Fundamental Requirements for Data Representations in Laser-Based Powder Bed Fusion

2015 ◽  
Author(s):  
Shaw C. Feng ◽  
Paul W. Witherell ◽  
Gaurav Ameta ◽  
Duck Bong Kim
Keyword(s):  
Additive Manufacturing ◽  
Heterogeneous Systems ◽  
Powder Bed Fusion ◽  
Process Data ◽  
Data Interoperability ◽  
Powder Bed ◽  
Related Data ◽  
Data Representations ◽  
Am Processes

Additive Manufacturing (AM) processes intertwine aspects of many different engineering-related disciplines, such as material metrology, design, in-situ and off-line measurements, and controls. Due to the increasing complexity of AM systems and processes, data cannot be shared among heterogeneous systems because of a lack of a common vocabulary and data interoperability methods. This paper aims to address insufficiencies in laser-based Powder Bed Fusion (PBF), a specific AM process, data representations to improve data management and reuse in PBF. Our approach is to formally decompose the processes and align PBF process-specifics with information elements as fundamental requirements for representing process-related data. The paper defines the organization and flow of process information. After modeling selected PBF processes and sub-processes as activities, we discuss requirements for the development of more advanced process data models that provide common terminology and process knowledge for managing data from various stages in AM.

Toward Metamodels for Composable and Reusable Additive Manufacturing Process Models

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Paul Witherell ◽  
Shaw Feng ◽  
Timothy W. Simpson ◽  
David B. Saint John ◽  
Pan Michaleris ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Metal Powder ◽  
Manufacturing Process ◽  
Process Model ◽  
Model Development ◽  
Process Models ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Future Work ◽  
Am Processes

In this paper, we advocate for a more harmonized approach to model development for additive manufacturing (AM) processes, through classification and metamodeling that will support AM process model composability, reusability, and integration. We review several types of AM process models and use the direct metal powder bed fusion AM process to provide illustrative examples of the proposed classification and metamodel approach. We describe how a coordinated approach can be used to extend modeling capabilities by promoting model composability. As part of future work, a framework is envisioned to realize a more coherent strategy for model development and deployment.

scholarly journals Correlation between surface texture and internal defects in laser powder-bed fusion additive manufacturing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Makiko Yonehara ◽  
Chika Kato ◽  
Toshi-Taka Ikeshoji ◽  
Koki Takeshita ◽  
Hideki Kyogoku
Keyword(s):  
Additive Manufacturing ◽  
Surface Texture ◽  
In Situ Monitoring ◽  
Mean Square ◽  
Powder Bed Fusion ◽  
Internal Defects ◽  
Powder Bed ◽  
Texture Parameters ◽  
Areal Surface

AbstractThe availability of an in-situ monitoring and feedback control system during the implementation of metal additive manufacturing technology ensures that high-quality finished parts are manufactured. This study aims to investigate the correlation between the surface texture and internal defects or density of laser-beam powder-bed fusion (LB-PBF) parts. In this study, 120 cubic specimens were fabricated via application of the LB-PBF process to the IN 718 Ni alloy powder. The density and 35 areal surface-texture parameters of manufactured specimens were determined based on the ISO 25,178–2 standard. Using a statistical method, a strong correlation was observed between the areal surface-texture parameters and density or internal defects within specimens. In particular, the areal surface-texture parameters of reduced dale height, core height, root-mean-square height, and root-mean-square gradient demonstrate a strong correlation with specimen density. Therefore, in-situ monitoring of these areal surface-texture parameters can facilitate their use as control variables in the feedback system.

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

Materials ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 3895 ◽  
Author(s):  
Abbas Razavykia ◽  
Eugenio Brusa ◽  
Cristiana Delprete ◽  
Reza Yavari
Keyword(s):  
Numerical Simulation ◽  
Additive Manufacturing ◽  
Selective Laser Melting ◽  
Powder Bed Fusion ◽  
Laser Melting ◽  
Powder Bed ◽  
Part Quality ◽  
Melt Pool ◽  
Wide Range ◽  
Am Processes

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.

scholarly journals In-situ characterization of laser-powder interaction and cooling rates through high-speed imaging of powder bed fusion additive manufacturing

2017 ◽  
Vol 135 ◽  
pp. 385-396 ◽  
Author(s):  
Umberto Scipioni Bertoli ◽  
Gabe Guss ◽  
Sheldon Wu ◽  
Manyalibo J. Matthews ◽  
Julie M. Schoenung
Keyword(s):  
Additive Manufacturing ◽  
High Speed ◽  
Powder Bed Fusion ◽  
In Situ Characterization ◽  
High Speed Imaging ◽  
Cooling Rates ◽  
Powder Bed

Powder-Scale Meshfree Simulations of Powder Bed Fusion Based Additive Manufacturing Processes

2019 ◽  
Author(s):  
Zongyue Fan ◽  
Hao Wang ◽  
Bo Li
Keyword(s):  
Additive Manufacturing ◽  
Optimal Transportation ◽  
The Novel ◽  
Powder Bed Fusion ◽  
Computational Framework ◽  
Powder Bed ◽  
Materials Behaviors ◽  
Melt Pool ◽  
Powder Particles ◽  
Am Processes

Abstract We present a powder-scale meshfree direct numerical simulation (DNS) capability for the powder bed fusion (PBF) based additive manufacturing (AM) processes using the novel Hot Optimal Transportation Meshfree (HOTM) method. The HOTM method is an incremental Lagrangian meshfree computational framework for materials behaviors under extreme thermomechanical loading conditions, which combines the Optimal Transportation Meshfree (OTM) method and the variational thermomechanical constitutive updates. The realistic multi-layer powder bed geometry is modeled explicitly in the HOTM simulations based on experimental data. A phase-aware constitutive model is developed to predict the phase change and multiphase mixing during the PBF AM processes automatically. The governing equations including the linear momentum and energy conservation equations are solved for the multiphase flow simultaneously to predict the deformation, temperature and local state of the powder particles. The powder-scale DNS is employed to study the influence of various laser powers on the melt pool thermodynamics.

scholarly journals In-situ Synchrotron imaging of keyhole mode multi-layer laser powder bed fusion additive manufacturing

2020 ◽  
Vol 20 ◽  
pp. 100650 ◽  
Author(s):  
Yunhui Chen ◽  
Samuel J. Clark ◽  
Chu Lun Alex Leung ◽  
Lorna Sinclair ◽  
Sebastian Marussi ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Synchrotron Imaging

Ultrasonics for monitoring melt pool dynamics and in situ sensing of microstructure during powder bed fusion additive manufacturing

2021 ◽  
Vol 150 (4) ◽  
pp. A307-A307
Author(s):  
Christopher M. Kube ◽  
Nathan Kizer ◽  
Abdalla Nassar ◽  
Edward Reutzel ◽  
Haifeng Zhang ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
In Situ Sensing

scholarly journals In Situ 3D Monitoring of Geometric Signatures in the Powder-Bed-Fusion Additive Manufacturing Process via Vision Sensing Methods

Sensors ◽  
2018 ◽  
Vol 18 (4) ◽  
pp. 1180 ◽  
Author(s):  
Zhongwei Li ◽  
Xingjian Liu ◽  
Shifeng Wen ◽  
Piyao He ◽  
Kai Zhong ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Manufacturing Process ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Vision Sensing
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