2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024): Application: Surface Finish in LPBF
Program Organizers: Joseph Beaman, University of Texas at Austin
Monday 1:30 PM
August 12, 2024
Room: Salon G
Location: Hilton Austin
Session Chair: David Leigh, University of Texas at Austin
1:30 PM
Soldering and Electroplating to AM Surfaces: Benjmain White1; Joseph Erwin1; Tylan Watkins1; 1Sandia National Labs
The advantages of AM are now clearly accessible to designers at the part level, however these compelling advantages are often lost when considering the system design as a whole, as additional post processing, particularly joining of AM parts becomes a new challenge. Heat exchangers and electrical components such as cables require excellent thermal, electrical, and even hermetic connections to the system. We will present data on soldering and electroplating to AM surfaces produced by BPE, powder DED, and LPBF processes. AM copper is presented as the primary material focus because its widespread use in both electrical and thermal applications that require a metallurgical joint. Electroplating parameters for AM 17-4 PH are also identified, and found to produce full coverage, solderable platings. The complex surface topography of AM surfaces produces an inhomogeneous wetting by molten solder, however even minor surface polishing was found to improve joint strength significantly.
1:50 PM
Influence of Scanning Strategy on the Microstructure and the Mechanical Properties of AlSi10Mg Parts Fabricated via LPBF: Stefan Dietrich1; Amelie Hamm1; Lukas Englert1; 1KIT
Laser powder bed fusion (LPBF) of AlSi10Mg is a widely used combination in the area of Additive Manufacturing (AM). Nonetheless, the influence of different scanning strategies on the properties of AlSi10Mg parts has not been considered extensively. In this study a total of 15 different scanning strategies has been investigated, including various non-standard scan patterns, contour sequences, re-melting strategies, and layer rotation angles. The results reveal a significant difference between scan strategies regarding porosity, pore morphology and surface roughness. Tensile tests were used to map the microstructural and surface topography differences of the samples to the mechanical material behaviour. The findings show that the measured density does not correlate with the expected tensile strength, the critical factor rather appears to be the pore morphology. Overall, the findings contribute to understanding the influence and usability of scanning strategies in LPBF manufacturing to reach optimized material properties in AM parts.
2:10 PM
Enhancing Surface Quality in Powder Bed Fusion of 316SS via Shot Peening: Sivasubramanian Chandramouli1; Michael Sealy1; Michael Titus1; 1Purdue University
Critical components in aerospace industries, such as turbine blades and landing gears, are increasingly produced using additive manufacturing (AM), especially laser-powder-bed-fusion (LPBF). Despite LPBF's advantages, the high surface roughness of as-printed parts compromises durability, necessitating post-processing to meet stringent industry standards. Shot peening, a surface work hardening process, improves surface quality, attaining uniform stress distribution and better durability. However, the effectiveness of shot peening on AM components with complex surface orientations is poorly understood. In this work, the effect of shot peening on roughness of LPBF-manufactured 316SS is analyzed, considering surface orientations from 0-90°. Additionally, peening parameters are optimized for achieving uniform roughness across various surface orientations. Optimized peening conditions effectively reduced roughness (≈50%), and induced compressive stresses, thereby increasing surface strength and hardness (≈35%). As the industry embraces AM for parts with complex-oriented designs, these results provide a pathway to achieve optimum surface in AM parts through shot peening.
2:30 PM
Effect of Pre- and Post-Contouring Strategies on the Sloped Downskin Surfaces of Laser Powder-Bed Fusion Parts.: Nismath Vadakkan Habeeb1; Rabiul Islam1; Kevin Chou1; 1University of Louisville
The L-PBF technique is known for fabricating intricate components without using support structures. However, due to the step edge formation and attachment of powder particles, attaining a good surface finish on these parts is challenging. Contouring the scanning region is a possible way to address this issue. This study evaluates the effects of pre- and post-contouring strategies on the downskin surfaces of sloped parts fabricated by L-PBF. The Ti6Al4V parts were printed at inclination angles of 30°, 45° and 60° using both contouring strategies. A double-contouring approach with varying processing conditions was employed and their effects were studied from the surface measurement analysis. The pre-contouring resulted in comparatively smoother downskin surfaces. Also, the parts inclined at 60° have less overhang area and hence resulted in lower surface roughness. In both strategies, low laser power and high scan speed caused less dross formation on the downskin surfaces.
2:50 PM
Extrapolation of Upskin and Downskin Surface Roughness Using 3D Simulated Data for Laser Powder-bed Fabrication of Ti64: Beytullah Aydogan1; Kevin Chou1; 1University Of Louisville
Simulation of additive manufacturing has become a prominent research area in the past decade. Surface roughness significantly influences part quality, yet accurately predicting it using simulation remains a persistent challenge. This study aims to calculate surface roughness by utilizing 3D surface topology extracted from simulated data. The laser powder-bed fusion technique was simulated using process physics simulation. Ten layers were simulated at three different linear energy densities, low, medium, and high, positioned at a 30-degree angle to accommodate upskin and downskin effects. Furthermore, a 3D representation of the melted region for each layer was generated using thermal-gradient output of simulation. Generated 3D layers were stacked on each other and merged to consolidate a 3D representation of the overall sample. Surfaces (upskin, downskin, and side skins) were harvested from this merged sample. Subsequently, surfaces were analyzed, and surface roughness was calculated using Matlab. These values were then compared with experimental results.
