Modeling Microstructure of AM Processes Using the FE Method ✶ ✶This chapter is based upon the original work: Jeff Irwin, Edward W. Reutzel, Pan Michaleris, Jay Keist, and Abdalla R. Nassar, “Predicting Microstructure from Thermal History during Additive Manufacturing for Ti-6Al-4V.” J Manuf Sci Eng 138(11) (2016): 111007-1 to 111007-11.

2018 ◽  
pp. 117-135
Author(s):  
Jeff Irwin
Keyword(s):  
Additive Manufacturing ◽  
Thermal History ◽  
Original Work ◽  
Fe Method ◽  
Am Processes

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 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).

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.

Differential Performance Signature Qualification for Additively Manufactured Parts

2018 ◽  
Author(s):  
John G. Michopoulos ◽  
John C. Steuben ◽  
Athanasios P. Iliopoulos
Keyword(s):  
Additive Manufacturing ◽  
Graphical Representation ◽  
Functional Performance ◽  
Complex Objects ◽  
Aircraft Landing ◽  
Differential Performance ◽  
Aircraft Landing Gear ◽  
Am Processes ◽  
Comparison Measures ◽  
Quantities Of Interest

Additive Manufacturing (AM) technologies and associated processes, enable successive accretion of material to a domain, and permit manufacturing of highly complex objects which would otherwise be unrealizable. However, the material micro- and meso-structures generated by AM processes can differ remarkably from those arising from conventional manufacturing (CM) methods. Often, a consequence of this fact is the sub-standard functional performance of the produced parts that can limit the use of AM in some applications. In the present work, we propose a rapid functional qualification methodology for AM-produced parts based on a concept defined as differential Performance Signature Qualification (dPSQ). The concept of Performance Signature (PerSig) is introduced both as a vector of featured quantities of interest (QoIs), and a graphical representation in the form of radar or spider graph, representing the QoIs associated with the performance of relevant parts. The PerSigs are defined for both the prequalified CM parts and the AM-produced ones. Comparison measures are defined and enable the construction of differential PerSigs (dPerSig) in a manner that captures the differential performance of the AM part vs. the prequalified CM one. The dPerSigs enable AM part qualification based on how their PerSigs are different from those of prequalified CM parts. After defining the steps of the proposed methodology, we describe its application on a part of an aircraft landing gear assembly and demonstrate its feasibility.

Design for Additive Manufacturing of Cellular Compliant Mechanism Using Thermal History Feedback

2018 ◽  
Author(s):  
Jivtesh Khurana ◽  
Bradley Hanks ◽  
Mary Frecker
Keyword(s):  
Additive Manufacturing ◽  
Energy Absorption ◽  
Thermal History ◽  
Test Problem ◽  
Compliant Mechanisms ◽  
Compliant Mechanism ◽  
Absorption Capacity ◽  
Unit Cell ◽  
Design For Additive Manufacturing ◽  
Area Of Interest

With growing interest in metal additive manufacturing, one area of interest for design for additive manufacturing is the ability to understand how part geometry combined with the manufacturing process will affect part performance. In addition, many researchers are pursuing design for additive manufacturing with the goal of generating designs for stiff and lightweight applications as opposed to tailored compliance. A compliant mechanism has unique advantages over traditional mechanisms but previously, complex 3D compliant mechanisms have been limited by manufacturability. Recent advances in additive manufacturing enable fabrication of more complex and 3D metal compliant mechanisms, an area of research that is relatively unexplored. In this paper, a design for additive manufacturing workflow is proposed that incorporates feedback to a designer on both the structural performance and manufacturability. Specifically, a cellular contact-aided compliant mechanism for energy absorption is used as a test problem. Insights gained from finite element simulations of the energy absorbed as well as the thermal history from an AM build simulation are used to further refine the design. Using the proposed workflow, several trends on the performance and manufacturability of the test problem are determined and used to redesign the compliant unit cell. When compared to a preliminary unit cell design, a redesigned unit cell showed decreased energy absorption capacity of only 7.8% while decreasing thermal distortion by 20%. The workflow presented provides a systematic approach to inform a designer about methods to redesign an AM part.

Approximate Functionally Graded Materials for Multi-Material Additive Manufacturing

2018 ◽  
Author(s):  
Yuen-Shan Leung ◽  
Huachao Mao ◽  
Yong Chen
Keyword(s):  
Mechanical Properties ◽  
Additive Manufacturing ◽  
Functionally Graded Materials ◽  
Functionally Graded ◽  
Gradual Transition ◽  
Material Distribution ◽  
Graded Materials ◽  
Base Materials ◽  
Multiple Materials ◽  
Am Processes

Functionally graded materials (FGM) possess superior properties of multiple materials due to the continuous transitions of these materials. Recent progresses in multi-material additive manufacturing (AM) processes enable the creation of arbitrary material composition, which significantly enlarges the manufacturing capability of FGMs. At the same time, the fabrication capability also introduces new challenges for the design of FGMs. A critical issue is to create the continuous material distribution under the fabrication constraints of multi-material AM processes. Using voxels to approximate gradient material distribution could be one plausible way for additive manufacturing. However, current FGM design methods are non-additive-manufacturing-oriented and unpredictable. For instance, some designs require a vast number of materials to achieve continuous transitions; however, the material choices that are available in a multi-material AM machine are rather limited. Other designs control the volume fraction of two materials to achieve gradual transition; however, such transition cannot be functionally guaranteed. To address these issues, we present a design and fabrication framework for FGMs that can efficiently and effectively generate printable and predictable FGM structures. We adopt a data-driven approach to approximate the behavior of FGM using two base materials. A digital material library is constructed with different combinations of the base materials, and their mechanical properties are extracted by Finite Element Analysis (FEA). The mechanical properties are then used for the conversion process between the FGM and the dual material structure such that similar behavior is guaranteed. An error diffusion algorithm is further developed to minimize the approximation error. Simulation results on four test cases show that our approach is robust and accurate, and the framework can successfully design and fabricate such FGM structures.

scholarly journals Investigation of microstructure and hardness of a rib geometry produced by metal forming and wire-arc additive manufacturing

2018 ◽  
Vol 190 ◽  
pp. 02005 ◽  
Author(s):  
Markus Hirtler ◽  
Angelika Jedynak ◽  
Benjamin Sydow ◽  
Alexander Sviridov ◽  
Markus Bambach
Keyword(s):  
Additive Manufacturing ◽  
Metal Forming ◽  
Batch Size ◽  
Unit Costs ◽  
Batch Sizes ◽  
Traditional Manufacturing ◽  
Manufacturing Technologies ◽  
Forming Tools ◽  
Wire Arc Additive Manufacturing ◽  
Am Processes

Within the scope of consumer-oriented production, individuality and cost-effectiveness are two essential aspects, which can barely be met by traditional manufacturing technologies. Conventional metal forming techniques are suitable for large batch sizes. If variants or individualized components have to be formed, the unit costs rise due to the inevitable tooling costs. For such applications, additive manufacturing (AM) processes, which do not require tooling, are more suitable. Due to the low production rates and limited build space of AM machines, the manufacturing costs are highly dependent on part size and batch size. Hence, a combination of both manufacturing technologies i.e. conventional metal forming and additive manufacturing seems expedient for a number of applications. The current study develops a process chain combining forming and additive manufacturing. First, a semi-finished product is formed with forming tools of reduced complexity and then finished by additive manufacturing. This research investigates the addition of features using AlSi12 created by Wire Arc Additive Manufacturing (WAAM) on formed EN-AW 6082 preforms. By forming, the strength of the material was increased, while this effect was partly reduced by the heat input of the WAAM process.

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