Modeling of Powder Bed Manufacturing Defects

Mindt, H.‐W.; Desmaison, Olivier; Megahed, Mustafa; Peralta, Alonso; Neumann, J.

doi:10.1007/s11665-017-2874-5

Cited by 61 publications

(26 citation statements)

References 27 publications

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“…Lack of sufficient understanding of the multi-physics process, such as cohesive and frictional powder flow in the spreading process [5,15] and heat transfer [16,17] in the sintering process, hinder further development of this technology and introduction of new materials [18,19]. The powder spreading process has an important effect on the characteristics and quality of the final product.…”

Section: Introductionmentioning

confidence: 99%

Jamming during particle spreading in additive manufacturing

et al. 2018

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Additive manufacturing (AM) is going through an exponential growth, due to its enormous potential for rapid manufacturing of complex shapes. One of the manufacturing methods is based on powder processing, but its major bottleneck is associated with powder spreading, as mechanical arching adversely affects both product quality and speed of production. Here we analyse transient jamming of gas-atomised metal powders during spreading. These particles are highly frictional, as they have asperities and multiple spheres and are prone to jamming in narrow gaps. Therefore their detailed characterisations of mechanical properties are critical to be able to reliably predict the jamming frequency as influenced by powder properties and process conditions. Special methods have been used to determine the physical and mechanical properties of gas-atomised stainless steel powders. These properties are then used in numerical simulations of powder spreading by the Discrete Element Method. Particle shape is reconstructed for the simulations as a function of particle size. The characteristic size D 90 by number (i.e. the particle size, based on the projected-area diameter, for which 90% of particles by number are smaller than this value) is used as the particle dimension accountable for jamming. Jamming is manifested by empty patches over the work surface. Its frequency and period have been characterised as a function of the spreader gap height, expressed as multiple of D 90 . The probability of formation of empty patches and their mean length, the latter indicating jamming duration, increase sharply with the decrease of the gap height. The collapse of the mechanical arches leads to particle bursts after the blade. The frequency of jamming for a given survival time decreases exponentially as the survival time increases.

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Section: Introductionmentioning

confidence: 99%

Jamming during particle spreading in additive manufacturing

et al. 2018

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“…Once the powder bed geometry is obtained, either via script or via modelling of the racking process, the particle distribution on the powder bed is provided to a computational fluid dynamics model that accounts for laser interaction with the feed stock providing more insight about the phase changes and solidification behaviour of the material [2,8]. The momentum equations are extended using source terms to account for gravitational body forces, recoil pressure, and surface tension.…”

Section: Computational Modelsmentioning

confidence: 99%

Influence of Powder Bed Characteristics on Material Quality in Additive Manufacturing

Zielinski

Vervoort

Mindt

et al. 2017

Berg Huettenmaenn Monatsh

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Abstract:In powder bed based Additive Manufacturing (AM) processes like Selective Laser Melting (SLM) or Electron Beam Melting (EBM), the spatial distribution of the individual powder particles is typically unknown. Nevertheless, the distribution of particles in the heat affected zone defines the thermophysical properties of the region being processed by the heat source and therefore plays a crucial role in heat transfer processes. In this work, the spatial distribution of individual particles and their influence on the AM process is numerically investigated. Two powder bed configurations are compared: One powder bed is generated using the discrete element method (DEM) to model the coating process; the second powder bed is arranged in the BCC structure. The melting and solidification of both configurations are modelled. The predicted melt pool dimensions are compared with experimentally determined values. The results indicate that modelling the coating process is necessary to ensure accurate modelling of the heat source powder bed interaction as well as an accurate prediction of the melt pool characteristics. Keywords

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“…2 This paper focuses on the application of a modeling platform encompassing powder-scale models as well as component-scale models towards assessing the final quality of a demonstrator component. [3][4][5][6][7] Ti6Al4V is chosen to demonstrate the modeling work flow. The numerical results of each step are compared to experimental measurements confirming the applicability of numerical methods towards quick economic qualification of additive manufactured parts.…”

Section: Introductionmentioning

confidence: 99%