Ingenieurwissenschaften und zugeordnete Tätigkeiten
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- 9.3 Schweißtechnische Fertigungsverfahren (328) (entfernen)
Eingeladener Vortrag
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Additive manufacturing is one of the most promising techniques for industrial production and maintenance, but the specifics of the layered structure must be considered. The Direct Energy Deposition-Arc process enables relatively high deposition rates, which is favourable for larger components. For this study, specimens with different orientations were prepared from one AISI316 steel block – parallel and orthogonal to the deposition plane. Quasistatic tensile loading tests were carried out, monitored by an infrared camera. The obtained surface temperature maps revealed structural differences between both orientations. The consideration of surface temperature transients yields more details about the behaviour of the material under tensile loading than the conventional stress-strain-curve. These preliminary investigations were supplemented by thermographic fatigue trials. Although the anisotropy was also observed during fatigue loading the fatigue behaviour in general was the same, at least for both inspected specimens. The presented results demonstrate the abilities and the potential of thermographic techniques for tensile tests.
As industries move for ever faster development and adoption cycles of emerging new technologies in the field of welding, the meticulous and longer-winded approach of the scientific research process can feel harder to integrate. To help bridge this gap and increase the speed, quality, and adoption rate of publicly funded research, the Bundesanstalt für Materialforschung und -prüfung (BAM) continues to work towards enabling scientists with direct access to necessary software tools and - in the future – highest quality welding research reference data to further foster collaborations.
On the experimental side, the arc welding group at BAM division 9.3 “welding technologies” is continuing to expand and upgrade its capacities of robotic welding systems with integrated state of the art sensor technologies and software solutions. This allows all experiments to be recorded and measured in micro-millimeter accuracy and at sub-millisecond precision, including welding process data, complete spatial geometry and temperature measurements, process video recordings and more. The custom software-based solutions and interfaces allow scaling of the welding systems from large thick plate offshore applications to small additive repair weldments in wind turbine blades to multi-hour continuous weldments in additive manufacturing applications. In addition to the data gathered during the welding process itself, the relevant testing results and materials properties produced at BAM or externally can be integrated seamlessly. This allows detailed traceability of all results back to the actual welding process.
Regardless of the scope and application, complete datasets can be made accessible for research or industry partners in the highest resolution based on the open source WelDX (welding data exchange) file format.
Figure 1. Welding experiment representation including dynamic process data, cross-section imaging and hardness measurements from a single weldx file.
The talk will give an overview of the experimental facilities and workflows as well as current software developments with a focus on research data quality assurance, traceability, and accessibility.
Based on the integration into latest research trends and activities of the “welding technologies” division, the path to publishing reference datasets for arc welding process for various applications and materials is outlined and discussed.
Direct energy deposition additive manufacturing technologies that utilize an electric arc have great potential for generating large volume metal components. However, selecting process parameters that yield the desired near net shape design and requested mechanical component behavior is not a trivial task due to the complex relationship between all process parameters and material characteristics. This presentation exemplifies the application of a newly developed solid welding wire doped with TiB to enhance grain refinement in the deposited metal for additive manufacturing based on DED-Arc of high-strength precipitation hardening AlMgSi-aluminum alloys. It is worth noting that the solid wire is the result of our preliminary metallurgical studies on grain refinement in aluminum weld metal.
Consequently, research focuses on the correlation between process parameters and component quality to understand the underlying mechanisms. This is crucial for evaluating a robust process parameter space that yields component quality in line with corresponding standards which are mainly taken from welding technology.
Specifically, we examine component quality by analyzing pore size and distribution, as well as grain morphology. To enhance the mechanical properties of the deposited metal, a post-weld heat treatment was conducted, comprising of solution treatment, quenching, and artificial aging. The study also evaluates the effects of various heat treatment strategies on the final mechanical properties of the material.
To demonstrate the applicability of 3D metal printing of high-strength aluminium alloys, a more complex demonstrator was created. It has been shown that DED-Arc can produce high-volume aluminium parts with the same quality as the corresponding subtractive processing strategy.
Additionally, the entire additive manufacturing chain has been digitally integrated, enabling traceability of all relevant process steps, which is essential for reliable subsequent quality assessment.
The present Ph.D. thesis provides a comprehensive experimental and theoretical study of the bulging-cracking relationship in laser beam welding of thick unalloyed steel sheets. It focuses on experimentally proving the existence of the bulging region and on developing a coupled multiphysics mathematical framework to analyze its influence on the three critical factors controlling the susceptibility to solidification cracking, namely the thermal, metallurgical, and mechanical factors.
