Bed Fusion Additive Manufacturing Process Research Articles

Recovery of residual polyamide (PA12) from polymer powder bed fusion additive manufacturing process through a binder jetting process

Purpose This study aims to propose the reuse of PA12 (powder) in another AM process, binder jettiinng, which is less sensitive to the chemical and mechanical degradation of the powder after multiple cycles in the laser system. Design/methodology/approach The experimental process for evaluating the reuse of SLS powders in a subsequent binder jetting process consists of four phases: powder characterization, bonding analysis, mixture testing and mixture characteristics. Analyses were carried out using techniques such as Fourier Transform Infrared Spectroscopy, scanning electron microscopy, thermogravimetric analysis and stress–strain tests for tension and compression. The surface roughness, color, hardness and density of the new mixture were also determined to find physical characteristics. A Taguchi design L8 was used to search for a mixture with the best mechanical strength. Findings The results indicated that the integration of waste powder PA12 with calcium sulfate hemihydrate (CSH) generates appropriate particle distribution with rounded particles of PA12 that improve powder flowability. The micropores observed with less than 60 µm, facilitated binder and infiltrant penetration on 3D parts. The 60/40 (CSH-PA12) mixture with epoxy resin postprocessing was found to be the best-bonded mixture in mechanical testing, rugosity and hardness results. The new CSH-PA12 mixture resulted lighter and stronger than the CSH powder commonly used in binder jetting technology. Originality/value This study adds value to the polymer powder bed fusion process by using its waste in a circular process. The novel reuse of PA12 waste in an established process was achieved in an accessible and economical manner.

Laser additive manufacturing of TiB2-modified Cu15Ni8Sn/GH3230 heterogeneous materials: Processability, interfacial microstructure and mechanical performance

Cu/Ni heterogeneous materials integrate excellent thermal conductivity and high-temperature mechanical properties, enabling them to be widely used in the aerospace domain. Differences in the thermal and physical properties of the Cu and Ni materials, however, make them difficult to be processed using the laser powder bed fusion (LPBF) additive manufacturing process. This study systematically examines the effects of various LPBF process parameters on microstructure, element diffusion, bonding strength and microhardness at the Cu/Ni interface, as well as investigating the mechanisms of defect formation within Cu/Ni heterogeneous materials. The results indicate that a reasonable control of laser energy input (< 100 J/mm3) facilitates the Cu/Ni components through strong interfacial metallurgical bonding without pore defect formation. Compared to single-material Cu alloy, the ultimate tensile strength (UTS) of the horizontally bonded Cu/Ni specimen increased by 55.25%, without significant reductions in elongation. The vertically bonded Cu/Ni tensile specimen fractured in the middle of the Cu region rather than the interfacial region, indicating superb interfacial bonding strength. Another advantage lies in the enhancement of thermophysical properties, with a 109.5% increase in thermal conductivity achieved in the LPBF-fabricated Cu/Ni heterogeneous materials compared to the single-material Ni alloy. Quasi-static compression experiments indicated that the Cu/Ni lattice structure could absorb more energy when compressed parallel to the build direction (BD), compared to being perpendicular to the BD. This study provides guidance for the design and manufacture of high-performance Cu/Ni heterogeneous components via LPBF.

L-PBF AM process failures causal chain: an FMEA-based monitoring approach for process control

ABSTRACT The laser powder bed fusion (L-PBF) additive manufacturing process offers many advantages. However, its industrial integration still needs to be improved due to the certification constraints of the produced parts. Thus, this paper proposes a phenomenological causal chain of process failures to ensure the control of the L-PBF process and further certify the quality of the parts produced. Consequences of unsuitable thermal regimes are analysed using a failure mode and effects analysis (FMEA) approach, allowing a more global understanding of all the causal chain-related data. The proposed approach is based on standard acquisition equipment available on industrial machines and proves relevant for identifying process failures. Experimental validation of the proposed monitoring method is implemented on a use case using dedicated software. Finally, it is shown that the method is relevant in this confrontation and compatible with the time scale of the process for future NC integration and real-time monitoring.

