Optimisation of blade type spreaders for powder bed preparation in Additive Manufacturing using DEM simulations

Powder Spreading Mechanism in Laser Powder Bed Fusion Additive Manufacturing: Experiments and Computational Approach Using Discrete Element Method

Laser powder bed fusion (LPBF) additive manufacturing (AM) has been adopted by various industries as a novel manufacturing technology. Powder spreading is a crucial part of the LPBF AM process that defines the quality of the fabricated objects. In this study, the impacts of various input parameters on the spread of powder density and particle distribution during the powder spreading process are investigated using the DEM (discrete element method) simulation tool. The DEM simulations extend over several powder layers and are used to analyze the powder particle packing density variation in different layers and at different points along the longitudinal spreading direction. Additionally, this research covers experimental measurements of the density of the powder packing and the powder particle size distribution on the construction plate.

Thermal Modeling of Polyamide 12 Powder in the Selective Laser Sintering Process Using the Discrete Element Method

Selective laser sintering (SLS) is one of the key additive manufacturing technologies that can build any complex three-dimensional structure without the use of any special tools. Thermal modeling of this process is required to anticipate the quality of the manufactured parts by assessing the microstructure, residual stresses, and structural deformations of the finished product. This paper proposes a framework for the thermal simulation of the SLS process based on the discrete element method (DEM) and numerically generated in Python. This framework simulates a polyamide 12 (PA12) particle domain to describe the temperature evolution in this domain using simple interaction laws between the DEM particles and considering the exchange of these particles with the boundary planes. The results obtained and the comparison with the literature show that the DEM frame accurately captures the temperature distribution in the domain scanned by the laser. The effect of laser power and projection time on the temperature of PA12 particles is investigated and validated with experimental settings to show the reliability of DEM in simulating powder-based additive manufacturing processes.

The Role of Roller Rotation Pattern in the Spreading Process of Polymer/Short-Fiber Composite Powder in Selective Laser Sintering

In this study, for the first time, a forward-rotating roller is proposed for the spreading of CF/PA12 composite powder in the selective laser sintering (SLS) process. The mesoscopic kinetic mechanism of composite particle spreading is investigated by utilizing the “multi-spherical” element within the discrete element method (DEM). The commercial software EDEM and the open-source DEM particle simulation code LIGGGHTS-PUBLIC are used for the simulations in this work. It is found that the forward-rotating roller produces a strong compaction on the powder pile than does the conventional counter-rotating roller, thus increasing the coordination number and mass flow rate of the particle flow, which significantly improves the powder bed quality. In addition, the forward-rotating pattern generates a braking friction force on the particles in the opposite direction to their spread, which affects the particle dynamics and deposition process. Therefore, appropriately increasing the roller rotation speed to make this force comparable to the roller dragging force could result in faster deposition of the composite particles to form a stable powder bed. This mechanism allows the forward-rotating roller to maintain a good powder bed quality, even at a high spreading speed, thus providing greater potential for the industry to improve the spreading efficiency of the SLS process.

Process Phenomena and Material Properties in Selective Laser Sintering of Polymers: A Review

Selective laser sintering (SLS) is a powder bed fusion technology that uses a laser source to melt selected regions of a polymer powder bed based on 3D model data. Components with complex geometry are then obtained using a layer-by-layer strategy. This additive manufacturing technology is a very complex process in which various multiphysical phenomena and different mechanisms occur and greatly influence both the quality and performance of printed parts. This review describes the physical phenomena involved in the SLS process such as powder spreading, the interaction between laser beam and powder bed, polymer melting, coalescence of fused powder and its densification, and polymer crystallization. Moreover, the main characterization approaches that can be useful to investigate the starting material properties are reported and discussed.

Calibration of DEM for Cohesive Particles in the SLS Powder Spreading Process

In this paper, a new DEM calibration procedure based on two different types of procedures to compare simulation with experiments is proposed. The aim is to find the values of the interfacial adhesive surface energy and the coefficient of rolling friction between the particles to be used in the simulation. The approach adopted is the so-called Bulk Calibration method. The experimental values of the angle of repose and unconfined yield strength, found with a static testing method and by shear testing, respectively, are compared, respectively, with the angle of repose, found in a simulation reproducing the experimental procedure, and the unconfined yield strength, obtained from an idealized uniaxial testing procedure. The simulated DEM particles are spheres equipped with the Hertz Mindlin with JKR contact model. The results suggest that a bulk calibration approach is not able to provide results that are consistent with two simple bulk property evaluations and, therefore, direct ways to estimate the surface energy based on the evaluation of interparticle forces, for example, should preferably be adopted.

