Additive Fertigung
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By allowing economic on demand manufacturing of highly customized and complex workpieces, metal based additive manufacturing (AM) has the prospect to revolutionize many industrial areas. Since AM is prone to the formation of defects during the building process, a fundamental requirement for AM to become applicable in most fields is the ability to guarantee the adherence to strict quality and safety standards. A possible solution for this problem lies in the deployment of various in-situ monitoring techniques. For most of these techniques, the application to AM is still very poorly understood. Therefore, the BAM in its mission to provide safety in technology has initiated the project “Process Monitoring of AM” (ProMoAM). In this project, a wide range of in-situ process monitoring techniques, including active and passive thermography, optical tomography, optical emission and absorption spectroscopy, eddy current testing, laminography, X-ray backscattering and photoacoustic methods, are applied to laser metal deposition (LMD), laser powder bed fusion and wire arc AM. Since it is still unclear which measured quantities are relevant for the detection of defects, these measurements are performed very thoroughly. In successive steps, the data acquired by all these methods is fused and compared to the results of reference methods such as computer tomography and ultrasonic immersion testing. The goal is to find reliable methods to detect the formation of defects during the building process. The detailed acquired data sets may also be used for comparison with simulations.
Here, we show first results of high speed (> 300 Hz) thermographic measurements of the LMD process in the SWIR range using 316L as building material. For these experiments, the camera was mounted fixed to the welding arm of the LMD machine to keep the molten pool in focus, regardless of the shape of the specimen. As the thermograms do not contain any information about the current spatial position during the building process, we use an acceleration sensor to track the movement and synchronize the measured data with the predefined welding path. This allows us to reconstruct the geometry of the workpieces and assign the thermographic data to spatial positions. Furthermore, we investigate the influence of the acquisition wavelength on the thermographic data by comparing measurements acquired with different narrow bandpass filters (50 nm FWHM) in a spectral range from 1150 nm to 1550 nm.
This research was funded by BAM within the Focus Area Materials.
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.
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.
The paper deals with the integration of a light emitting diode (LED) into an additive manufactured metal component. Selective laser melting (SLM) and laser metal deposition (LMD) are used. The material used is the chrome-nickel steel 316L. The basic component is manufactured by means of SLM and consists of a solid body and an area with grid structure. The solid body includes a duct in the shape of a groove with a recess for the positioning of the power cable. The LED is embedded in the grid structure via an inlet from the solid body. In further processing, the groove is filled with LMD. Two strategies with different parameter combinations were investigated. It shows that a high energy input near the power cable leads to its destruction. By using multiple parameter combinations during the manufacturing process, this destruction can be prevented. There was a comparison of both strategies with regard to the necessary number of tracks and duration of welding time.
The laser-based direct energy deposition (DED) as a technology for additive manufacturing allows the production of near net shape components. Industrial applications require a stable process to ensure reproducible quality. Instabilities in the manufacturing process can lead to faulty components which do not meet the required properties.
The DED process is adjusted by various parameters such as laser power, velocity, powder mass flow and spot diameter, which interact with each other. A frequently used comparative parameter in welding is the energy per unit length and is calculated from the laser power and the velocity in laser welding. The powder per unit length comparative parameter in the DED process has also be taken into account, because this filler material absorbs energy in addition to the base material.
This paper deals with the influence of mass energy as a comparative parameter for determining the properties of additively manufactured parts. The same energy per unit length of 60 J/mm as well as the same powder per unit length of 7.2 mg/mm can be adjusted with different parameter sets. The energy per unit length and the powder per unit length determine the mass energy. The laser power is varied within the experiments between 400 W and 900 W. Energy per unit length and powder per unit length are kept constant by adjusting velocity and powder mass flow. Using the example of Inconel 718, experiments are carried out with the determined parameter sets. In a first step, individual tracks are produced and analyzed by means of micro section. The geometry of the tracks shows differences in height and width. In addition, the increasing laser power leads to a higher dilution of the base material. To determine the suitability of the parameters for additive manufacturing use, the individual tracks are used to build up parts with a square base area of 20x20 mm². An investigation by Archimedean principle shows a higher porosity with lower laser power. By further analysis of the micro sections, it can be seen that at low laser power, connection errors occur between the tracks.
The results show that laser power, velocity and powder mass flow have to be considered in particular, because a constant mass energy can lead to different geometric as well as microscopic properties.
The paper deals with the integration of a light emitting diode (LED) into an additive manufactured metal component. Selective laser melting (SLM) and laser metal deposition (LMD) are used. The material used is the chrome-nickel steel 316L. The basic component is manufactured by means of SLM and consists of a solid body and an area with grid structure. The solid body includes a duct in the shape of a groove with a recess for the positioning of the power cable. The LED is embedded in the grid structure via an inlet from the solid body. In further processing, the groove is filled with LMD. Two strategies with different parameter combinations were investigated. It shows that a high energy input near the power cable leads to its destruction. By using multiple parameter combinations during the manufacturing process, this destruction can be prevented. There was a comparison of both strategies with regard to the necessary number of tracks and duration of welding time.
As a part of ProMoAM project, we are optimizing a prototype X-ray backscatter to reach NDT requirements, and thereafter to apply it for process monitoring. Moreover, we studied the capability of a radiography approach to detect artificial defects in AM components made by laser powder bed fusion (L-PBF).
Pores in additive manufactured metal parts occur due to different reasons and affect the part Quality negatively. Few investigations on the origins of porosity are available, especially for Ni-based super alloys. This paper presents a new study to examine the influence of common processing Parameters on the Formation of pores in parts built by laser metal Deposition using Inconel 718 powder. Further, a comparison between the computed tomography (CT) and the Archimedes method was made. The Investigation Shows that CT is able to identify different kinds of pores and to give further Information about their distribution. The identification of some pores as well as their shape can be dependent on the Parameter Setting of the Analysis tool. Due to limited measurement Resolution, CT is not able to identify correctly pores with Diameters smaller than 0.1 mm, which leads to a false decrease on Overall porosity. The applied Archimedes method is unable to differentiate between gas porosity and other Kinds of holes like internal cracks or lack of Fusion, but it delivered a proper value for Overall porosity. The method was able to provide suitable data for the statistical Evaluation with design of Experiments, which revealed significant Parameters ont he Formation of pores in LMD.
Directed energy deposition (DED) has been in industrial use as a coating process for many years. Modern applications include the repair of existing components and additive manufacturing. The main advantages of DED are high deposition rates and low energy input. However, the process is influenced by a variety of parameters affecting the component quality. Artificial neural networks (ANNs) offer the possibility of mapping complex processes such as DED. They can serve as a tool for predicting optimal process parameters and quality characteristics. Previous research only refers to weld beads: a transferability to additively manufactured three-dimensional components has not been investigated. In the context of this work, an ANN is generated based on 86 weld beads. Quality categories (poor, medium, and good) are chosen as target variables to combine several quality features. The applicability of this categorization compared to conventional characteristics is discussed in detail. The ANN predicts the quality category of weld beads with an average accuracy of 81.5%. Two randomly generated parameter sets predicted as “good” by the network are then used to build tracks, coatings,walls, and cubes. It is shown that ANN trained with weld beads are suitable for complex parameter predictions in a limited way.