Search Results (684)

Friction stir lap welding has been utilized across research and industry for over a decade. However, difficulties in welding in the lap configuration without an interface-related defect have prevented the process from moving beyond low feed rates (generally less than 1.5 m per minute). As a means of making a huge leap in welding productivity, this study will evaluate friction stir welds made at 10 m per minute (mpm), detailing the changes to tool geometries and weld parameters that result in fully consolidated welds. Characterization of the subsequent material properties, namely through optical microscopy, CT scanning, microhardness testing, tensile and fatigue testing, hermetic seal pressure tests, and electron backscattered diffraction, is presented as a means of demonstrating the quality and repeatability of friction stir lap welds made at 10 mpm. Fully consolidated welds were produced at spindle speeds 5.5% faster and 2.9% slower than nominal values and weld depths ranging from 1% shallower to 8.2% deeper than nominal values. Additionally, the loading direction of the weld had a significant impact on tensile properties, with the advancing side of the weld measured to be 16% stronger in lap-shear tensile and 289% fatigue life improvement under all loading conditions measured when compared to the retreating side. Full article

The article presents a comprehensive review of key issues and challenges related to enhancing the durability of hot forging tools. It discusses modern strategies aimed at increasing tool life, including modifications to tool materials, heat treatment, surface engineering, tool and die design, die geometry, tribological conditions, and lubrication. The review is based on extensive literature data, including recent publications and the authors’ own research, which has been implemented under industrial conditions at the modern forging facility in Forge Plant “Glinik” (Poland). The study introduces original design and technological solutions, such as an innovative concept for manufacturing forging dies from alloy structural steels with welded impressions, replacing traditional hot-work tool steel dies. It also proposes a zonal hardfacing approach, which involves applying welds with different chemical compositions to specific surface zones of the die impressions, selected according to the dominant wear mechanisms in each zone. General guidelines for selecting hardfacing material compositions are also provided. Additionally, the article presents technological processes for die production and regeneration. The importance and application of computer simulations of forging processes are emphasized, particularly in predicting wear mechanisms and intensity, as well as in optimizing tool and forging geometry. Full article

To address the issues of hydrogen embrittlement, creep, and fatigue that commonly occur in the welds of hydrogen production reactor operating under hydrogen exposure, high temperature and high pressure, this study proposes adding Si and Mo as reinforcing elements to the welding materials to enhance weld performance. Given the varying performance requirements of different weld layers in the stacked weld, a gradient performance optimization method for the stacked weld of hydrogen production reactors based on the response surface methodology (RSM)–genetic algorithm (GA) is proposed. Using tensile strength, the hydrogen embrittlement sensitivity index, fatigue strain strength, creep rate and weld performance evaluation indices, a high-precision regression model for Si and Mo contents and weld performance indices was established through RSM and analysis of variance (ANOVA). A multi-objective optimization mathematical model for gradient improvement of the stacked weld was also established. This model was solved using a GA to obtain the optimal element content combination added to the welding wire and the optimal weld thickness for each weld layer. Finally, submerged arc welding experiments of the stacked weld were conducted according to the optimization results. The results show that the tensile strength of the base layer, filling layer and cover layer of the stacked weld increased by 5.60%, 6.16% and 4.53%, respectively. Hydrogen embrittlement resistance increased by 70.56%, 52.40% and 45.16%, respectively. The fatigue and creep resistance were also improved. The experimental results validate the feasibility and accuracy of the proposed optimization method. Full article

The laser heterogeneous lap welding of nickel-plated steel and Cu sheets has been investigated in this study. The YAG (Yttrium-Aluminum-Garnet) laser beam only penetrates the upper Ni-plated steel sheet and cannot weld the bottom Cu sheet due to the low absorption coefficient of the YAG laser beam. Incorporating a blue-light and fiber laser into the coaxial laser beam significantly improves the quality of the weld fusion zone. The fiber laser beam can penetrate the upper nickel-plated steel sheet, and the blue-light laser beam can melt the bottom copper sheet. Introducing the blue-light laser to the coaxial laser beams overcomes the low reflectivity of the bottom copper sheet. The fiber/blue-light coaxial laser continuous welding can achieve the best integrity and defect-free welding. It shows potential in the mass production of the next generation of lithium batteries. Full article

