Simulation of Forming Process of Powder Bed for Additive Manufacturing

2016 ◽  
Vol 138 (8) ◽  
Author(s):  
Zhaowei Xiang ◽  
Ming Yin ◽  
Zhenbo Deng ◽  
Xiaoqin Mei ◽  
Guofu Yin
Keyword(s):  
Additive Manufacturing ◽  
Coordination Number ◽  
Layer Thickness ◽  
Packing Density ◽  
Size Distributions ◽  
Forming Process ◽  
Powder Bed ◽  
Soft Sphere ◽  
Number Increase ◽  
Initial Packing

The forming process of powder bed for additive manufacturing (AM) is analyzed and is simplified to three processes, including random packing, layering, and compression. The processes are simulated by using the discrete element method (DEM). First, the particles with monosize, bimodal, and Gaussian size distributions are randomly packed. Then, the packed particles are layered with different thicknesses. Finally, a 20 μm compression is applied on the top surface of the layered powder beds. All the processes are simulated based on the soft sphere model. Packing density and coordination number are calculated to evaluate the packing mesostructure. The results indicate that the packing density and coordination number increase with the layer thickness increasing in the initial packing, and compression can effectively increase the density and coordination number of powder bed and decrease the effect of ranging layer thickness. The results also show that powder bed with monosize distribution initially has the best combination performance. Our research provides a theoretical guide to choosing the layer thickness and size distribution initially of powder bed for AM.

scholarly journals Spreadability Testing of Powder for Additive Manufacturing

2021 ◽  
Vol 166 (1) ◽  
pp. 9-13
Author(s):  
Christopher Neil Hulme-Smith ◽  
Vignesh Hari ◽  
Pelle Mellin
Keyword(s):  
Additive Manufacturing ◽  
Layer Thickness ◽  
Measurement Procedure ◽  
Quantitative Information ◽  
Thin Layers ◽  
Spreading Speed ◽  
Powder Bed ◽  
Critical Step ◽  
Robust Image

AbstractThe spreading of powders into thin layers is a critical step in powder bed additive manufacturing, but there is no accepted technique to test it. There is not even a metric that can be used to describe spreading behaviour. A robust, image-based measurement procedure has been developed and can be implemented at modest cost and with minimal training. The analysis is automated to derive quantitative information about the characteristics of the spread layer. The technique has been demonstrated for three powders to quantify their spreading behaviour as a function of layer thickness and spreading speed.

scholarly journals Analysis of Density, Roughness, and Accuracy of the Atomic Diffusion Additive Manufacturing (ADAM) Process for Metal Parts

Materials ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4122 ◽  
Author(s):  
Manuela Galati ◽  
Paolo Minetola
Keyword(s):  
Additive Manufacturing ◽  
Layer Thickness ◽  
Dimensional Accuracy ◽  
Raw Material ◽  
Atomic Diffusion ◽  
Powder Bed ◽  
Metal Parts ◽  
Unique System ◽  
Am Processes ◽  
Metal Additive

Atomic Diffusion Additive Manufacturing (ADAM) is a recent layer-wise process patented by Markforged for metals based on material extrusion. ADAM can be classified as an indirect additive manufacturing process in which a filament of metal powder encased in a plastic binder is used. After the fabrication of a green part, the plastic binder is removed by the post-treatments of washing and sintering (frittage). The aim of this work is to provide a preliminary characterisation of the ADAM process using Markforged Metal X, the unique system currently available on the market. Particularly, the density of printed 17-4 PH material is investigated, varying the layer thickness and the sample size. The dimensional accuracy of the ADAM process is evaluated using the ISO IT grades of a reference artefact. Due to the deposition strategy, the final density of the material results in being strongly dependent on the layer thickness and the size of the sample. The density of the material is low if compared to the material processed by powder bed AM processes. The superficial roughness is strongly dependent upon the layer thickness, but higher than that of other metal additive manufacturing processes because of the use of raw material in the filament form. The accuracy of the process achieves the IT13 grade that is comparable to that of traditional processes for the production of semi-finished metal parts.

