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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).

The primary purpose of this study is to illustrate a practical approach for industrial work process design that, in an integrative manner, captures essential concerns from different parties associated with manufacturing. It aims explicitly to incorporate utility expectation from the perspectives of operational managers, floor workers, and financial planners into the decision making process.

Through a real industrial scenario, the case study illustrates the use of a Bayesian belief network (BBN)‐based expert system and influence diagram in work process design. What‐if analysis is performed. Statistical tests are then used to benchmark and validate the experimental results and actual data.

The results suggest that the proposed BBN framework is effective in modeling and solving the work design problem. The findings can draw meaningful insights into the adoption and capacity of BBN in the fields of ergonomics, worker health management, and performance improvement.

Practically, the industrial problem is to compare the new stand‐up sewing cells against the traditional sit‐down sewing layout while taking into consideration of ergonomic effect (repetitive motion injury (RMI) likelihood), floor space (SF), yield (%), and cost ($). The study illustrates the use of an expert system and influence diagram to evaluate different alternatives for ergonomic work design in production process.

The results of this study can potentially improve health safety management and worker ergonomics.

The paper is among the few systematic studies that have applied BBN and influence diagram to production ergonomics and worker health management. A methodological framework utilizing these probabilistic reasoning techniques are developed. This new framework can capture essential concerns from different parties in manufacturing.

The purpose of this study was to explore the dimensions of apparel manufacturing strategy (i.e. cost, quality, flexibility, delivery time) and their relationship to style and sewing systems. U.S. apparel producers are seeking strategies that will make their production competitive to production in low wage countries. Two style types were defined: new styles and standardized styles. Results indicated that the production of new styles of apparel is related to the manufacturing dimensions of quality and delivery. The standardized style is related to the dimension of cost. Significant associations were also found between the multiple‐sewing systems used by plants and dimensions of manufacturing strategy (cost, delivery, and flexibility).

Reports on a study for which data were generated from responses to a survey by 132 US apparel manufacturers in 1993. States that the purpose of the study was to determine the extent to which companies were investing in ergonomic equipment as a prevention strategy, and whether there was a relationship between such investments and positive results in four areas: increased productivity, increased quality, decreased workers’ compensation costs and improved employee morale. Using chi‐square analysis, a significant difference was found for those who invested in automatic sewing equipment in both increased productivity and increased quality. Provides justification for companies to invest in ergonomic equipment because of additional benefits.

Defects in fabric have been and continue to be a major source of seconds in finished garments. These defects persist despite several visual inspections and intensive efforts to remove defective parts during sewing operations. The increased use of automation in assembly steps will intensify the problem of detection and removal of fabric defects in cut‐parts. Describes a workstation utilizing machine vision which has been designed and constructed to detect and remove defective cut‐parts prior to the initiation of assembly operations. The workstation employs two vision systems — an area camera and a line camera — to inspect parts on a conveyor belt both statically and dynamically. The colour of the parts is also determined and the area and perimeter are measured to detect improperly cut parts. The acceptable parts are then stacked in a manner suitable for input to an automated sewing station. The workstation should permit placing into the assembly operations a set of defect‐free, properly‐cut and colour‐matched parts. It is estimated that this cut‐part inspection system will reduce defects in finished garments by approximately 50 per cent and should greatly simplify the labour‐intensive and costly fabric defect control systems currently in place in most apparel plants.

The purpose of this paper is to find the most efficient assembly line balancing solution across many heuristic line balancing methods, in assistance with a developed computer program.

In this paper, assembly line balancing problem was analyzed using t-shirt and knitted pants data. A computer program using MATLAB software for the solution of assembly line balancing problems has been developed. In this study, following heuristic assembly line balancing methods were applied: Hoffman method; position weight method; COMSOAL method; and Kilbridge and Wester method. A MATLAB program has been developed by taking into account of theoretical solution of all these methods. Later the program is developed further by analyzing solutions made manually and is made to verify the developed program.

Pre-studies which were conducted in order to decide which programming language would be the best choice for line balancing methods’ application came out with the result that MATLAB, from between C, C++, C# and Java, would be the best software choice. The main reason for this choice is that MATLAB is a powerful matrix operation software with a powerful user interface designing tool and has the tools to make development program to be used universally in every computer.

When the researches were investigated, it is clearly seen that, this study is the first research on using computer program for solving assembly line balancing problem.

Automation and the new buzzword, “Industry 4.0”, have dominated the media headlines in recent months. In this scenario, apparel manufacturers should not only install automatic machines but also standardise them based on specific industry requirements, and precise measures are required for daily target demands.