Zirconium-89 (⁸⁹Zr) is a widely used radionuclide in immune-PET imaging due to its physical decay characteristics. Despite its importance, the production of ⁸⁹Zr radiopharmaceuticals remains largely manual, with limited cost-effective automation solutions available. To address this, we developed an automated system for the agile and reliable production of radiopharmaceuticals. The system performs transmutations, dissolution, and separation for a range of radioisotopes. Steps in the production of ⁸⁹Zr-oxalate are used as an exemplar to illustrate its use. Three-dimensional (3D) printing was exploited to design and manufacture a target holder able to include solid targets, in this case an ⁸⁹Y foil. Spot welding was used to attach ⁸⁹Y to a refractory tantalum (Ta) substrate. A commercially available CPU chiller was repurposed to efficiently cool the metal target. Furthermore, a commercial resin (ZR Resin) and compact peristaltic pumps were employed in a compact (10 × 10 × 10 cm³) chemical separation unit that operates automatically via computer-controlled software. Additionally, a standalone 3D-printed unit was designed with three automated functionalities: photolabelling, vortex mixing, and controlled heating. All components of the assembly, except for the target holder, are housed inside a commercially available hot cell, ensuring safe and efficient operation in a controlled environment. This paper details the design, construction, and modelling of the entire assembly, emphasising its innovative integration and operational efficiency for widespread radiopharmaceutical automation. Full article

As a key component in the hydraulic brake system of automobiles, the brake joint directly affects the braking performance and driving safety of the vehicle. Therefore, improving the quality of brake joints is crucial. During the processing, due to the complexity of the welding material and welding process, the weld seam is prone to various defects such as cracks, pores, undercutting, and incomplete fusion, which can weaken the joint and even lead to product failure. Traditional weld seam detection methods include destructive testing and non-destructive testing; however, destructive testing has high costs and long cycles, and non-destructive testing, such as radiographic testing and ultrasonic testing, also have problems such as high consumable costs, slow detection speed, or high requirements for operator experience. In response to these challenges, this article proposes a defect detection and classification method for laser welding seams of automotive brake joints based on machine vision inspection technology. Laser-welded automotive brake joints are subjected to weld defect detection and classification, and image processing algorithms are optimized to improve the accuracy of detection and failure analysis by utilizing the high efficiency, low cost, flexibility, and automation advantages of machine vision technology. This article first analyzes the common types of weld defects in laser welding of automotive brake joints, including craters, holes, and nibbling, and explores the causes and characteristics of these defects. Then, an image processing algorithm suitable for laser welding of automotive brake joints was studied, including pre-processing steps such as image smoothing, image enhancement, threshold segmentation, and morphological processing, to extract feature parameters of weld defects. On this basis, a welding seam defect detection and classification system based on the cascade classifier and AdaBoost algorithm was designed, and efficient recognition and classification of welding seam defects were achieved by training the cascade classifier. The results show that the system can accurately identify and distinguish pits, holes, and undercutting defects in welds, with an average classification accuracy of over 90%. The detection and recognition rate of pit defects reaches 100%, and the detection accuracy of undercutting defects is 92.6%. And the overall missed detection rate is less than 3%, with both the missed detection rate and false detection rate for pit defects being 0%. The average detection time for each image is 0.24 s, meeting the real-time requirements of industrial automation. Compared with infrared and ultrasonic detection methods, the proposed machine-vision-based detection system has significant advantages in detection speed, surface defect recognition accuracy, and industrial adaptability. This provides an efficient and accurate solution for laser welding defect detection of automotive brake joints. Full article

The study aims to increase productivity in the cold room door manufacturing industry by addressing non-value-adding operations, identifying bottlenecks, and reducing processing time through digital twin (DT)-based simulation. The goal is to eliminate the need for supply chain outsourcing and increase overall efficiency. The research involves developing a DT of the existing production process for five distinct categories of cold room doors: flush door, single door, double door, face-mounted door, and sliding door. Simulation was used to uncover problems at multiple stations, encompassing curing, welding, and packing. Lean principles were used to identify the causes of inefficiency, and the process was improved using TRIZ principles. These changes produced a 42.90% improvement in productivity, a 20% dependence reduction on outsourcing and an increase of 10.5% added inventory to the shortage demand level. The approach presented is provided for a particular manufacturer of cold room doors, but the methods and techniques used are generally applicable to other manufacturing companies to support systematic innovation. Combining DT simulation, lean techniques and TRIZ principles, this study presents a strong approach to addressing the productivity challenges in manufacturing. The incorporation of these methods has brought considerable operational efficiency and has minimised dependency on external outsourcing. Full article

