Towards the Fabrication Strategies for Intelligent Wire Arc Additive Manufacturing of Wire Structures from CAD Input to Finished Product

With the increasing demand for freedom of part design in the industry, additive manufacturing (AM) has become a vital fabrication process for manufacturing metallic workpieces with high geometrical complexity. Among all metal additive manufacturing technologies, wire arc additive manufacturing (WAAM), which uses gas metal arc welding (GMAW), is gaining popularity for rapid prototyping of sizeable metallic workpieces due to its high deposition rate, low processing conditions limit, and environmental friendliness. In recent years, WAAM has been developed synergistically with industrial robotic systems or CNC machining centers, enabling multi-axis free-form deposition in 3D space. On this basis, the current research of WAAM has gradually focused on fabricating strut-based wire structures to enhance its capability of producing low-fidelity workpieces with high spatial complexity. As a typical wire structure, the large-size free-form lattice structure, featuring lightweight, superior energy absorption, and a high strength-weight ratio, has received extensive attention in developing its WAAM fabrication process. However, there is currently no sophisticated WAAM system commercially available in the industry to implement an automated fabrication process of wire or lattice structures. The challenges faced in depositing wire structures include the lack of methods to effectively identify individual struts in wire structures, 3D slicing algorithms for the whole wire structures, and path planning algorithms to establish reasonable deposition paths for these generated discrete sliced layers. Moreover, the welded area of the struts within the wire structure is relatively small, so the strut forming is more sensitive and more easily affected by the interlayer temperature. Therefore, the control and prediction of strut formation during the fabricating process is still another industry challenge. Simultaneously, there is also an urgent need to improve the processing efficiency of these structures while ensuring the reliability of their forming result

Bead geometry modeling on uneven base metal surface by fuzzy systems for multi-pass welding

This paper presents a modeling method of weld bead profiles deposited on uneven base metal surfaces and its application in multi-pass welding. The robotized multi-pass tungsten inert gas welding requires precise positioning of the weld beads to avoid welding defects and achieve the desirable welding join since the weld bead shapes depend on the surface of the previously deposited beads. The proposed model consists of fuzzy systems to estimate the coefficients of the profile function. The characteristic points of the trapezoidal membership functions in the rule bases are tuned by the Bacterial Memetic Algorithm during supervised training. The fuzzy systems are structured as multiple-input-single-output systems, where the inputs are the welding process variables and the coefficients of the shape functions of the segments underlying the modeled bead; the outputs are the coefficients of the bead shape function. Each segment surface is approximated by a second-order polynomial function defined in the weld bead’s local coordinate system. The model is developed from empirical data collected from single and multi-pass welding. The performance of the proposed model is compared with a multiple linear regression model. During the experimental validation, first, the individual beads are evaluated by comparing the estimated coefficients of the profile function and other bead characteristics (bead area, width, contact angles, and position of the toe points) with the measurements, and the estimations of a multiple linear regression model. Second, the sequential placement of the weld beads is evaluated while filling a straight Vgroove by comparing the estimated bead characteristics with the measurements and calculating the accumulated error of the filled groove cross-section. The results show that the proposed model provides a good estimation of the bead shapes during deposition on uneven base metal surfaces and outperforms the regression model with low error in both validation cases. Furthermore, it is experimentally validated that the derived bead characteristics provide a suitable measure to identify locations sensitive to welding defects

Manufacturing of Large Metallic Components through Wire and Arc Additive Manufacturing(WAAM)

Metal additive manufacturing have been in trend due to its ability to produce components at reduced cost and low buy-to- y ratio. There are various techniques employed for metal additive manufacturing depending on energy source and type of raw materials used. Based on raw materials, metal additive manufacturing can be classi ed as wire-based, powder-based and sheet-based (laminated object manufacturing). Amongst these three, wire based systems have higher material e ciency and high deposition rates. They also better suited for continious and uncluttered material supply. Hence, they are most suitable for large components. These wire based systems can be used in conjuction to di erent energy sources like Laser, Electron Beam and Arc. WLAM (wire and laser based additive manufacturing), EBAM (electron beam additive manufacturing) and WAAM (wire and arc based additive manufacturing) are examples of each of these energy sources respectively. In this study, Weld-depsotion based WAAM is chosen. The objective of this work is to fabricate large (greater than 1m in size) metallic components using WAAM process. Parameter study, kinematic setup for such working volumes and thermal analysis of deposition process to minimize distortions are some of the related aspects. Sample components in both multi-pass and single-pass geometries were also fabricated successfuly. This work was mainly carried out for mild steel (ER70S6); some priliminary studies on extending this to IN625 are also presented. Overall, this thesis presents the sutiability of WAAM in conjuction with a robotic or CNC type kinemetic setup to produce large metallic components

