scholarly journals Numerical Modeling of the Additive Manufacturing (AM) Processes of Titanium Alloy

10.5772/34848 ◽  
2012 ◽  
Author(s):  
Zhiqiang Fan ◽  
Frank Liou
Keyword(s):  
Numerical Modeling ◽  
Titanium Alloy ◽  
Additive Manufacturing ◽  
Am Processes

Electrochemical Surface Finishing of Additively Manufactured Parts

2018 ◽  
Author(s):  
Holly Garich ◽  
Tim Hall ◽  
Jennings E. Taylor ◽  
Danny Lui ◽  
John Porter ◽  
...  
Keyword(s):  
Titanium Alloy ◽  
Electron Beam ◽  
Additive Manufacturing ◽  
Surface Finish ◽  
Material Removal ◽  
Surface Finishing ◽  
Metallic Materials ◽  
Powder Bed ◽  
Am Processes ◽  
Complex Components

Additive manufacturing (AM) processes have the potential to revolutionize the art of manufacturing complex components, essentially enabling a build to print scenario where the designer has unlimited bounds. However, when printing fine featured metallic materials using powder bed (pb) approaches the surface left by the AM process are usually rough with adherent particles (20 to 75 µm in diameter) covering the entirety of the surface. This work discusses an electrochemical surface finishing approach for the titanium alloy Ti64 prepared by an electron beam pb-AM process. The goal of this work is to achieve the desired surface finish while minimizing material removal.

scholarly journals MODEL-BASED DESIGN OF AM COMPONENTS TO ENABLE DECENTRALIZED DIGITAL MANUFACTURING SYSTEMS

2021 ◽  
Vol 1 ◽  
pp. 2127-2136
Author(s):  
Olivia Borgue ◽  
John Stavridis ◽  
Tomas Vannucci ◽  
Panagiotis Stavropoulos ◽  
Harry Bikas ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Data Generation ◽  
Production Networks ◽  
Model Based ◽  
Manufacturing Technologies ◽  
Am Processes ◽  
Final Consumer

AbstractAdditive manufacturing (AM) is a versatile technology that could add flexibility in manufacturing processes, whether implemented alone or along other technologies. This technology enables on-demand production and decentralized production networks, as production facilities can be located around the world to manufacture products closer to the final consumer (decentralized manufacturing). However, the wide adoption of additive manufacturing technologies is hindered by the lack of experience on its implementation, the lack of repeatability among different manufacturers and a lack of integrated production systems. The later, hinders the traceability and quality assurance of printed components and limits the understanding and data generation of the AM processes and parameters. In this article, a design strategy is proposed to integrate the different phases of the development process into a model-based design platform for decentralized manufacturing. This platform is aimed at facilitating data traceability and product repeatability among different AM machines. The strategy is illustrated with a case study where a car steering knuckle is manufactured in three different facilities in Sweden and Italy.

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.

Recent Developments of the Multiphysics Discrete Element Method for Additive Manufacturing Modeling and Simulation

2017 ◽  
Author(s):  
John C. Steuben ◽  
Athanasios P. Iliopoulos ◽  
John G. Michopoulos
Keyword(s):  
Additive Manufacturing ◽  
Discrete Element Method ◽  
Discrete Element ◽  
Additive Manufacture ◽  
Computational Tools ◽  
Computational Performance ◽  
Macro Scale ◽  
Recent Developments ◽  
Am Processes ◽  
Element Method

Recent years have seen a sharp increase in the development and usage of Additive Manufacturing (AM) technologies for a broad range of scientific and industrial purposes. The drastic microstructural differences between materials produced via AM and conventional methods has motivated the development of computational tools that model and simulate AM processes in order to facilitate their control for the purpose of optimizing the desired outcomes. This paper discusses recent advances in the continuing development of the Multiphysics Discrete Element Method (MDEM) for the simulation of AM processes. This particle-based method elegantly encapsulates the relevant physics of powder-based AM processes. In particular, the enrichment of the underlying constitutive behaviors to include thermoplasticity is discussed, as are methodologies for modeling the melting and re-solidification of the feedstock materials. Algorithmic improvements that increase computational performance are also discussed. The MDEM is demonstrated to enable the simulation of the additive manufacture of macro-scale components. Concluding remarks are given on the tasks required for the future development of the MDEM, and the topic of experimental validation is also discussed.