Experimental characterisation of the spreading of polymeric powders in powder bed fusion additive manufacturing process at changing temperature conditions

This study investigates the spreadability behaviour of four different polymeric materials, namely Polyamide 6, Polyamide 6 Black, Polypropylene, and Thermoplastic Polyurethane, under different spreading speeds (30 and 3 mm/s) and powder bed temperatures (25, 80, 110 °C) using a purposely developed experimental apparatus. Macroscopic and microscopic images of the powder layer were taken after completing the powder spreading step. A thresholding-based image processing method was utilised to evaluate the fraction of the bed area not covered by particles (NCF), and the standard deviation of pixel intensities in grayscale images (SDG) was calculated to evaluate powder layer quality in macroscopic images. NCF and SDG can provide quantitative evaluation of the quality of the spread layer, NCF in a logarithmic scale ranking and SDG in a linear scale ranking. A wavelet analysis technique was developed on microscopic panorama images obtained with grazing light to characterise the surface roughness of the layer. Results indicate that the spreadability generally worsens much more significantly than powder flow properties at increasing temperatures and, remarkably, that flowability and spreadability are unrelated. As expected, the temperature effect on powder spreading changes for the different powders are mostly governed by the approach to the powder melting temperature. Minor effects on the final layer quality were also observed at changing spreading speed.

Effect of quenching and tempering treatments on microstructure and mechanical properties of 300M ultra-high strength steel fabricated by laser powder bed fusion

To achieve high-performance 300 M steel parts through the Laser Powder Bed Fusion (LPBF) additive manufacturing process, post-heat treatments are indispensable. Herein, the effects of quenching and tempering treatments on the microstructure and mechanical properties of LPBF-fabricated 300M ultra-high strength steel were investigated, and the relevant strengthening and toughening mechanisms were analyzed. The microstructure of quenched samples primarily consisted of quenched martensite with minor amounts of bainite and some grain boundary allotriomorphic ferrite. The quenched samples presented significantly higher strength than the 300M forgings, primarily attributed to the contributions of solid solution strengthening, grain boundary strengthening and dislocation strengthening. After following tempering treatment, the microstructure of LPBF-fabricated samples mainly consisted of tempered martensite with minor amounts of bainite and residual austenite. Compared to the quenched samples, the tempered samples exhibited a decrease in strength while demonstrating a significant increase in ductility. The samples treated with the optimal heat treatment process (900 °C/1 h/Oil Cooling for quenching + two times of 300 °C/2 h/Air Cooling for tempering) demonstrated a remarkable strength–ductility balance, with a yield strength (YS) of 1834 MPa, an ultimate tensile strength (UTS) of 2099 MPa, and an elongation (EL) of 10.2%, which are all beyond or comparable to those of 300M forgings.

Enhancing Part Quality Management Using a Holistic Data Fusion Framework in Metal Powder Bed Fusion Additive Manufacturing

Abstract Metal powder bed fusion additive manufacturing (AM) processes have gained widespread adoption for the ability to produce complex geometries with high performance. However, a multitude of factors still affect the build process, which significantly impacts the adoption rate. This, in turn, leads to great challenges in achieving consistent and reliable part quality. To address this challenge, simulations and measurements have been progressively deployed to provide valuable insights into the quality of individual builds. This paper proposes an AM data fusion framework that combines data sources beyond a single-part, development cycle. Those sources include the aggregation of measurements from multiple builds and the outputs from their related models and simulations. Both can be used to support decision-makings that can improve part quality. The effectiveness of the holistic AM data fusion framework is illustrated through three use case scenarios: one that fuses process data from a single build, one that fusses data from a build and simulation, and one that fuses data from multiple builds. The case studies demonstrate that a data fusion framework can be applied to effectively detect over-melting scan strategies, monitor material melting conditions, and predict down-skin surface defects. Overall, the proposed method provides a practical solution for enhancing part quality management when individual data sources or models have intrinsic limitations.

A new variant of the inherent strain method for the prediction of distortion in powder bed fusion additive manufacturing processes

A new variant of the inherent strain (IS) method is proposed to predict component distortion in powder bed fusion additive manufacturing (AM) that addresses some of the shortcomings of the previous work by accounting for both the compressive plastic strain formed adjacent to the melt pool and the thermal strain associated with the changing macroscale thermal field in the component during fabrication. A 3D thermomechanical finite element (FE) model using the new approach is presented and applied to predict the distortion of a component fabricated in an electron beam powder bed fusion (EB-PBF) machine. To improve computational efficiency, each computational layer is comprised of six powder layers. A time-averaged volumetric heat input based on beam voltage and current data obtained from the EB-PBF system was calculated and applied to each computational layer, consistent with the process timing. The inherent strains were applied per computational layer as an initial anisotropic contribution to the thermal strain at the time of activation of each computational layer, resulting in the sequential establishment of static equilibrium during component fabrication, which accounts for the variation in the local macroscale thermal field. The thermal field and distortion predicted by the thermomechanical model were verified using experimentally derived data. The model predicts in-plane compressive strains in the order of 10−3. Differences in the inherent strain were found at different locations in the component, consistent with differences in the macroscale thermal field. The proposed method is general and may also be applied to the laser powder bed fusion (L-PBF) process.