Vibratory Powder Feeding for Powder Bed Additive Manufacturing Using Water and Gas Atomized Metal Powders

Commercial powder bed fusion additive manufacturing systems use re-coaters for the layer-by-layer distribution of powder. Despite the known limitations of re-coaters, there has been relatively little work presented on the possible benefits of alternative powder delivery systems. Here, we reveal a feeding technology that uses vibration to control flow for powder bed additive manufacturing. The capabilities of this approach are illustrated experimentally using two very different powders; a ‘conventional’ gas atomized Ti-6Al-4V powder designed for electron beam additive manufacturing and a water atomized Fe-4 wt.% Ni alloy used in powder metallurgy. Single layer melt trials are shown for the water atomized powder to illustrate the fidelity of the melt tracks in this material. Discrete element modelling is next used to reveal the mechanisms that underpin the observed dependence of feed rate on feeder process parameters and to investigate the potential strengths and limitations of this feeding methodology.

Discrete Element Method Analysis of the Spreading Mechanism and Its Influence on Powder Bed Characteristics in Additive Manufacturing

Laser powder bed fusion additive manufacturing is among the most used industrial processes, allowing for the production of customizable and geometrically complex parts at relatively low cost. Although different aspects of the powder spreading process have been investigated, questions remain on the process repeatability on the actual beam–powder bed interaction. Given the influence of the formed bed on the quality of the final part, understanding the spreading mechanism is crucial for process optimization. In this work, a Discrete Element Method (DEM) model of the spreading process is adopted to investigate the spreading process and underline the physical phenomena occurring. With parameters validated through ad hoc experiments, two spreading velocities, accounting for two different flow regimes, are simulated. The powder distribution in both the accumulation and deposition zone is investigated. Attention is placed on how density, effective layer thickness, and particle size distribution vary throughout the powder bed. The physical mechanism leading to the observed characteristics is discussed, effectively defining the window for the process parameters.

An Overview of Additive Manufacturing Technologies-A Review to Technical Synthesis in Numerical Study of Selective Laser Melting

Additive Manufacturing (AM) processes enable their deployment in broad applications from aerospace to art, design, and architecture. Part quality and performance are the main concerns during AM processes execution that the achievement of adequate characteristics can be guaranteed, considering a wide range of influencing factors, such as process parameters, material, environment, measurement, and operators training. Investigating the effects of not only the influential AM processes variables but also their interactions and coupled impacts are essential to process optimization which requires huge efforts to be made. Therefore, numerical simulation can be an effective tool that facilities the evaluation of the AM processes principles. Selective Laser Melting (SLM) is a widespread Powder Bed Fusion (PBF) AM process that due to its superior advantages, such as capability to print complex and highly customized components, which leads to an increasing attention paid by industries and academia. Temperature distribution and melt pool dynamics have paramount importance to be well simulated and correlated by part quality in terms of surface finish, induced residual stress and microstructure evolution during SLM. Summarizing numerical simulations of SLM in this survey is pointed out as one important research perspective as well as exploring the contribution of adopted approaches and practices. This review survey has been organized to give an overview of AM processes such as extrusion, photopolymerization, material jetting, laminated object manufacturing, and powder bed fusion. And in particular is targeted to discuss the conducted numerical simulation of SLM to illustrate a uniform picture of existing nonproprietary approaches to predict the heat transfer, melt pool behavior, microstructure and residual stresses analysis.

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

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 V_s, 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.

