scholarly journals A Voxel-Based Watermarking Scheme for Additive Manufacturing

2021 ◽  
Vol 11 (19) ◽  
pp. 9177
Author(s):  
Shyh-Kuang Ueng ◽  
Ya-Fang Hsieh ◽  
Yu-Chia Kao
Keyword(s):  
Additive Manufacturing ◽  
Geometric Model ◽  
Region Of Interest ◽  
Virtual Manufacturing ◽  
Test Results ◽  
Volumetric Models ◽  
Complex Models ◽  
G Code ◽  
Watermarking Scheme ◽  
Am Processes

Digital and analog contents, generated in additive manufacturing (AM) processes, may be illegally modified, distributed, and reproduced. In this article, we propose a watermarking scheme to enhance the security of AM. Compared with conventional watermarking methods, our algorithm possesses the following advantages. First, it protects geometric models and printed parts as well as G-code programs. Secondly, it embeds watermarks into both polygonal and volumetric models. Thirdly, our method is capable of creating watermarks inside the interiors and on the surfaces of complex models. Fourth, the watermarks may appear in various forms, including character strings, cavities, embossed bumps, and engraved textures. The proposed watermarking method is composed of the following steps. At first, the input geometric model is converted into a distance field. Then, the watermark is inserted into a region of interest by using self-organizing mapping. Finally, the watermarked model is converted into a G-code program by using a specialized slicer. Several robust methods are also developed to authenticate digital models, G-code programs, and physical parts. These methods perform virtual manufacturing, volume rendering, and image processing to extract watermarks from these contents at first. Then, they employ similarity evaluation and visual comparison to verify the extracted signatures. Some experiments had been conducted to validify the proposed watermarking method. The test results, analysis, discussion, and comparisons are also presented in this article.

Effect of Thermal Deformation on Part Errors in Metal Powder Based Additive Manufacturing Processes

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Ratnadeep Paul ◽  
Sam Anand ◽  
Frank Gerner
Keyword(s):  
Electron Beam ◽  
Additive Manufacturing ◽  
Thermal Deformation ◽  
Thermal Stresses ◽  
Geometric Model ◽  
Virtual Manufacturing ◽  
Deformation Model ◽  
Fe Model ◽  
Slice Thickness ◽  
Part Orientation

In metal additive manufacturing (AM) processes, parts are manufactured in layers by sintering or melting metal or metal alloy powder under the effect of a powerful laser or an electron beam. As the laser/electron beam scans the powder bed, it melts the powder in successive tracks which overlap each other. This overlap, called the hatch overlap, results in a continuous cycle of rapid melting and resolidification of the metal. The melting of the metal from powder to liquid and subsequent solidification causes anisotropic shrinkage in the layers. The thermal strains caused by the thermal gradients existing between the different layers and between the layers and the substrate leads to considerable thermal stresses in the part. As a result, stress gradients develop in the different directions of the part which lead to distortion and warpage in AM parts. The deformations due to shrinkage and thermal stresses have a significant effect on the dimensional inaccuracies of the final part. A three-dimensional thermomechanical finite element (FE) model has been developed in this paper which calculates the thermal deformation in AM parts based on slice thickness, part orientation, scanning speed, and material properties. The FE model has been validated and benchmarked with results already available in literature. The thermal deformation model is then superimposed with a geometric virtual manufacturing model of the AM process to calculate the form and runout errors in AM parts. Finally, the errors in the critical features of the AM parts calculated using the combined thermal deformation and geometric model are correlated with part orientation and slice thickness.

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.

scholarly journals An Optimization Workflow in Design for Additive Manufacturing

2021 ◽  
Vol 11 (6) ◽  
pp. 2572
Author(s):  
Stefano Rosso ◽  
Federico Uriati ◽  
Luca Grigolato ◽  
Roberto Meneghello ◽  
Gianmaria Concheri ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Structural Optimization ◽  
Geometric Model ◽  
Complex Geometries ◽  
Design Phase ◽  
Design For Additive Manufacturing ◽  
Engineering Software ◽  
Embodiment Design ◽  
Pros And Cons

Additive Manufacturing (AM) brought a revolution in parts design and production. It enables the possibility to obtain objects with complex geometries and to exploit structural optimization algorithms. Nevertheless, AM is far from being a mature technology and advances are still needed from different perspectives. Among these, the literature highlights the need of improving the frameworks that describe the design process and taking full advantage of the possibilities offered by AM. This work aims to propose a workflow for AM guiding the designer during the embodiment design phase, from the engineering requirements to the production of the final part. The main aspects are the optimization of the dimensions and the topology of the parts, to take into consideration functional and manufacturing requirements, and to validate the geometric model by computer-aided engineering software. Moreover, a case study dealing with the redesign of a piston rod is presented, in which the proposed workflow is adopted. Results show the effectiveness of the workflow when applied to cases in which structural optimization could bring an advantage in the design of a part and the pros and cons of the choices made during the design phases were highlighted.

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.

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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