Ingenieurwissenschaften und zugeordnete Tätigkeiten
Filtern
Erscheinungsjahr
- 2023 (4) (entfernen)
Dokumenttyp
- Vortrag (3)
- Forschungsdatensatz (1)
Sprache
- Englisch (4)
Referierte Publikation
- nein (4)
Schlagworte
- DED-Arc (3)
- Additive manufacturing (2)
- Life Cycle Assessment (2)
- Additive Manufacturing (1)
- Arc welding (1)
- Ermüdung (1)
- Fusion welding (1)
- Grain refinement (1)
- High strength AlMgSi aluminium alloys (1)
- Mechanical properties (1)
Organisationseinheit der BAM
Eingeladener Vortrag
- nein (3)
Despite the advances in hardware and software techniques, standard numerical methods fail in providing real-time simulations, especially for complex processes such as additive manufacturing applications. A real-time simulation enables process control through the combination of process monitoring and automated feedback, which increases the flexibil- ity and quality of a process. Typically, before producing a whole additive manufacturing structure, a simplified experiment in form of a bead-on- plate experiment is performed to get a first insight into the process and to set parameters suitably. In this work, a reduced order model for the transient thermal problem of the bead-on-plate weld simulation is devel- oped, allowing an efficient model calibration and control of the process. The proposed approach applies the proper generalized decomposition (PGD) method, a popular model order reduction technique, to decrease the computational effort of each model evaluation required multiple times in parameter estimation, control and optimization. The welding torch is modeled by a moving heat source, which leads to difficulties separating space and time, a key ingredient in PGD simulations. A novel approach for separating space and time is applied and extended to 3D problems allowing the derivation of an efficient separated representation of the tem- perature. The results are verified against a standard finite element model showing excellent agreement. The reduced order model is also leveraged in a Bayesian model parameter estimation setup, speeding up calibrations and ultimately leading to an optimized real-time simulation approach for welding experiment using synthetic as well as real measurement data.
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.