Robotic welding techniques in marine structures and production processes : a systematic literature review

Robotic welding has garnered significant attention in the maritime industry for its potential to enhance marine structure quality and optimize production processes. This systematic literature review aims to provide a comprehensive overview of the current state of research in robotic welding for marine applications, encompassing marine structures and production processes, following the PRISMA statement and guidelines. The review encompasses various facets, including welding techniques, processed materials, types of robotic welding, technological advancements, potential advantages, and challenges encountered when implementing robotic welding systems in the maritime sector. The results spotlight the pivotal role of gas metal arc welding (GMAW) in propelling robotic welding technology forward, while wire arc additive manufacturing (WAAM) has experienced a notable surge in popularity, signifying its potential to catalyze significant changes in maritime manufacturing processes. Notably, the predominant use of robotic welding centers on carbon steel materials. However, ongoing advancements indicate a growing diversification, with the incorporation of advanced materials like high-strength alloys on the horizon. Additionally, the utilization of 6-axis robot welding in conjunction with fully autonomous systems has emerged as a versatile and potent instrument that has revolutionized welding methodologies across various maritime research domains. Robotic welding provides a number of advantages, such as increased productivity, higher quality, adherence to industry standards, adaptation to confined and dangerous locations, and facilitation of innovative construction techniques. Nevertheless, adoption of this cutting-edge technology is not without challenges. By synthesizing the results from several investigations, this research study offers useful insights into the current knowledge gaps, emerging trends, and future prospects for the growth of robotic welding in maritime applications

Advanced titanium welding in particle physics and aerospace engineering

The quest for answers that will unlock the mysteries of the cosmos and broaden our perception and understanding of the physical laws that govern the universe, demands studying particle collisions of high energies at particle accelerators. Monitoring of these collisions requires complex detectors whose development pushes the boundaries of engineering. In the present study advanced titanium welding is explored in the development of the new ATLAS Inner Tracker detector to be installed in line with the High-Luminosity Large Hadron Collider at CERN. Pulsed welding currents are employed to join thin titanium pipes used in the detector’s evaporative CO2 cooling system. The benefits of the low heat input enabled by the welding process are utilised in the repair and remanufacturing industry of aerospace applications. Wire arc additive manufacturing is applied in the regeneration of aerospace components providing successive material deposition on a layer-upon-layer manner. To this extent investigations and implementations related to Pulsed Gas Tungsten Arc Welding are explored in the presented work aiming to further understand, implement and advance the welding process. Assurance of the weld quality is furthered studied, as the outcome of the process depends on maintaining input parameters and welding conditions at optimum levels for the whole duration of the process. By implementing process monitoring methodologies, invaluable data are recorded whose analysis can be utilised in the detection of process disturbances and weld quality assessment

Seam tracking and gap bridging during robotic laser beam welding via grayscale imaging and wobbling

The use of laser beam welding with robotic manipulators is expanding towards wider industrial applications as the system availability increases with reduced capital costs. Conventionally, laser welding requires high positioning and coupling accuracy. Due to the variability in the part geometry and positioning, as well as the thermal deformation that may occur during the process, joint position and fit-up are not always acceptable nor predictable a-priori if simple fixtures are used. This makes the passage from virtual CAD/CAM environment to real production site not trivial, limiting applications where short part preparations are a need like small-batch productions. Solutions that render the laser welding operations feasible for production series with non-stringent tolerances are required to serve a wider range of industrial applications. Such solutions should be able to track the seam as well as tolerating variable gaps formed between the parts to be joined. In this work, an online correction for robot trajectory based on a greyscale coaxial vision system with external illumination and an adaptive wobbling strategy are proposed as means to increase the overall flexibility of a manufacturing plant. The underlying vision algorithm and control architectures are presented; the robustness of the system to poor illumination conditions and variable reflection conditions is also discussed. The developed solution employed two control loops: the first is able to change the robot pose to follow varying trajectories; the second, able to vary the amplitude of circular wobbling as a function of the gap formed in butt-joint welds. Demonstrator cases on butt-joint welds with AISI 301 stainless steel with increased complexity were used to test the efficacy of the solution. The system was successfully tested on 2 mm thick, planar stainless-steel sheets at a maximum welding speed of 25 mm/s and yielded a maximum positioning and yaw-orientation errors of respectively 0.325 mm and 4.5°. Continuous welds could be achieved with up to 1 mm gaps and variable seam position with the developed control method. The acceptable weld quality could be maintained up to 0.6 mm gap in the employed autogenous welding configuration