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Ultrasonic welding is an emerging apparel manufacturing technique. However, the applications are widely explored in the field of technical textiles, with less exploration in the apparel endues. The purpose of this study is to explore the application of ultrasonic welding in apparel by analyzing the impacts of different parameters.

This study analyzed the influence of ultrasonic welding parameters, including pressure, welding speed and ultrasonic power on the seam performances (seam strength, seam bursting strength, seam thickness and seam stiffness). The parameters are optimized using Box–Behnken experimental design to achieve better seam performances.

The properties of ultrasonic seams are influenced by welding and fabric properties. Ultrasonically welded seams showed better performances in the case of comfort properties of seams, whereas the functional properties are lesser compared to conventional seams.

The findings of the research clearly outline the level of influence of different parameters on the performance of the ultrasonically welded seams in knitted fabrics, which can greatly help in applying ultrasonic welding manufacturing methods in apparel manufacturing.

The purpose of this study is to establish a method for accurately extracting torch and seam features. This will improve the quality of narrow gap welding. An adaptive deflection correction system based on passive light vision sensors was designed using the Halcon software from MVtec Germany as a platform.

This paper proposes an adaptive correction system for welding guns and seams divided into image calibration and feature extraction. In the image calibration method, the field of view distortion because of the position of the camera is resolved using image calibration techniques. In the feature extraction method, clear features of the weld gun and weld seam are accurately extracted after processing using algorithms such as impact filtering, subpixel (XLD), Gaussian Laplacian and sense region for the weld gun and weld seam. The gun and weld seam centers are accurately fitted using least squares. After calculating the deviation values, the error values are monitored, and error correction is achieved by programmable logic controller (PLC) control. Finally, experimental verification and analysis of the tracking errors are carried out.

The results show that the system achieves great results in dealing with camera aberrations. Weld gun features can be effectively and accurately identified. The difference between a scratch and a weld is effectively distinguished. The system accurately detects the center features of the torch and weld and controls the correction error to within 0.3mm.

An adaptive correction system based on a passive light vision sensor is designed which corrects the field-of-view distortion caused by the camera’s position deviation. Differences in features between scratches and welds are distinguished, and image features are effectively extracted. The final system weld error is controlled to 0.3 mm.

The purpose of this study is to optimize and improve conventional welding using EMF assisted technology. Current industrial production has put forward higher requirements for welding technology, so the optimization and improvement of traditional welding methods become urgent needs.

External magnetic field assisted welding is an emerging technology in recent years, acting in a non-contact manner on the welding. The action of electromagnetic forces on the arc plasma leads to significant changes in the arc behavior, which affects the droplet transfer and molten pool formation and ultimately improve the weld seam formation and joint quality.

In this paper, different types of external magnetic fields are analyzed and summarized, which mainly include external transverse magnetic field, external longitudinal magnetic field and external cusp magnetic field. The research progress of welding behavior under the effect of external magnetic field is described, including the effect of external magnetic field on arc morphology, droplet transfer and weld seam formation law.

However, due to the extremely complex physical processes under the action of the external magnetic field, the mechanism of physical fields such as heat, force and electromagnetism in the welding has not been thoroughly analyzed, in-depth theoretical and numerical studies become urgent.

Breastfeeding bras are functional garments having specialised features to facilitate easy breastfeeding. The purpose of this paper is to design and develop breastfeeding bra prototypes with a focus on the needs of the user.

The method uses gathering breastfeeding user requirements through consumer surveys. The subsequent data analysis and a literature review provided the basis for feature selection for the breastfeeding bra designs. The bras were constructed using ultrasonic welding and bonding techniques. The mechanical properties of the fabric were measured. Lastly, the designed bras underwent a wear trial to evaluate their effectiveness.

The bra prototypes use non-restrictive designs and aesthetically appealing construction methods with smooth panel joints. The results of the wear trial demonstrated the successful incorporation of user requirements in the final product.

The insights from user-need mapping through consumer surveys and a literature review provided the basis for the new design of breastfeeding bras using stitchless technology. The developed bras have unique features that have not been explored earlier in this product category.

The purpose of this paper is to demonstrate the impact of the welding sequence on the substrate plate distortion during the wire and arc additive manufacturing (WAAM) process. This paper also aims to show the capability of finite element simulations in the prediction of those thermally induced distortions.

An experiment was conducted in which solid aluminum blocks were manufactured using two different welding sequences. The distortion of the substrates was measured at predefined positions and converted into bending and torsion values. Subsequently, a weakly coupled thermo-mechanical finite element model was created using the Abaqus simulation software. The model was calibrated and validated with data gathered from the experiments.

The results of this paper showed that the welding sequence of a part significantly affects the formation of thermally induced distortions of the final part. The calibrated simulation model was able to capture the different distortion behavior attributed to the welding sequences.

Within this work, a simulation model was developed capable of predicting the distortion of WAAM parts in advance. The findings of this paper can be used to improve the design of WAAM welding sequences while avoiding high experimental efforts.

This paper aims to propose a lightweight, high-accuracy object detection model designed to enhance seam tracking quality under strong arcs and splashes condition. Simultaneously, the model aims to reduce computational costs.

The lightweight model is constructed based on Single Shot Multibox Detector (SSD). First, a neural architecture search method based on meta-learning and genetic algorithm is introduced to optimize pruning strategy, reducing human intervention and improving efficiency. Additionally, the Alternating Direction Method of Multipliers (ADMM) is used to perform structural pruning on SSD, effectively compressing the model with minimal loss of accuracy.