Investigating the effect of temperature on powder spreading behaviour in powder bed fusion additive manufacturing process by Discrete Element Method

In this study, a Discrete Element Method (DEM)-based model was developed to simulate the powder spreading process in Powder bed Fusion (PBF) for Polyamide 6 (PA6) powder, which considered the spreading speed (3 mm/s and 30 mm/s) and temperature (25 °C and 110 °C) as parameters affecting the final spreading powder layer quality. The particle horizontal and vertical velocities were analysed in regions near the spreading blade, where at the lower spreading speed, particle velocities are far less compared to the higher spreading speed. The lower particle velocities lead to gently settling down and rearranging particles during spreading on the bed, allowing a uniform powder layer to form. Increasing the spreading speed led to an increase in shear stress and inertia number. At higher temperatures, shear stresses also rise while the inertia number is slightly reduced due to the greater cohesion between particles. The generated powder layer by the DEM model was analysed using the wavelet analysis technique and compared to experiments. The spreadability index of experiments can be estimated with less than 5% error using DEM simulations, though in an approximately consistent manner that captures the experimental trends of spreading speed and temperature. The packing fraction of simulated powder layers was investigated in the spreading direction. The DEM simulations show that packing fraction decreases as temperature or spreading speed are increased, with its variation across the bed increasing for higher spreading speeds. Increasing the spreading speed leads to greater motion and inertia number of particles and, consequently, it intensifies the particle ejection and results in many unfilled areas in the spread powder layer. Increasing temperature leads to an increase in cohesivity between particles, resulting in aggregates forming on the spread powder layer.

Understanding Melt Pool Behavior of 316L Stainless Steel in Laser Powder Bed Fusion Additive Manufacturing.

In the laser powder bed fusion additive manufacturing process, the quality of fabrications is intricately tied to the laser-matter interaction, specifically the formation of the melt pool. This study experimentally examined the intricacies of melt pool characteristics and surface topography across diverse laser powers and speeds via single-track laser scanning on a bare plate and powder bed for 316L stainless steel. The results reveal that the presence of a powder layer amplifies melt pool instability and worsens irregularities due to increased laser absorption and the introduction of uneven mass from the powder. To provide a comprehensive understanding of melt pool dynamics, a high-fidelity computational model encompassing fluid dynamics, heat transfer, vaporization, and solidification was developed. It was validated against the measured melt pool dimensions and morphology, effectively predicting conduction and keyholing modes with irregular surface features. Particularly, the model explained the forming mechanisms of a defective morphology, termed swell-undercut, at high power and speed conditions, detailing the roles of recoil pressure and liquid refilling. As an application, multiple-track simulations replicate the surface features on cubic samples under two distinct process conditions, showcasing the potential of the laser-matter interaction model for process optimization.

Prediction of Compressive Behavior of Laser-Powder-Bed Fusion-Processed TPMS Lattices by Regression Analysis

Triply periodic minimal surface (TPMS) structures offer lightweight and high-stiffness solutions to different industrial applications. However, testing of these structures to calculate their mechanical properties is expensive. Therefore, it is important to predict the mechanical properties of these structures effectively. This study focuses on the effectiveness of using regression analysis and equations based on experimental results to predict the mechanical properties of diamond, gyroid, and primitive TPMS structures with different volume fractions and build orientations. Gyroid, diamond, and primitive specimens with three different volume fractions (0.2, 0.3, and 0.4) were manufactured using a laser powder bed fusion (LPBF) additive manufacturing process using three different build orientations (45°, 60°, and 90°) in the present study. Experimental and statistical results revealed that regression analysis and related equations can be used to predict the mass, yield stress, elastic modulus, specific energy absorption, and onset of densification values of TPMS structures with an intermediate volume fraction value and specified build orientation with an error range less than 1.4%, 7.1%, 19.04%, 21.6%, and 13.4%, respectively.