Spreading Process Maps for Powder-Bed Additive Manufacturing Derived from Physics Model-Based Machine Learning

The powder bed additive manufacturing (AM) process is comprised of two repetitive steps—spreading of powder and selective fusing or binding the spread layer. The spreading step consists of a rolling and sliding spreader which imposes a shear flow and normal stress on an AM powder between itself and an additively manufactured substrate. Improper spreading can result in parts with a rough exterior and porous interior. Thus it is necessary to develop predictive capabilities for this spreading step. A rheometry-calibrated model based on the polydispersed discrete element method (DEM) and validated for single layer spreading was applied to study the relationship between spreader speeds and spread layer properties of an industrial grade Ti-6Al-4V powder. The spread layer properties used to quantify spreadability of the AM powder, i.e., the ease with which an AM powder spreads under a set of load conditions, include mass of powder retained in the sampling region after spreading, spread throughput, roughness of the spread layer and porosity of the spread layer. Since the physics-based DEM simulations are computationally expensive, physics model-based machine learning, in the form of a feed forward, back propagation neural network, was employed to interpolate between the highly nonlinear results obtained by running modest numbers of DEM simulations. The minimum accuracy of the trained neural network was 96%. A spreading process map was generated to concisely present the relationship between spreader speeds and spreadability parameters.

3D Printing of Bioceramics for Bone Tissue Engineering

Bioceramics have frequent use in functional restoration of hard tissues to improve human well-being. Additive manufacturing (AM) also known as 3D printing is an innovative material processing technique extensively applied to produce bioceramic parts or scaffolds in a layered perspicacious manner. Moreover, the applications of additive manufacturing in bioceramics have the capability to reliably fabricate the commercialized scaffolds tailored for practical clinical applications, and the potential to survive in the new era of effective hard tissue fabrication. The similarity of the materials with human bone histomorphometry makes them conducive to use in hard tissue engineering scheme. The key objective of this manuscript is to explore the applications of bioceramics-based AM in bone tissue engineering. Furthermore, the article comprehensively and categorically summarizes some novel bioceramics based AM techniques for the restoration of bones. At prior stages of this article, different ceramics processing AM techniques have been categorized, subsequently, processing of frequently used materials for bone implants and complexities associated with these materials have been elaborated. At the end, some novel applications of bioceramics in orthopedic implants and some future directions are also highlighted to explore it further. This review article will help the new researchers to understand the basic mechanism and current challenges in neophyte techniques and the applications of bioceramics in the orthopedic prosthesis.

Fabrication of Demineralized Bone Matrix/Polycaprolactone Composites Using Large Area Projection Sintering (LAPS)

Cadaveric decellularized bone tissue is utilized as an allograft in many musculoskeletal surgical procedures. Typically, the allograft acts as a scaffold to guide tissue regeneration with superior biocompatibility relative to synthetic scaffolds. Traditionally these scaffolds are machined into the required dimensions and shapes. However, the geometrical simplicity and, in some cases, limited dimensions of the donated tissue restrict the use of allograft scaffolds. This could be overcome by additive manufacturing using granulated bone that is both decellularized and demineralized. In this study, the large area projection sintering (LAPS) method is evaluated as a fabrication method to build porous structures composed of granulated cortical bone bound by polycaprolactone (PCL). This additive manufacturing method utilizes visible light to selectively cure the deposited material layer-by-layer to create 3D geometry. First, the spreading behavior of the composite mixtures is evaluated and the conditions to attain improved powder bed density to fabricate the test specimens are determined. The tensile strength of the LAPS fabricated samples in both dry and hydrated states are determined and compared to the demineralized cancellous bone allograft and the heat treated demineralized-bone/PCL mixture in mold. The results indicated that the projection sintered composites of 45–55 wt %. Demineralized bone matrix (DBM) particulates produced strength comparable to processed and demineralized cancellous bone.

Revealing particle-scale powder spreading dynamics in powder-bed-based additive manufacturing process by high-speed x-ray imaging

Powder spreading is a key step in the powder-bed-based additive manufacturing process, which determines the quality of the powder bed and, consequently, affects the quality of the manufactured part. However, powder spreading behavior under additive manufacturing condition is still not clear, largely because of the lack of particle-scale experimental study. Here, we studied particle-scale powder dynamics during the powder spreading process by using in-situ high-speed high-energy x-ray imaging. Evolution of the repose angle, slope surface speed, slope surface roughness, and the dynamics of powder clusters at the powder front were revealed and quantified. Interactions of the individual metal powders, with boundaries (substrate and container wall), were characterized, and coefficients of friction between the powders and boundaries were calculated. The effects of particle size on powder flow dynamics were revealed. The particle-scale powder spreading dynamics, reported here, are important for a thorough understanding of powder spreading behavior in the powder-bed-based additive manufacturing process, and are critical to the development and validation of models that can more accurately predict powder spreading behavior.