scholarly journals Analysis of Cohesive Microsized Particle Packing Structure Using History-Dependent Contact Models

2015 ◽  
Vol 138 (4) ◽  
Author(s):  
Raihan Tayeb ◽  
Xin Dou ◽  
Yijin Mao ◽  
Yuwen Zhang
Keyword(s):  
Particle Size ◽  
Coordination Number ◽  
Gaussian Distribution ◽  
Packing Density ◽  
Mean Value ◽  
Distribution Functions ◽  
Particle Packing ◽  
Size Distributions ◽  
Packing Structure ◽  
Contact Models

Granular packing structures of cohesive microsized particles with different sizes and size distributions, including monosized, uniform, and Gaussian distribution, are investigated by using two different history dependent contact models with discrete element method (DEM). The simulation is carried out in the framework of liggghts, which is a DEM simulation package extended based on branch of granular package of widely used open-source code LAMMPS. Contact force caused by translation and rotation, frictional and damping forces due to collision with other particles or container boundaries, cohesive force, van der Waals force, and gravity is considered. The radial distribution functions (RDFs), force distributions, porosities, and coordination numbers under cohesive and noncohesive conditions are reported. The results indicate that particle size and size distributions have great influences on the packing density for particle packing under cohesive effect: particles with Gaussian distribution have the lowest packing density, followed by the particles with uniform distribution; the particles with monosized distribution have the highest packing density. It is also found that cohesive effect to the system does not significantly affect the coordination number that mainly depends on the particle size and size distribution. Although the magnitude of net force distribution is different, the results for porosity, coordination number, and mean value of magnitude of net force do not vary significantly between the two contact models.

On the measurement of effective powder layer thickness in laser powder-bed fusion additive manufacturing of metals

2018 ◽  
Vol 4 (2) ◽  
pp. 109-116 ◽  
Author(s):  
Yahya Mahmoodkhani ◽  
Usman Ali ◽  
Shahriar Imani Shahabad ◽  
Adhitan Rani Kasinathan ◽  
Reza Esmaeilizadeh ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Layer Thickness ◽  
Powder Layer ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed

Fundamental Study of Fused-Coating Based Metal Additive Manufacturing

2017 ◽  
Author(s):  
Xuewei Fang ◽  
Jun Du ◽  
Zhengying Wei ◽  
Xin Wang ◽  
Pengfei He ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Layer Thickness ◽  
Molten Metal ◽  
Optimal Parameter ◽  
Measurement Unit ◽  
Transfer Model ◽  
Forming Process ◽  
Metal Additive Manufacturing ◽  
Metal Parts ◽  
Metal Additive

Fused-coating based metal additive manufacturing (FCAM) is a newly established direct metal forming process. This method is characterized by deposition metal materials in a crucible and under the driving pressure the molten metal is extruded out from a special designed nozzle. Hence, dense metal parts with different kind of materials can be built on the moving substrate layer by layer. It provides a method to fabricate metal components with lower costs, clean and cheap materials compared with other AM processes. To study the feasibility of this new AM methodology, an experimental system with a molten metal stream generator, a fused-coating nozzle, a process monitor unit, an inert atmosphere protection unit and a temperature measurement unit has been established. In order to determine the proper parameters in the building process, a metal fused-coating heat transfer model analysis and experimental study is performed by using Sn63-37Pb alloy in building three-dimensional components. The process parameters that may affect fabrication are molten and substrate temperature, layer thickness, the substrate-speed, the temperature of substrate, the distance between the nozzle and substrate and the pressure. Microscopy images were used to investigate the metallurgical bonding between layers. The influence of different parameters on the layer thickness and width was studied quantitatively. At last, the optimal parameter was used to fabricate complex metal parts to demonstrate the feasibility of this new technology compared with other AM methods.