Effect of parameters on quality of IN718 parts using laser additive manufacturing

The objective of this study is to determine the effect of process parameters such as laser power, scanning speed and layer thickness on the mechanical properties, microstructure and fracture mechanism of Inconel 718 using laser powder bed fusion additive manufacturing process. Full factorial design, regression modelling and response surface methodology are used to optimise the process parameters. The highest tensile strength occurs at 350 W laser power, 1300 mm/s scanning speed and 30 µm layer thickness. The optimal parameters for multi-objective optimisation are identical to those used for single-objective optimisation for tensile strength. The difference between the predicted and actual tensile strength is 0.33%. This work shows a successful methodology using IN718 superalloy for various applications in aerospace industry.

Accelerating phase-field simulation of three-dimensional microstructure evolution in laser powder bed fusion with composable machine learning predictions

Phase-field (PF) modeling is a versatile physics-based computational method that has been used to simulate the evolution of microstructures. The PF method can produce accurate microstructures but suffers from a high computational cost, limiting its use in length scales relevant to additive manufacturing. Using small-scale PF simulations as training data, we trained a surrogate machine learning (ML) model as a computationally cheaper alternative. We use a three-dimensional (3D) U-Net convolutional neural network and learn microstructure evolution in a supervised fashion. With initial microstructure and thermal history as inputs, the ML model can predict the resulting grain orientations at a high accuracy compared to the PF model. Computationally, the ML model is orders of magnitudes faster than the direct PF simulation in a GPU implementation, and scales favorably with increasing number of cells. By spatio-temporally composing multiple ML model predictions at the small-scale, we demonstrate a large-scale 64-layer simulation of a 2 mm × 2 mm × 2 mm cube for a powder bed fusion additive manufacturing process. The ML results revealed a mixture of equiaxed, columnar, and curved grains, comparable to experimental observations. Microstructures resulting from different toolpath strategies, and lack of fusion defects are also demonstrated. This approach paves the way for microstructure-driven process design.

Achieving superelastic shape recoverability in smart flexible CuAlMn metamaterials via 3D printing

Despite the remarkable advancements in the additive manufacturing of metamaterials, tradeoffs remain between functionality and mechanical performance owning to static configuration, which limits their application, particularly in areas that require efficient multifunctionality. In this paper, we present a novel approach for fabricating multifunctional smart flexible metal metamaterials using laser powder bed fusion technology. This approach enables the reversible recovery superelastic strain exceeding 20 % with a 100 % recovery rate—ten times higher than that observed in the printed alloy. This is achieved by utilising an innovative metamaterial structural design and a novel shape memory alloy powder. To achieve the aforementioned purpose, the metamaterial unit cells were initially designed to ensure flexible deformation ability with a Poisson's ratio of zero. Then, we prepared a novel shape memory alloy composition of Cu-18at%Al-l0at%Mn-0.3 at%Si, which exhibited excellent printability and adaptability within the laser powder bed fusion additive manufacturing process. Additionally, the printed SMA exhibited superelasticity, one-way and two-way shape memory effect under varying parameters. Furthermore, the combination of multifunctionality into the flexible CuAlMn metamaterials was achieved by manipulating process parameters. Remarkably, the printed metamaterial demonstrates exceptional flexibility deformation, and presents superelasticity or shape memory effect, ensuring the recovery of its original shape after experiencing deformation. This work not only demonstrates the vast potential of utilising additive manufacturing technology for fabricating functional and adaptable metal metamaterials but also presents an innovative approach for creating smart metal metamaterial.

Effect of hard and soft re-coater blade on porosity and processability of thin walls and overhangs in laser powder bed fusion additive manufacturing

AbstractSpreading powder into thin layers is a fundamental step in the laser powder bed fusion (PBF-LB) additive manufacturing process. This step is called re-coating and it is typically performed using either a hard, soft or brush-type re-coater blade or a rotating roller, depending on the machine brand and model. With such variety in powder spreading approaches, the question arises whether the used re-coater type has a significant effect on the quality of parts produced? In this study, an industrial contact image sensor integrated to the re-coater of a PBF-LB system was used for powder bed quality monitoring. Powder bed images at 21 µm/pixel resolution, 184 mm scanning width and 95 mm/s re-coating speed were acquired. With this, the effect of using either soft (rubber) or hard (steel) re-coater blade on the processability of challenging features such as thin walls and steep overhangs was studied. In addition, porosity and dimensional accuracy of parts produced using either the soft or hard blade was analyzed with X-ray computed tomography. It is shown that when building bulk material without any complex features, both the hard and soft re-coating blade results in extremely low porosity ≤ 0.001% without any issues in the processability. However, when thin walls and overhangs are produced, differences in processability, porosity and dimensional accuracy are observed as a function of re-coater blade and part orientation. This is an important factor in understanding all the significant sources contributing to the variability on quality of parts produced using different PBF-LB machines.