Background/Objectives: Additive manufacturing (AM) enables the production of cementless acetabular cups with porous surfaces that facilitate early osseointegration. Directed energy deposition (DED), a form of AM, allows the direct welding of porous structures onto metal substrates without requiring a vacuum environment, offering advantages over conventional powder bed fusion methods. Despite growing interest in DED, no prospective clinical studies evaluating DED-based acetabular components have been published to date. This study assessed short-term outcomes of a DED-based 3D-printed acetabular cup in total hip arthroplasty (THA). Methods: A total of 120 patients who underwent primary cementless THA using the Corentec Mirabo Z^® acetabular cup were prospectively enrolled. Among them, 124 hips from 100 patients who had completed a minimum of 24 months of follow-up were included in the analysis. Clinical outcomes were assessed using the Harris hip score (HHS), WOMAC, EQ-5D-5L, and pain NRS. Radiographic evaluation included measurements of cup position, osseointegration, and detection of interfacial or polar gaps on CT and plain radiographs. Implant-related complications were also recorded. Results: At a mean follow-up of 34.6 months, the implant survival rate was 99.3%, with one revision due to suspected osseointegration failure. The HHS improved from 56.6 to 91.4 at 24 months, and the NRS decreased from 6.2 to 1.1 (both p < 0.001). Interfacial gaps were observed in 58.1% of cases on CT, though most were <1 mm and not clinically significant. Common postoperative issues included greater trochanteric pain syndrome, squeaking, and iliotibial band tightness, all of which were resolved with conservative treatment. Conclusions: DED-based 3D-printed acetabular cups demonstrated favorable short-term clinical and radiographic outcomes, with high survivorship and reliable early osseointegration in cementless THA. Full article

With the rise of digital twin technology, the application of digital twin technology to industrial automation provides a new direction for the digital transformation of the global smart manufacturing industry. In order to further improve production efficiency, as well as realize enterprise digital empowerment, this paper takes a welding robot arm as the research object and constructs a welding robot arm digital twin system. Using three-dimensional modeling technology and model rendering, the welding robot arm digital twin simulation environment was built. Parent–child hierarchy and particle effects were used to truly restore the movement characteristics of the robot arm and the welding effect, with the help of TCP communication and Bluetooth communication to realize data transmission between the virtual segment and the physical end. A variety of UI components were used to design the human–machine interaction interface of the digital twin system, ultimately realizing the data-driven digital twin system. Finally, according to the digital twin maturity model constructed by Prof. Tao Fei’s team, the system was scored using five dimensions and 19 evaluation factors. After testing the system, we found that the combination of digital twin technology and automation is feasible and achieves the expected results. Full article

This study investigates the tribo-mechanical properties of a modified Cu-Cr-Zr alloy with nickel addition, aimed at enhancing its suitability as a resistance spot welding (RSW) electrode material. Two alloy compositions, designated as Sample A (Cu-0.871%Cr-0.156%Zr) and Sample B (modified with 8.94% Ni), were prepared. Microstructural examination revealed a coarse, mixed equiaxed–columnar grain structure in Sample A, while Sample B exhibited a refined dendritic morphology of about 50 μm PDAS, due to nickel-induced solute partitioning, improving microhardness from 72.763 HV to 83.981 HV. The wear behavior was evaluated using a pin-on-disc tribometer with a full factorial design, assessing the effects of rotational speed, load, and time on mass loss and surface roughness. Sample A exhibited increased mass loss and roughness with higher loads and speeds, indicating severe wear. In contrast, Sample B showed reduced mass loss and roughness at higher loads, suggesting a polishing effect from plastic deformation. Design of experiments analysis identified load as the dominant factor for mass loss in Sample A, with speed primarily affecting roughness, while in Sample B, load negatively influenced both responses, with speed–time interactions being significant. These findings highlight the nickel-modified alloy’s superior wear resistance and hardness, making it a promising candidate for RSW electrodes in high-production environments. Full article