scholarly journals Discrete Element Simulation of the Effect of Roller-Spreading Parameters on Powder-Bed Density in Additive Manufacturing

Materials ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2285
Author(s):  
Jiangtao Zhang ◽  
Yuanqiang Tan ◽  
Tao Bao ◽  
Yangli Xu ◽  
Xiangwu Xiao ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Layer Thickness ◽  
Rotational Speed ◽  
High Performance ◽  
Ceramic Powder ◽  
Discrete Element ◽  
Parameters Optimization ◽  
Powder Layer ◽  
Translational Velocity ◽  
Powder Bed

The powder-bed with uniform and high density that determined by the spreading process parameters is the key factor for fabricating high performance parts in Additive Manufacturing (AM) process. In this work, Discrete Element Method (DEM) was deployed in order to simulate Al2O3 ceramic powder roller-spreading. The effects of roller-spreading parameters include translational velocity Vs, roller’s rotational speed ω, roller’s diameter D, and powder layer thickness H on powder-bed density were analyzed. The results show that the increased translational velocity of roller leads to poor powder-bed density. However, the larger roller’s diameter will improve powder-bed density. Moreover, the roller’s rotational speed has little effect on powder-bed density. Layer thickness is the most significant influencing factor on powder-bed density. When layer thickness is 50 μm, most of particles are pushed out of the build platform forming a lot of voids. However, when the layer thickness is greater than 150 μm, the powder-bed becomes more uniform and denser. This work can provide a reliable basis for roller-spreading parameters optimization.

scholarly journals Slicing Algorithm and Partition Scanning Strategy for 3D Printing Based on GPU Parallel Computing

Materials ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4297
Author(s):  
Xuhui Lai ◽  
Zhengying Wei
Keyword(s):  
Additive Manufacturing ◽  
3D Printing ◽  
Layer Thickness ◽  
Numerical Control ◽  
Electron Gun ◽  
Normal Vector ◽  
Processing Unit ◽  
Scanning Strategy ◽  
Forming Process ◽  
Deformation Control

Aiming at the problems of over stacking, warping deformation and rapid adjustment of layer thickness in electron beam additive manufacturing, the 3D printing slicing algorithm and partition scanning strategy for numerical control systems are studied. The GPU (graphics processing unit) is used to slice the 3D model, and the STL (stereolithography) file is calculated in parallel according to the normal vector and the vertex coordinates. The voxel information of the specified layer is dynamically obtained by adjusting the projection matrix to the slice height. The MS (marching squares) algorithm is used to extract the coordinate sequence of the binary image, and the ordered contour coordinates are output. In order to avoid shaking of the electron gun when the numerical control system is forming the microsegment straight line, and reduce metal overcrowding in the continuous curve C0, the NURBS (non-uniform rational b-splines) basis function is used to perform curve interpolation on the contour data. Aiming at the deformation problem of large block components in the forming process, a hexagonal partition and parallel line variable angle scanning technology is adopted, and an effective temperature and deformation control strategy is formed according to the European-distance planning scan order of each partition. The results show that the NURBS segmentation fits closer to the original polysurface cut line, and the error is reduced by 34.2% compared with the STL file slice data. As the number of triangular patches increases, the algorithm exhibits higher efficiency, STL files with 1,483,132 facets can be cut into 4488 layers in 89 s. The slicing algorithm involved in this research can be used as a general data processing algorithm for additive manufacturing technology to reduce the waiting time of the contour extraction process. Combined with the partition strategy, it can provide new ideas for the dynamic adjustment of layer thickness and deformation control in the forming process of large parts.

scholarly journals Influence of Stress States on Forming Hybrid Parts with Sheet Metal and Additively Manufactured Element

2021 ◽  
Author(s):  
Jan Hafenecker ◽  
Thomas Papke ◽  
Marion Merklein
Keyword(s):  
Mechanical Properties ◽  
Additive Manufacturing ◽  
Sheet Metal ◽  
Metal Forming ◽  
Forming Process ◽  
Powder Bed ◽  
Geometrical Properties ◽  
Hybrid Parts ◽  
Metal Materials ◽  
Stress States