A highly efficient computational approach for fast scan-resolved simulations of metal additive manufacturing processes on the scale of real parts

This article proposes a novel high-performance computing approach for the prediction of the temperature field in powder bed fusion (PBF) additive manufacturing (AM) processes. In contrast to many existing approaches to part-scale simulations, the underlying computational model consistently resolves physical scan tracks without additional heat source scaling, agglomeration strategies or any other heuristic modeling assumptions. A growing, adaptively refined mesh accurately captures all details of the laser beam motion. Critically, the fine spatial resolution required for resolved scan tracks in combination with the high scan velocities underlying these processes mandates the use of comparatively small time steps to resolve the underlying physics. Explicit time integration schemes are well-suited for this setting, while unconditionally stable implicit time integration schemes are employed for the interlayer cool down phase governed by significantly larger time scales. These two schemes are combined and implemented in an efficient fast operator evaluation framework providing significant performance gains and optimization opportunities. The capabilities of the novel framework are demonstrated through realistic AM examples on the centimeter scale including the first scan-resolved simulation of the entire NIST AM Benchmark cantilever specimen, with a computation time of less than one day. Apart from physical insights gained through these simulation examples, also numerical aspects are thoroughly studied on basis of weak and strong parallel scaling tests. As potential applications, the proposed thermal PBF simulation approach can serve as a basis for microstructure and thermo-mechanical predictions on the part-scale, but also to assess the influence of scan pattern and part geometry on melt pool shape and temperature, which are important indicators for well-known process instabilities.

Laser powder bed fusion of Inconel 718-based composites: Effect of TiB2 content on microstructure and mechanical performance

The laser powder bed fusion (LPBF) additive manufacturing process has been extensively used to manufacture various nickel-based metal components because it offers the capability of manufacturing three-dimensional structures with complex shapes directly from raw materials. Although LPBF-fabricated Inconel 718 (IN718) superalloys have been successfully applied in the aerospace field, IN718-based composites can offer an alternative pathway to further enhance high-temperature performance. This systematic study examined the effect of various TiB2 contents on the microstructure and mechanical performance of IN718 fabricated by LPBF. Pure IN718 (IN718-P), IN718-1 wt% TiB2 (IN718-1) and IN718-2 wt% TiB2 (IN718-2) composites were nearly fully dense, with relative densities of 99.71%, 99.34% and 99.67% respectively, when fabricated under the optimal process parameters. The degree of grain size refinement was greater for IN718-2 than for IN718-1, and the IN718-1 grains were mainly refined in the width direction, while the IN718-2 grains were refined in both the width and length directions. The proportion of low-angle grain boundaries was significantly higher for the composites than for IN718-P, and it increased with increasing proportions of TiB2. Compared with the IN718-P sample, the microhardness, yield strength and ultimate tensile strength of IN718-2 at room temperature were increased by 19.93%, 24.83% and 11.07%, respectively, while the yield strength and ultimate tensile strength of IN718-2 at a high temperature of 650 °C were increased by 31.76% and 17.62%, respectively. This indicated that the enhancement of mechanical performance was more noticeable at high temperature than at room temperature. By contrast, less improvement in mechanical properties was achieved by adding 1 wt% TiB2 particles than by adding 2 wt% TiB2 particles. These findings indicate an alternative way to manufacture IN718 superalloys with improved mechanical properties through the synthesis of composite materials.