Compared to state-of-the-art models, this method better balances feature extraction accuracy and inference speed. Furthermore, seam tracking experiments on this welding robot experimental platform demonstrate that the proposed method exhibits excellent accuracy and robustness in practical applications.

This paper presents an innovative approach that combines ADMM structural pruning and meta-learning-based neural architecture search to significantly enhance the efficiency and performance of the SSD network. This method reduces computational cost while ensuring high detection accuracy, providing a reliable solution for welding robot laser vision systems in practical applications.

Stitching is the traditional method of creating seams using needles and threads. However, this is not useful for waterproof breathable garments as needle holes allow water to penetrate inside the garment, compromising its functionality. This study aims to investigate different techniques for covering the needle holes formed during stitching to achieve a seam that is waterproof, durable and functionally effective.

This study investigates different methods to cover needle holes formed during stitching with the help of seam tape, seam grip adhesive and fuser thread. The emphasis is on evaluating the seam characteristics, including seam strength, seam efficiency, puckering, bending stiffness and resistance to water penetration. Statistical analysis involves the use of the Shapiro–Wilk test, Levene statistic, one-way ANOVA and Tukey’s HSD and Tamhane post-hoc tests.

The experimental results suggest that seam tape is effective in enhancing water resistance, seam strength and seam efficiency, but it contributes to stiffness and aesthetically degrades seams due to increased puckering. Meanwhile, the use of fuser thread presents an alternative, exhibiting improved waterproof properties compared to regular stitching. It offers more flexibility and less puckering compared to seam tape.

This study contributes novel insights by shifting the focus from alternative seaming methods such as bonding and welding, to enhancing traditional stitching for waterproof seam construction. While prior research primarily explored alternatives to stitching, this study uniquely addresses the effectiveness of different techniques in covering needle holes to achieve waterproof seams. The findings provide valuable information for enhancing the functionality of stitched seams in the production of waterproof breathable garments.

This paper aims to develop a specific type of mobile nonrigid support friction stir welding (FSW) robot, which can adapt to aluminum alloy trucks for rapid online repair.

The friction stir welding robot is designed to complete online repair according to the surface damage of large aluminum alloy trucks. A rotatable telescopic arm unit and a structure for a cutting board in the shape of a petal that was optimized by finite element analysis are designed to give enough top forging force for welding to address the issues of inadequate support and significant deformation in the repair process.

The experimental results indicate that the welding robot is capable of performing online surface repairs for large aluminum alloy trucks without rigid support on the backside, and the welding joint exhibits satisfactory performance.

Compared with other heavy-duty robotic arms and gantry-type friction stir welding robots, this robot can achieve online welding without disassembling the vehicle body, and it requires less axial force. This lays the foundation for the future promotion of lightweight equipment.

The designed friction stir welding robot is capable of performing online repairs without dismantling the aluminum alloy truck body, even in situations where sufficient upset force is unavailable. It ensures welding quality and exhibits high efficiency. This approach is considered novel in the field of lightweight online welding repairs, both domestically and internationally.

The purpose of this study is to address the welding demands within large steel structures by presenting a global spatial motion planning algorithm for a mobile manipulator. This algorithm is based on an independently developed wall-climbing robot, which comprises a four-wheeled climbing mobile platform and a six-degree-of-freedom robotic manipulator, ensuring high mobility and operational flexibility.

A convex hull feasible domain constraint is developed for motion planning in the mobile manipulator. For extensive spatial movements, connected sequences of convex polyhedra are established between the composite robot’s initial and target states. The composite robot’s path and obstacle avoidance optimization problem are solved by constraining the control points on B-spline curves. A dynamic spatial constraint rapidlye-xploring random trees-connect (RRTC) motion planning algorithm is proposed for the manipulator, which quickly generates reference paths using spherical spatial constraints at the manipulator’s end, eliminating the need for complex nonconvex constraint modeling.

Experimental results show that the proposed motion planning algorithm achieves optimal paths that meet task constraints, significantly reducing computation times in task conditions and shortening operation times in non-task conditions.

The algorithm proposed in this paper holds certain application value for the realization of automated welding operations within large steel structures using mobile manipulator.

Welding is a widely used manufacturing process in many industries. The process consumes a lot of energy and resources, pollutes the environment, and emits gases and fumes into the atmosphere that are dangerous to human health. There are various welding processes, and the suitable welding process is usually chosen based on cost, material, and conditions. Subjectivity is the most significant impediment to selecting an optimal process. As a result, it is critical to develop the appropriate set of criteria, use the best tool and methodology, and collect sufficient data. This study examines the sustainability of welding processes and their environmental impact.

The welding process’s sustainability was examined and discussed in general, considering the technological specifics of each welding process, physical performance, and environmental, economic, and social effects. The study investigates the environmental impact of MMAW, GMAW, and GTAW/GMAW processes through experimental work and LCA methodology.

MMAW is the most environmentally harmful technology, whereas GMAW has the least impact. The GTAW/GMAW process outperformed the other processes in terms of yield stress, but the analyses revealed that it had a greater environmental impact than GMAW.

The study provides an environmental impact summary and demonstrates the effects of welding parameters and processes. This gives users an understanding of choosing the best welding technique or making the process more environmentally friendly. These recommendations help policymakers identify hot spots and implement the right plans to achieve more sustainable manufacturing.