A review on wire and arc additive manufacturing of titanium alloy

2021 ◽  
Vol 70 ◽  
pp. 24-45
Author(s):  
Zidong Lin ◽  
Kaijie Song ◽  
Xinghua Yu
Keyword(s):  
Titanium Alloy ◽  
Additive Manufacturing

A Scalable Framework for Process-Aware Thermal Simulation of Additive Manufacturing Processes

2021 ◽  
pp. 1-16
Author(s):  
Yaqi Zhang ◽  
Vadim Shapiro ◽  
Paul Witherell
Keyword(s):  
Additive Manufacturing ◽  
Heat Source ◽  
Spatial Data ◽  
Manufacturing Process ◽  
Thermal Simulation ◽  
Physical Parameters ◽  
Moving Heat Source ◽  
Time Step ◽  
Fused Deposition ◽  
Am Processes

Abstract Many additive manufacturing (AM) processes are driven by a moving heat source. Thermal field evolution during the manufacturing process plays an important role in determining both geometric and mechanical properties of the fabricated parts. Thermal simulation of AM processes is challenging due to the geometric complexity of the manufacturing process and inherent computational complexity that requires a numerical solution at every time increment of the process. We propose a new general computational framework that supports scalable thermal simulation at path scale of any AM process driven by a moving heat source. The proposed framework has three novel ingredients. First, the path-level discretization is process-aware, which is based on the manufacturing primitives described by the scan path and the thermal model is formulated directly in terms of manufacturing primitives. Second, a spatial data structure, called contact graph, is used to represent the discretized domain and capture all possible thermal interactions during the simulation. Finally, the simulation is localized based on specific physical parameters of the manufacturing process, requiring at most a constant number of updates at each time step. The latter implies that the constructed simulation not only scales to handle three-dimensional (3D) printed components of arbitrary complexity but also can achieve real-time performance. To demonstrate the efficacy and generality of the framework, it has been successfully applied to build thermal simulations of two different AM processes, fused deposition modeling (FDM) and powder bed fusion (PBF).

In situ design of advanced titanium alloy with concentration modulations by additive manufacturing

Science ◽  
2021 ◽  
Vol 374 (6566) ◽  
pp. 478-482
Author(s):  
Tianlong Zhang ◽  
Zhenghua Huang ◽  
Tao Yang ◽  
Haojie Kong ◽  
Junhua Luan ◽  
...  
Keyword(s):  
Titanium Alloy ◽  
Additive Manufacturing

Design for Additive Manufacturing in the Cloud Platform

2017 ◽  
Author(s):  
Yuanbin Wang ◽  
Robert Blache ◽  
Xun Xu
Keyword(s):  
Knowledge Management ◽  
Decision Support ◽  
Additive Manufacturing ◽  
Full Advantage ◽  
New Technologies ◽  
Design Stage ◽  
Design For Additive Manufacturing ◽  
Cloud Platform ◽  
Am Processes

Additive manufacturing (AM) has experienced a phenomenal expansion in recent years and new technologies and materials rapidly emerge in the market. Design for Additive Manufacturing (DfAM) becomes more and more important to take full advantage of the capabilities provided by AM. However, most people still have limited knowledge to make informed decisions in the design stage. Therefore, an interactive DfAM system in the cloud platform is proposed to enable people sharing the knowledge in this field and guide the designers to utilize AM efficiently. There are two major modules in the system, decision support module and knowledge management module. A case study is presented to illustrate how this system can help the designers understand the capabilities of AM processes and make rational decisions.

Sign in / Sign up

Export Citation Format

Share Document