The automotive industry is a key pillar of many national economies, and automotive body manufacturing is among the most complex production processes. In the automotive body manufacturing process, quality control and safety assurance are of paramount importance, directly influencing the overall safety performance, structural reliability, and comfort of vehicles. Therefore, it is crucial to analyze the primary factors that influence quality and safety during the car body manufacturing process. The study first focuses on four key processes of car body manufacturing—stamping, welding, painting, and assembly—using the man, machine, material, method, environment (4M1E) framework to analyze the factors affecting quality and safety. Subsequently, a quality and safety early-warning indicator system is established for the automotive body manufacturing process, followed by a comprehensive analysis of the constructed system. To address the issue of subjectivity in traditional technique for order of preference by similarity to an ideal solution (TOPSIS) evaluation methods, this paper employs the coefficient of variation method for objective analysis of criterion-level indicators, the trapezoidal fuzzy number method for subjective analysis of criterion-level indicators, and establishes a model for optimizing target weight that balances subjective and objective approaches. Furthermore, a relative entropy-based method is applied to comprehensively evaluate criterion-level indicators. This approach reduces the information loss associated with separate weighting schemes and overcomes a known limitation of traditional TOPSIS—its inability to distinguish alternatives that lie equidistant from ideal solutions. Finally, an evaluation model for quality and safety influencing factors in body manufacturing is developed and validated through a case study, demonstrating its feasibility. The results show that the proposed model can effectively identify the key quality and safety influencing factors in the automobile body manufacturing process, guarantee quality control and safety assurance in the body manufacturing process, and thus ensure that the automobile production process meets the quality and safety requirements. Full article

In industrial inspection, X-ray detection methods are the mainstream approach for non-destructive testing (NDT) of weld defects. In response to the issues of insufficient detection accuracy and slow detection speed in existing X-ray weld defect detection (WDD) methods, a lightweight X-ray WDD model, AFD-YOLOv10, based on an improved YOLOv10n, is proposed. First, by introducing variable kernel convolution (AKConv) to replace traditional convolution in the backbone network, the model better adapts to the multi-scale variations in weld defects while maintaining its lightweight nature. Second, a lightweight C2f-Faster module is incorporated into both the backbone and neck networks to achieve a more symmetrical and efficient feature flow, reducing the model’s computational complexity and achieving lightweight design. Finally, dynamic upsampling (DySample) is added to the neck network to enhance the model’s detection accuracy for targets of different scales. This combination of innovations strikes an effective symmetry between model complexity, inference speed, and detection performance. Experimental results show that the improved AFD-YOLOv10 model achieves accuracies, recall rates, and mean average precision values of 90.7%, 88.8%, and 93.8%, respectively, on five typical X-ray weld defects, representing improvements of 4.9%, 4.1%, and 5.3% over the YOLOv10n baseline model, with a 10.1% reduction in model parameters and a 13.3% increase in detection speed. Compared with other existing mainstream detection methods, the AFD-YOLOv10 model not only improves the accuracy of X-ray WDD but also achieves model lightweighting, demonstrating overall detection performance superior to other mainstream algorithms, thus meeting the industrial production requirements for X-ray WDD. Additionally, generalization experiments conducted using a public dataset of surface defects in steel validate the good generalization performance of the AFD-YOLOv10 model. Full article