This study demonstrates the application of Predetermined Motion and Time System (PMTS) tools in various automatic and semiautomatic machines to obtain higher productivity and the highest utilisation percentage of operator and automats between the 1:1 and 1:2 man vs machine configuration models. In this study, timeSSD® was used to calculate the micro motions of humans. In addition, a video annotation and modelling software Tracker was used to calculate high-speed machine movements with loading frames of 30 FPS.

After the implementation of PMTS tools, it was found that for a 1:1 man vs machine configuration, the operator utilisation is 75% per shift and the operator idle time is 50% per cycle time, and the operator is sitting idle for 2 h per 8 h of shift. So, there is scope to improve the utilisation and idle time of operator.

With the PMTS software, an industrial engineer professional with knowledge of the micromotion economy can only calculate micromotion.

Exploring the first time in the world to establish standard allowed minute (SAM) of a partly automated single-unit sewing machine with partial human intervention and a semiautomatic machine. Theoretical underpinnings indicate that manufacturers use the experience to determine the SAM of any operation over time, necessitating this work to calculate standard minutes automatically.

Summarizes the work conducted on the research and development of machinery to automate the turning and pressing of collars and their automated assembly to the shirt‐collar bands sponsored by the Defense Logistics Agency. This research and development has involved the conceptualization, design and development of proof‐of‐concept shirt‐collar turning and pressing processes based on “double‐point turning and pressing” and their systems integration into a robot‐assisted apparel workstation. The work has also involved a second activity to understand, design and develop technology which can temporarily fold and crease single‐ply shirt‐collar bands for continuous automated assembly of shirt collars and collar‐bands. This work has involved the understanding of the folding and creasing properties of various apparel fabrics, the evaluation of two technology approaches for accomplishing this task, and the attachment machine control technology for high‐speed collar and collar‐band joining.

Garment manufacturing is a traditional industry with global competition. The most critical part is streamline, as it generally involves a great number of operations. The purpose of this paper is to, based on the model of group technology (GT), sum up the methods of assembly line optimization to optimize the streamline, so that the machines of the workstation can perform the assigned tasks with a balanced loading.

In this paper, the methods of obtaining and optimizing data includes literature, research and optimization methods of basing on GT model. The main direction of literature has two aspects: Lean production theory and streamline assignment. Research mainly concludes three aspects: research place, research object and the research content. The method of time determination is averaging the testing values of repeated measurements. Optimization methods of basing on GT model mainly include combination of the same type of technologic processes in sequence, combination of independent branch process, the combination of mainstream and branch processes and offside combination of the same type of processes.

After optimization, in the utilization rate of equipment: hanging system ratio was increased from 22.95 to 62.12 percent, which greatly improved the utilization rate of enterprise equipment. In equipment layout: hanging equipment layout was turned linear type into “U” type, which realized the synchronization of production. GT model will be well applied in the garment production streamline. Compared with other enterprises, A company has large garment hanging system, which reflects the advanced, comprehensive, representative. Therefore, the paper applied optimization methods to trousers, production efficiency has been improved greatly, the utilization rate of equipment is promoted and reworking phenomenon is reduced greatly.

Through the optimization of the production process and equipment layout, the A company’s compiling efficiency has been greatly improved, but how can the system become computerized, accurately and intelligence, which has been an important direction of research now.

By optimizing, it is fully proved that applying GT to the streamline optimization is feasible. GT is an important branch of Lean production, summing up the optimization methods basing on the GT model to optimize the streamline not only enriches the relevant theory research, but also provides a theoretical basis for the practical production. GT model not only can be used in the shirt production process, as for other production processes, for example, trousers, skirts can also be widely applied, which realizes the theory application in the practical production.

The originality of this paper is that through the analysis of the model of GT, the paper sums up the methods of assembly line optimization to optimize the streamline. Although the model of GT is used widely in electronics, automobile and industry, it is relatively weak in the optimization of garment production line, there are not many literatures on practical application of group technology in the clothing. Besides, the paper is applied to practical production, which not only can improve production efficiency, but also make the theoretical research have basis and combine the theory and practical production.

Investigates the use of robotic sewing systems for assembling car headrest covers at Moll, a German company. Notes the key role of robots in the production process by virtue of their flexible movement. Reports on increased use of computerization by the company and mentions a current research project looking at the use of robotic sewing systems aimed at the clothing industry, a much greater market.