior and vibration. Unfortunately, despite the importance of the dynamic behavior of the needle driver mechanism from practical point of view, very little publications have focused especially on the investigation of the effect of clearance joint on the dynamic behavior of the sewing machine which could lead to undesired vibration of the system and shorter lifetime as a result. In this paper, the dynamic behavior of the system including, needle velocity and acceleration, crank moment and base reaction force was compared with that of the ideal mechanism. Finally, the effect of clearance size on the dynamic behavior of the system was investigated.

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.