AbstractHybrid parts with additively manufactured elements (AME) combine the advantages of two or more manufacturing processes, e.g., forming and additive manufacturing (AM), and thus offer a solution to the increasing demands of industrial trends such as personalized mass production. Despite their advantageous properties, research in this field still lacks in clear classification and process interactions. Due to the strong influence of the AME on the formability of hybrid parts, the combination of laser-based powder bed fusion (PBF-LB) with subsequent sheet metal forming is examined in this paper. Therefore, cylindrical functional elements are built up on sheet metal and the resulting hybrid components are subsequently formed. Common forming processes such as bending, stretch forming and deep drawing are compared in regard to the different stress states. The results show a reduction in formability for hybrid components compared to conventional sheet metal materials. Reasons found are geometrical properties, gradients of mechanical properties and induced stresses. Consequently, requirements for the additive manufacturing process regarding a subsequent forming process are outlined. Namely, the gradient of mechanical properties should be smoothened, residual stresses kept low and the design of AMEs should avoid stress concentration.

Effect of Laser Energy Density on Bulk Properties of SS 316L Structures Built by Laser Additive Manufacturing Using Powder Bed Fusion

2019 ◽  
Author(s):  
Saurav K. Nayak ◽  
Sanjay K. Mishra ◽  
Christ P. Paul ◽  
Arackal N. Jinoop ◽  
Sunil Yadav ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Energy Density ◽  
Layer Thickness ◽  
Laser Energy ◽  
Advanced Technology ◽  
Incomplete Fusion ◽  
Laser Energy Density ◽  
Powder Bed Fusion ◽  
Laser Additive Manufacturing ◽  
Powder Bed

Abstract Laser Additive Manufacturing using Powder Bed Fusion (LAM-PBF) is one of the revolutionary technologies playing a key role in fourth industrial revolution for redefining manufacturing from mass production to mass customization. To upkeep the pace, Raja Ramanna Centre for Advanced Technology (RRCAT) has indigenously developed an LAM-PBF system and it is being used for process and component development for various engineering applications. This paper reports a parametric investigation to evaluate the influence of process parameters on the sample properties and to develop the process window for fabricating complex shaped engineering components. In the present work, an experimental investigation is carried out to investigate the effect of Laser Energy density (LED) on the porosity, microstructure and mechanical properties of SS 316L bulk structures fabricated by LAM-PBF system. LED is a combined parameter simultaneously considering the effect of Laser Power (P), Scan Speed (v), hatch spacing (h) and layer thickness (t). The effect of three LED values such as 83.33 J/mm3, 253.97 J/mm3 and 476.19 J/mm3 is investigated in the present work by building cuboidal samples at a layer thickness of 75 microns. Porosity is estimated using area fraction method in optical microscopy and it is found that the minimum porosity of 0.14 % and pore area of 1.28 mm2 are observed at 253.97 J/mm3. Maximum porosity of 18.85 % is observed at 83 J/mm3 due to incomplete fusion defects. However, porosity observed at 475 J/mm3 is 6.56 % with average pore size of 17.8 mm2. Microstructural studies show primarily columnar growth in all the samples with fine dendrites. The dendrite size is observed to be 3.2 μm, 2.4 μm and 1.46 μm at 83.33 J/mm3, 253.97 J/mm3 and 476.19 J/mm3 respectively. Micro-hardness and single cycle automatic ball indentation studies are found to be in agreement with dendritic size, with lower hardness at larger dendrite size. X-Ray Diffraction (XRD) studies indicate similar peaks at all the conditions, with slight peak shift observed with increase in LED primarily due to higher amount of residual stress. Thus, it can be inferred that LED of 253.97 J/mm3 is suitable for fabricating engineering components due to combination of lower porosity and fine dendritic structure.

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