Magnetic pulse welding (MPW) is a promising solid-state joining process that utilizes electromagnetic forces to create high-speed, impact-like collisions between two metal components. This welding technique is widely known for its ability to join dissimilar metals, including aluminum, steel, and copper, without the need for additional filler materials or fluxes. MPW offers several advantages, such as minimal heat input, no distortion or warping, and excellent joint strength and integrity. The process is highly efficient, with welding times typically ranging from microseconds to milliseconds, making it suitable for high-volume production applications in sectors including automotive, aerospace, electronics, and various other industries where strong and reliable joints are required. It provides a cost-effective solution for joining lightweight materials, reducing weight and improving fuel efficiency in transportation systems. This contribution concerns an application for the automotive sector (body-in-white) and specifically examines the welding of AA6082-T6 aluminum alloy with HC420LA cold-rolled micro-alloyed steel. One of the main aspects for MPW optimization is the determination of the process window that does not depend on the equipment used but rather on the parameters associated with the physical mechanisms of the process. It was demonstrated that process windows based on contact angle versus output voltage diagrams can be of interest for production use for a given component (shock absorbers, suspension struts, chassis components, instrument panel beams, next-generation crash boxes, etc.). The process window based on impact pressures versus impact velocity for different impact angles, in addition to not depending on the equipment, allows highlighting other factors such as the pressure welding threshold for different temperatures in the impact zone, critical transition speeds for straight or wavy interface formation, and the jetting/no jetting effect transition. Experimental results demonstrated that optimal welding conditions are achieved with impact velocities between 900 and 1200 m/s, impact pressures of 3000–4000 MPa, and impact angles ranging from 18–35°. These conditions correspond to optimal technological parameters including gaps of 1.5–2 mm and output voltages between 7.5 and 8.5 kV. Successful welds require mean energy values above 20 kJ and weld specific energy values exceeding 150 kJ/m². The study establishes critical failure thresholds: welds consistently failed when gap distances exceeded 3 mm, output voltage dropped below 5.5 kV, or impact pressures fell below 2000 MPa. To determine these impact parameters, relationships based on Buckingham’s π theorem provide a viable solution closely aligned with experimental reality. Additionally, shear tests were conducted to determine weld cohesion, enabling the integration of mechanical resistance isovalues into the process window. The findings reveal an inverse relationship between impact angle and weld specific energy, with higher impact velocities producing thicker intermetallic compounds (IMCs), emphasizing the need for careful parameter optimization to balance weld strength and IMC formation. Full article

Automated and robotic welding have become standard practices in manufacturing, requiring precise control to maintain weld quality without relying on skilled welders. In Tungsten Inert Gas (TIG) welding, monitoring the weld pool is crucial for ensuring the necessary weld penetration, which is vital for maintaining weld integrity. Real-time observation is essential to prevent defects and improve weld quality. Various sensing technologies have been developed to address this need, with vision-based systems showing particular effectiveness in enhancing welding quality and productivity within the framework of Industry 4.0. This review looks at the latest technologies for monitoring weld pools and bead shapes. It covers methods like using Complementary Metal-Oxide Semiconductors (CMOS) to take clear images of the melt pool for better process identification, Active Appearance Model (AAM) to capture 3D images of the weld pool for accurate penetration measurement, and Charge-Coupled Devices (CCD) and Laser-Induced Breakdown Spectroscopy (LIBS) to analyze plasma spectra and create material composition graphs. Full article

Tungsten Inert Gas (TIG) welding is a widespread welding process used in the industry for high-quality joints. However, this welding process suffers from lower productivity. Activated Tungsten Inert Gas (ATIG) is a variant of the TIG that aims to increase the depth penetration capability of conventional TIG welding. This is achieved by applying a thin coating of activating flux material onto the workpiece surface before welding. This work investigates the effect of the thermophysical properties of individual metallic oxide fluxes on 316L stainless steel weld morphology. Four levels of current intensity (120, 150, 180, 200 A) are considered. The weld speed up to 15 cm/min and arc length of 2 mm are maintained constant. Thirteen oxides were tested under various levels of current intensity in addition to multiple thermophysical properties combinations, and the depth penetration (D) and the aspect ratio (R) were recorded. This process has provided 52 combinations (13 oxides * 4 currents). Based on the numerical observations, linear and nonlinear models for describing the effect of the thermophysical parameters on the weld characteristics were tuned using a particle swarm optimization algorithm. While the linear model provided good prediction accuracy, the nonlinear exponential model outperformed the linear one for the depth yielding a mean absolute percentage error of 17%, a coefficient of determination of 0.8266, and a root mean square error of 0.9665 mm. The inverse optimization process, where the depth penetration ranged from 1.5 mm to 12 mm, thus covering a large spectrum of industries, the automotive, power plants, and construction industries, was solved to determine the envelopes’ lower and upper limits of optimal oxide thermophysical properties. The results that allowed the design of the fluxes to be used in advance were promising since they provided the oxide designer with the numerical ranges of the oxide components to achieve the targeted depths. Future directions of this work can be built around investigating additional nonlinear models, including saturation and dead-zone, to efficiently estimate the effect of the thermophysical properties on the welding process of other materials. Full article