Developing a novel high-strength Mg-Gd-Y-Zn-Mn alloy for laser powder bed fusion additive manufacturing process

Laser powder bed fusion (LPBF) of Mg alloys mainly focuses on the traditional commercial casting Mg alloys such as AZ91D, ZK60 and WE43, which usually display relatively low tensile strengths. Herein we developed a novel high-strength Mg-12Gd-2Y-1Zn-0.5Mn (wt.%, GWZ1221M) alloy for the LPBF additive manufacturing process, and the evolution of microstructure and mechanical properties from the as-built state to LPBF-T4 and LPBF-T6 states was systematically investigated. The as-built GWZ1221M alloy exhibited fine equiaxed grains with an average grain size of only 4.3 ± 2.2 μm, while the as-cast alloy displayed typical coarse dendrite grains (178.2 ± 73.6 μm). Thus, the as-built alloy showed significantly higher tensile strengths than the as-cast counterpart, and its yield strength (YS), ultimate tensile strength (UTS) and elongation (EL) were 315 ± 8 MPa, 340 ± 7 MPa and 2.7 ± 0.5 % respectively. Solution treatment transformed hard and brittle β-(Mg,Zn)3(Gd,Y) phase into basal X phase and lamellar long period stacking ordered (LPSO) with better plastic deformability, leading to the improvement of EL. Then peak-aging heat treatment introduced numerous nano-sized prismatic β′ precipitates inside grains, resulting in the enhancement of YS. Finally, the LPBF-T6 alloy achieved appreciably high strength with YS, UTS and EL of 320 ± 3 MPa, 395 ± 4 MPa and 2.1 ± 0.4 % respectively. Both as-built and LPBF-T6 GWZ1221M alloys showed remarkably higher tensile strengths than the as-cast counterparts and as-built commercial Mg alloys, highlighting the great potential of high-strength as-built Mg-Gd based alloys for structural applications.

A novel multiscale process simulation to predict the impact of intrinsic heat treatment on local microstructure gradients and bulk hardness of AISI 4140 manufactured by laser powder bed fusion

ABSTRACT Although finite element model based process simulations for the laser powder bed fusion additive manufacturing process have become more common in the recent years, the proposed approaches are often only viable for materials without complex phase transformations. Process simulations for materials such as the quench and tempering steel AISI 4140 typically lead to higher computational cost due to the finer mesh and time steps needed for more complex material models. This study proposes a novel multiscale approach to combine the advantages of the macroscale and mesoscale models into one framework, in order to reduce computational cost while retaining the high accuracy. The implementation of these multiscale methods was validated by experimentally analyzing multiple parameter combinations regarding bulk hardness and local microstructure differences. The results show an accurate prediction of bulk hardness and localised tempering effects while reducing the computational cost in order to simulate the component scale.

Understanding the corrosion behaviour of Al-Mg alloy fabricated using a Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) process

Metal additive manufacturing (AM) is an emerging disruptive technology capable of manufacturing complex shaped components that are difficult to manufacture through conventional methods. However, the corrosion behaviour of AM fabricated parts must be considered for safety critical applications. For this reason, we have studied the relationship between AM fabricated Scalmalloy (Al-Mg-Sc-Zr) microstructures and their corresponding corrosion behaviours. This comparison has been drawn against a comparable commercial Al-Mg alloy (5182). The corrosion resistance of the samples in salt water was assessed via various electrochemical analytics techniques. It was observed that Scalmalloy produced better corrosion resistance than 5182 Al-alloy. This can be attributed to the spontaneous formation of a passive film on refined AM microstructure and the presence of Sc and Zr, specifically when samples were fabricated with higher density (less porosity). The alloys’ corrosion mechanisms were dependent on immersion time and the microstructural features of the samples.

In-situ observation of powder spreading in powder bed fusion metal additive manufacturing process using particle image velocimetry

Providing a dense powder bed is necessary to ensure the rationality of the final product prepared by powder bed fusion-based additive manufacturing under broad building parameters. In this study, the powder spreading mechanism was elucidated using particle image velocimetry and discrete element simulations. The particle flow regimes in the spreading process were identified based on the particle displacement: alignment, rotation, and deposition. The alignment regime was dominant in gas-atomized stainless steel 304 powder piles, whereas the rotation regime was dominant in plasma rotating electrode processed stainless steel 304 powder piles. A high-fidelity spreading simulation model was developed to clarify the critical factors resulting in the different flow regimes of different stainless steel 304 powders. The dominant rotational regime of the plasma rotating electrode processed powder was substituted for alignment by increasing the cohesive force. The particle supply in the spreading process was further suppressed by increasing the cohesive force, owing to the formation of a strong force arch and agglomeration. The high cohesive force in the gas-atomized powder was mainly attributed to the electrostatic force caused by the thick oxide film. Therefore, it was proven that the oxide film thickness is a key factor in determining the powder spreading mechanism and powder bed quality in the powder bed fusion additive manufacturing process.