Influence of multiple scan fields on the processing of 316L stainless steel using laser powder bed fusion

The sharp growth that additive manufacturing has been showing recently has broadened its application field and resulted in more varied demand of high-volume parts as well as a general increase in part series. The current focus on productivity enhancement of additive manufacturing has imposed the implementation of multiple-laser systems with larger scan fields. Its usage, combined with adequate layer thickness and laser power selection, makes high-volume parts less challenging to obtain. This paper focuses on understanding the influence of using multiple-scan fields for the fabrication of large components, especially on the parts region corresponding to scan field interface. The microstructure as well as mechanical behaviour of the multi-field manufactured samples are compared with parts fabricated using a single-field, for distinct processing parameters. Moreover, given the unreliability of additive manufacturing regarding dimensional and geometrical tolerances with increasing build rates, post-processing metal-cutting operations were studied towards additive manufacturing process hybridization. Despite the typical additive manufacturing process variability, a set of parameters, within testing conditions, could be identified as the most appropriate solution towards mechanical strength enhancement. Nonetheless, porosity levels can significantly impact the ductility of parts, which may be additionally compromised by its occurrence in the scan-field interface region.

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Toward Metamodels for Composable and Reusable Additive Manufacturing Process Models

Journal of Manufacturing Science and Engineering ◽

10.1115/1.4028533 ◽

2014 ◽

Vol 136 (6) ◽

Cited By ~ 28

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.

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Additive Manufacturing of Glass

Journal of Manufacturing Science and Engineering ◽

10.1115/1.4028531 ◽

2014 ◽

Vol 136 (6) ◽

Cited By ~ 48

Author(s):

Junjie Luo ◽

Heng Pan ◽

Edward C. Kinzel

Keyword(s):

Additive Manufacturing ◽

Glass Powder ◽

Processing Parameters ◽

Gradient Index ◽

Continuous Line ◽

Single Track ◽

Laser Melting ◽

Powder Bed ◽

Transparent Parts ◽

Insight Into

Selective laser melting (SLM) is a technique for the additive manufacturing (AM) of metals, plastics, and even ceramics. This paper explores using SLM for depositing glass structures. A CO2 laser is used to locally melt portions of a powder bed to study the effects of process parameters on stationary particle formation as well as continuous line quality. Numerical modeling is also applied to gain insight into the physical process. The experimental and numerical results indicate that the absorptivity of the glass powder is nearly constant with respect to the processing parameters. These results are used to deposit layered single-track wide walls to demonstrate the potential of using the SLM process for building transparent parts. Finally, the powder bed process is compared to a wire-fed approach. AM of glass is relevant for gradient index optics, systems with embedded optics, and the formation of hermetic seals.

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A multi-scale multi-physics modeling framework of laser powder bed fusion additive manufacturing process

Metal Powder Report ◽

10.1016/j.mprp.2018.01.003 ◽

2018 ◽

Vol 73 (3) ◽

pp. 151-157 ◽

Cited By ~ 8

Author(s):

Jing Zhang ◽

Yi Zhang ◽

Weng Hoh Lee ◽

Linmin Wu ◽

Hyun-Hee Choi ◽

...

Keyword(s):

Additive Manufacturing ◽

Manufacturing Process ◽

Powder Bed Fusion ◽

Laser Powder Bed Fusion ◽

Modeling Framework ◽

Powder Bed ◽

Multi Scale ◽

Physics Modeling

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Comparison of Electron Beam and Laser Beam Powder Bed Fusion Additive Manufacturing Process for High Temperature Turbine Component Materials, Phase II

10.2172/1658007 ◽

2019 ◽

Author(s):

Sebastien Dryepondt ◽

Michael Kirka ◽

Daniel Ryan

Keyword(s):

Electron Beam ◽

High Temperature ◽

Additive Manufacturing ◽

Laser Beam ◽

Phase Ii ◽

Manufacturing Process ◽

Powder Bed Fusion ◽

Powder Bed ◽

Turbine Component

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Bayesian Calibration of Multiple Coupled Simulation Models for Metal Additive Manufacturing: A Bayesian Network Approach

ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg ◽

10.1115/1.4052270 ◽

2021 ◽

Author(s):

Jiahui Ye ◽

Mohamad Mahmoudi ◽

Kubra Karayagiz ◽

Luke Johnson ◽

Raiyan Seede ◽

...

Keyword(s):

Additive Manufacturing ◽

Bayesian Network ◽

Simulation Models ◽

Processing Parameters ◽

Network Approach ◽

Structure Property ◽

Coupled Simulation ◽

Niobium Alloys ◽

Powder Bed ◽

Physical Phenomena

Abstract Modeling and simulation for additive manufacturing (AM) are critical enablers for understanding process physics, conducting process planning and optimization, and streamlining qualification and certification. It is often the case that a suite of hierarchically linked (or coupled) simulation models is needed to achieve the above task, as the entirety of the complex physical phenomena relevant to the understanding of process-structure-property-performance relationships in the context of AM precludes the use of a single simulation framework. In this study using a Bayesian network approach, we address the important problem of conducting uncertainty quantification (UQ) analysis for multiple hierarchical models to establish process-microstructure relationships in laser powder bed fusion (LPBF) AM. More significantly, we present the framework to calibrate and analyze simulation models that have unmeasurable variables, which are quantities of interest predicted by an upstream model and necessary for the downstream model in the chain that are difficult or impossible to observe experimentally. We validate the framework using a case study on predicting the microstructure of binary nickel-niobium alloys processed using LPBF as a function of processing parameters. Our framework is shown to be able to predict segregation of niobium with up to 94.3% prediction accuracy in test data.

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