3:10 PM Break
3:40 PM
Surface Roughness of the Micro Milled 3D Printed 316L Stainless Steel Parts Fabricated by FDM/ FFF Technology: Suleiman Obeidat1; Eduardo Rodriguez1; Allen Madathil1; Junkun Ma1; Iftekhar Basith1; Ulan Dakeev1; 1Sam Houston State University
This study aims to explore the impact of various 3D printing parameters, notably raster angle, on the surface roughness of micromilled 316L stainless steel components produced through Fused Deposition Modeling (FDM) technology. Utilizing BASF Ultrafuse 316L metal 3D printing filaments, comprising 80% 316L stainless steel powder and 20% resin, parts are printed at varying raster angles (0°, 30°, 45°, and 90°) and layer thicknesses, oriented flat and on the edge. The parts are machined in directions that align with or are perpendicular to the printing direction. The investigation involves measuring surface roughness to discern the relationship between machining direction, raster angle, and building direction. Additionally, correlations between surface roughness, raster angle, and apparent density of sintered parts will be established. This research contributes insights into optimizing 3D printing parameters for achieving desired surface qualities in metal components.
4:00 PM
The Influence of Contour Offset in Laser Powder Bed Fusion: Alexander Kleen1; Edwin Glaubitz1; Joy Gockel1; 1Colorado School of Mines
Surface roughness and porosity have been linked to decreased performance in laser powder bed fusion (PBF-LB) parts. Prior work has shown that contour laser power and power influence surface roughness: however, changing these parameters also changes the contour melt pool size and the placement of the contour needs to be considered to fully understand the behavior. Contour offset defines the placement of the contour pass relative to the bulk scans. Coupons with a range of contour speed, power, and offset values are fabricated in PBF-LB from 316L stainless steel. Sources of variation such as dimensional accuracy, contour stability, surface roughness, contour melt pool size, and sub-surface porosity are characterized. Results suggest that the contour placement is a critical parameter to control variation in material structure using the PBF-LB process. Relationships between contour process parameters and properties will optimize future process development.
4:20 PM
Influence of Powder Particle Size Distributions on Surface Topography of Polymer Laser Powder Bed Fusion Parts: Aakil Raj Lalwani1; Christian Budden1; Venkata Nadimpalli1; Anders Daugaard1; David Pedersen1; 1Technical University of Denmark
The morphology and particle size distribution of commercial polymer powders for Laser Powder Bed Fusion (LPBF) spans a wide range. This is a consequence of the traditional manufacturing methods of milling and grinding. In theory, a combination of large and fine powder particles provides dense powder packing which in turn allow for good processability and parts. This study focuses on correlating powder properties and part quality for parts manufactured with 3 different size distributions, i.e. commercial grade, narrower than commercial, and bimodal. Parts were made with polyamide-11 and on two different machines. The results indicate towards a more suitable particle size distribution for a specific material and a specific machine. Hence spending some additional resources on sieving powder prior to use can be beneficial. However, an optimization should be carried out for each powder and material to find the ideal powder size distribution corresponding to desired part quality.
4:40 PM
Surface Roughness Measurements of Additively Manufactured Components via X-Ray Computed Tomography: Julio Ortega Rojas1; Amir Ziabari1; Obaid Rahman1; Paul Brackman2; Curtis Frederick2; Michael Kirka1; 1Oak Ridge National Laboratory; 2Carl Zeiss
The surface topology and roughness of a material play a crucial role in determining functional properties, impacting aspects such as fluid dynamics, heat transfer, frictional behavior, and mechanical performance. Additive manufacturing (AM) has emerged as a transformative technology, offering unique advantages for fabricating components with complex geometries and novel materials, improving the efficiency of numerous applications. However, a limiting factor of AM is the surface quality of the as-built components, remaining as a critical constraint when good fatigue properties are required for an application. This study focuses on investigating the surface roughness of components fabricated via additive manufacturing. X-Ray computed tomography (CT) data and deep learning algorithms were leveraged to conduct a comprehensive evaluation of surface characteristics and compare our findings with those obtained from confocal microscopy. By exploring the usage of deep learning algorithms, we reveal the potential of advanced CT techniques to evaluate surface roughness of AM components.
5:00 PM
Correlation of Surface Topography with Fatigue Life and Failure Location in Additively Manufactured AlSi10Mg via Computed Tomography: Lukas Englert1; Volker Schulze1; Stefan Dietrich1; 1Institute for Applied Materials, Karlsruhe Institute of Technology (KIT)
The fabrication of AlSi10Mg components via PBF-LB results in the formation of porosity and a rough surface topography. Depending on the relative position to the inert gas flow, the geometry of the component and other factors, these features are also distributed inhomogeneously, which has an adverse effect on fatigue performance. Computed tomography enables the measurement of the entire component surface, making it possible to locate failure critical spots on component surfaces. In this work, surfaces of additively manufactured components are analyzed by a novel method using computed tomography. This allows the visualization of the variation in roughness and near-surface porosity, which in turn facilitates the identification of failure critical spots and their comparison to real failure spots. Furthermore, the location of the failure critical spot can be predicted in 50% of cases, while a correlation with fatigue life is found for low stress amplitudes.