The research employs a novel experimental setup, utilizing a combination of transparent quartz glass and thick unalloyed steel sheet, enabling real-time visualization of the weld pool geometry and confirming the existence of a distinctive bulging region. To deepen the understanding of these experimental insights, an extensive multiphysics mathematical framework was developed and rigorously verified and validated. This framework introduces an innovative approach using Lamé curves for accurately describing complex three-dimensional weld pool geometries, including the bulging region's characteristics. Through analytical solutions and numerical procedures, it facilitates the computation of solidification parameters, which are crucial for understanding the metallurgical aspects of crack formation. The framework also incorporates a mechanical model to assess and evaluate the local stress distribution within the bulging region.
The findings indicate that an elongated, sharply shaped bulging region significantly increases the susceptibility to solidification cracking. This is attributed to its adverse impact on the distribution and local dwell time of liquid metal residing at grain boundaries during solidification, combined with the localized tensile stresses identified in the bulging region.
In essence, this research contributes to the broader understanding of solidification cracking in laser beam welding of thick unalloyed steel sheets, with a particular focus on the bulging region. The insights and methodologies developed in this thesis are valuable for future research and advancements in the application of the laser beam welding technology for joining high-thickness unalloyed steel components.
It is proposed to model the experimentally observed weld pool boundary with superellipses (Lamé curves) and to find the unknown parameters of the curves using optimization methods. It has been shown experimentally that during laser welding of austenitic stainless steel with a thickness of 2 mm at a speed of 20 mm/s, the rear weld pool part has a shape close to triangular which can be accurately approximated by a superellipse. Analytical dependences of the trajectory and growth rate of the crystal and its cross-sectional area on the geometry of the rear weld pool part are obtained.
A method of solving the thermo-fluid dynamics problem is presented, enabling the prediction of the shape and dimensions of the weld pool during keyhole laser welding of thick plates. It is shown that the rear weld pool boundary can be satisfactorily approximated by a set of superellipses (Lamé curves). The presence of a convex rear weld pool boundary in the mid-plane has been observed experimentally and reproduced numerically. It was shown that in this zone the concentration of liquating impurities increases and the local solidification temperature decreases, contributing to the susceptibility to hot cracking.
Direct energy deposition additive manufacturing technologies utilizing an electric arc offer a great potential in generating large volume metal components. However, the selection of process parameters that yield the desired near net shape design as well as the requested mechanical component behavior is not a trivial task due to the complex relationship. Exemplarily for additive manufacturing of high-strength precipitation hardening AlMgSi-aluminum alloy this paper shows the application of a newly developed matching solid welding wire doped with TiB as grain refiner. The correlation between process parameters and component quality is examined analyzing the size and distribution of pores as well as the grain morphology. Furthermore, the influences of different post-weld heat treatments are evaluated to meet the reference mechanical properties of the corresponding wrought material. Finally, the digital integration of the entire additive manufacturing chain enables an overall traceability of the relevant process steps which is the basis for a reliable subsequent quality assessment.
In manufacturing, fusion welding processes use a lot of resources, which presents an opportunity to reduce environmental impact. While there is a general understanding of the environmental impact of these processes, it is difficult to quantitatively assess key parameters. This study introduces a welding-specific methodology that uses life cycle assessment (LCA) to evaluate the environmental impact of fusion welding technologies. Our approach analyses the main parameters that affect the environmental performance of different welding techniques, including traditional methods and additive manufacturing through the Direct Energy Deposition-Arc (DED-Arc) process. We integrate real-time resource usage data to offer an innovative framework for directly deriving environmental impacts. This research contributes to optimising welding processes by providing a precise and quantifiable measure of their ecological impact, facilitating the advancement of sustainable manufacturing practices.
Life cycle assessment of fusion welding processes considering upstream and downstream process steps
(2023)
In manufacturing, fusion welding processes consume significant resources, presenting a significant opportunity for reducing environmental impact. Although there is a qualitative understanding of the environmental implications of these processes, a quantitative assessment of key parameters remains complex. This study introduces a welding-specific methodology that employs life cycle assessment (LCA) to quantitatively evaluate the environmental footprint of fusion welding technologies. Our approach identifies and analyses the principal parameters affecting the environmental performance of various welding techniques, including traditional joint welding and additive manufacturing via the Direct Energy Deposition-Arc (DED-Arc) process. Real-time resource usage data is integrated to offer an innovative framework for directly deriving environmental impacts. This research contributes to optimising welding processes by providing a precise and quantifiable measure of their ecological impact. This facilitates the advancement of sustainable manufacturing practices.
Beim Unterpulverschweißen sind die Prozessgeräusche ein Indikator für eine gute Fügequalität. Diese Beurteilung kann i.d.R. nur von einer erfahrenen Fachkraft durchgeführt werden. Eine kürzlich entwickelte künstliche Intelligenz kann automatisch das akustische Prozesssignal anhand vortrainierter Merkmale klassifizieren und die Fügequalität anhand des Geräuschs beurteilen. Der Algorithmus, einmal richtig trainiert, kann den Prüfaufwand beim Unterpulverschweißen deutlich reduzieren.