scholarly journals Use of Miniature Step Gauges to Assess the Performance of 3D Optical Scanners and to Evaluate the Accuracy of a Novel Additive Manufacture Process

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 738 ◽  
Author(s):  
Maria Grazia Guerra ◽  
Leonardo De Chiffre ◽  
Fulvio Lavecchia ◽  
Luigi Maria Galantucci
Keyword(s):  
Additive Manufacturing ◽  
Uncertainty Budget ◽  
Polyphenylene Sulfide ◽  
Additive Manufacture ◽  
Optical Scanners ◽  
Manufacture Process ◽  
Structured Light Scanner ◽  
Line Scanner ◽  
Am Processes ◽  
Good Agreement

In this work, we show how miniature step gauges featuring unidirectional and bidirectional lengths can be used to assess the performance of 3D optical scanners as well as the accuracy of novel Additive Manufacturing (AM) processes. A miniature step gauge made of black polyphenylene sulfide (PPS) was used for the performance verification of three different optical scanners: a structured light scanner (SLS), a laser line scanner (LLS), and a photogrammetry-based scanner (PSSRT), having comparable resolutions and working volumes. Results have shown a good agreement between the involved scanners, with errors below 5 μm and expanded uncertainties below 10 μm. The step gauge geometry due to the bidirectional lengths, highlights that there is a different interaction between the optical properties of the step gauge under measurement and each optical instrument involved and this aspect has to be considered in the uncertainty budget. The same geometry, due to its great significance in the detection of systematic errors, was used, as a novelty, to evaluate the accuracy of Lithography-based Ceramics Manufacturing (LCM), a proprietary additive manufacturing technology used for the fabrication of medical implants. In particular, two miniature step gauges made of Tricalcium Phosphate (TCP) were produced. Measurements conducted with the SLS scanner were characterized by a negligible error and by an uncertainty of about 5 μm. Deviations of the manufactured step gauges with respect to the Computer Aided Designed (CAD) model were comprised between ±50 μm, with positive deviations in the order of 100 μm on vertical sides. Differences in the order of 50 μm between the two step gauges were registered.

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.

Additive Manufacturing of Aluminum Alloys

2019 ◽  
Author(s):  
Sriram Praneeth Isanaka ◽  
Sreekar Karnati ◽  
Frank Liou
Keyword(s):  
Mechanical Properties ◽  
Additive Manufacturing ◽  
Aluminum Alloys ◽  
Raw Material ◽  
Additive Manufacture ◽  
Silicon Alloys ◽  
Aluminum Silicon Alloys ◽  
Grain Structures ◽  
Direct Energy ◽  
Am Processes

Successful additive manufacturing (AM) of aluminum alloys has been demonstrated using a number of processes, which is the focus of this article. Utilization of some aluminum alloys with relatively low reflectivity coupled with process optimization to achieve high retained energy densities enabled the successful deposition of aluminum–silicon alloys that were previously manufactured exclusively using casting processes. The design flexibility of AM processes coupled to the ability to direct energy and material to specific spatial locations has also been used to demonstrate the ability to join dissimilar aluminum alloys, with applicability toward functional grading and repair. Researchers have shown that the additively manufactured alloys exhibit comparable and, in cases, improved mechanical properties to their conventional counterparts with highly refined grain structures. Elaborate investigations into their microstructures to determine the causality of the mechanical properties are also discussed in detail. Understanding the relationship between these desired high retained energy densities and the factors favoring them, including the alloy composition, input energy, and the deposition speed and volume, plays a pivotal role toward successful additive manufacture. With further process parameter optimization and the development of raw material supply chains that can create and tailor alloys based on need, the applicability of these AM processes can be adapted to many more aluminum alloys and can be tailored to serve a wide range of industries.

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.

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 CAD/CAM System for Additive Manufacturing with a Robust and Efficient Topology Optimization Algorithm Based on the Function Representation

2021 ◽  
Vol 11 (16) ◽  
pp. 7409
Author(s):  
Dmitry Popov ◽  
Yulia Kuzminova ◽  
Evgenii Maltsev ◽  
Stanislav Evlashin ◽  
Alexander Safonov ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
3D Modeling ◽  
Mechanical Tests ◽  
Simulation Data ◽  
Function Representation ◽  
Modeling Simulation ◽  
Cad Cam ◽  
Design Ideas ◽  
Good Agreement

Additive manufacturing erases the distance between design ideas and finished parts. However, designers must use several software tools to use these advantages. Moreover, these tools operate with different representations of geometry. This paper describes the architecture of a new CAD/CAM system that uses only the function representation of the geometry (FRep). It provides all widely used design operations and allows an engineer to employ robust and efficient topology optimization algorithms. The developed CAD/CAM system consists of 3D modeling, simulation, topology optimization, and direct manufacturing modules. We successfully printed designed parts and performed mechanical tests of printed parts. The results of tests show good agreement with simulation data. The system makes it possible to create structures with the desired properties in a fast and flexible way. The proposed approach significantly helps in designing additive manufacturing process and saves time for its users.

scholarly journals Modelling, Design and Validation of a Parallel Kinematic Robot for Additive Manufacture Applications

2021 ◽  
pp. 019-029
Author(s):  
Lahoud Marcel ◽  
Melendez Leonardo ◽  
Gil Arturo
Keyword(s):  
Additive Manufacturing ◽  
Open Source Software ◽  
Design Method ◽  
Kinematic Model ◽  
Additive Manufacture ◽  
Parallel Kinematics ◽  
Cartesian Space ◽  
Parallel Kinematic ◽  
Manufacturing Applications ◽  
Design Construction

The additive manufacture is a fabrication process that has taken huge steps in the last decade, even though the first researches and prototypes are around since almost forty years ago. In this article, a design method for a Parallel Kinematics Robot for Additive Manufacturing Applications is proposed. A numerical model is obtained from the kinematics of the robot for which the design, construction and assembly are planned using recycled materials and equipment. The control of the robot is done using open source software, allowing the planning of trajectories in the Cartesian space on a maximum designed cylindrical workspace of 300mm in diameter by 300mm high. At the end of the work the robot was identified, the kinematic model was validated and considerations for future works were given.

Sign in / Sign up

Export Citation Format

Share Document