Toward Metamodels for Composable and Reusable Additive Manufacturing Process Models

2014 ◽  
Author(s):  
Paul Witherell ◽  
Shaw C. Feng ◽  
Timothy W. Simpson ◽  
David B. Saint John ◽  
Pan Michaleris ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Modeling And Simulation ◽  
Model Development ◽  
Process Models ◽  
Loop Control ◽  
Powder Bed ◽  
Potential Benefits ◽  
Future Work ◽  
Application Specific ◽  
Am Processes

Though the advanced manufacturing capabilities offered by additive manufacturing (AM) have been known for several decades, industry adoption of AM technologies has been relatively slow. Recent advances in modeling and simulation of AM processes and materials are providing new insights to help overcome some of the barriers that have hindered adoption. However, these models and simulations are often application specific, and few are developed in an easily reusable manner. Variations are compounded because many models are developed as independent or proprietary efforts, and input and output definitions have not been standardized. To further realize the potential benefits of modeling and simulation advancements, including predictive modeling and closed-loop control, more coordinated efforts must be undertaken. In this paper, we advocate a more harmonized approach to model development, through classification and metamodeling that will support model composability, reusability, and integration. We review several types of AM models and use direct metal powder bed fusion characteristics 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.

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.

The Environmental Impacts of Metal Powder Bed Additive Manufacturing

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Jiankan Liao ◽  
Daniel R. Cooper
Keyword(s):  
Additive Manufacturing ◽  
Environmental Impacts ◽  
Metal Powder ◽  
Future Research ◽  
Research Directions ◽  
Powder Bed ◽  
Direct Energy ◽  
Potential Benefits ◽  
Future Research Directions ◽  
Am Processes

Abstract Additive manufacturing (AM) is widely recognized as a critical pillar of advanced manufacturing and is moving from the design shop to the factory floor. As AM processes become more popular, it is paramount that engineers and policymakers understand and then reduce their environmental impacts. This article structures the current work on the environmental impacts of metal powder bed processes: selective laser melting (SLM), direct metal laser sintering (DMLS), electron beam melting (EBM), and binder jetting (BJ). We review the potential benefits and pitfalls of AM in each phase of a part's lifecycle and in different application domains (e.g., remanufacturing and hybrid manufacturing). We highlight critical uncertainties and future research directions throughout. The environmental impacts of AM are sensitive to the specific production and use-phase context; however, several broad lessons can be extracted from the literature. Unlike in conventional manufacturing, powder bed production impacts are dominated by the generation of the direct energy (electricity) required to operate the AM machines. Combined with a more energy-intensive feedstock (metal powder), this means that powder bed production impacts are higher than in conventional manufacturing unless production volumes are very small (saving tool production impacts), and/or there are significant material savings through part light weighting or improved buy-to-fly ratios.

The Environmental Impacts of Metal Powder Bed Additive Manufacturing

2020 ◽  
Author(s):  
Jiankan Liao ◽  
Daniel R. Cooper
Keyword(s):  
Additive Manufacturing ◽  
Environmental Impacts ◽  
Metal Powder ◽  
Future Research ◽  
Research Directions ◽  
Powder Bed ◽  
Direct Energy ◽  
Potential Benefits ◽  
Future Research Directions ◽  
Am Processes

Abstract Additive manufacturing (AM) is widely recognized as a critical pillar of advanced manufacturing and is moving from the design shop to the factory floor. As AM processes become more popular, it is paramount that engineers and policymakers understand and then reduce their environmental impacts. This article structures the current work on the environmental impacts of metal powder bed processes: selective laser melting (SLM), direct metal laser sintering (DMLS), electron beam melting (EBM), and binder jetting (BJ). We review the potential benefits and pitfalls of AM in each phase of a part’s lifecycle and in different application domains (e.g., remanufacturing, hybrid manufacturing etc.). We highlight critical uncertainties and future research directions throughout. The environmental impacts of AM are sensitive to the specific production and use-phase context; however, several broad lessons can be extracted from the literature. Unlike in conventional manufacturing, powder bed production impacts are dominated by the generation of the direct energy (electricity) required to operate the AM machines. Combined with a more energy-intensive feedstock (metal powder) this means that powder bed production impacts are higher than in conventional manufacturing unless production volumes are very small (saving tool production impacts) and/or there are significant material savings through part light weighting or improved buy-to-fly ratios.

scholarly journals An Overview of Additive Manufacturing Technologies—A Review to Technical Synthesis in Numerical Study of Selective Laser Melting

Materials ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 3895 ◽  
Author(s):  
Abbas Razavykia ◽  
Eugenio Brusa ◽  
Cristiana Delprete ◽  
Reza Yavari
Keyword(s):  
Numerical Simulation ◽  
Additive Manufacturing ◽  
Selective Laser Melting ◽  
Powder Bed Fusion ◽  
Laser Melting ◽  
Powder Bed ◽  
Part Quality ◽  
Melt Pool ◽  
Wide Range ◽  
Am Processes

Additive Manufacturing (AM) processes enable their deployment in broad applications from aerospace to art, design, and architecture. Part quality and performance are the main concerns during AM processes execution that the achievement of adequate characteristics can be guaranteed, considering a wide range of influencing factors, such as process parameters, material, environment, measurement, and operators training. Investigating the effects of not only the influential AM processes variables but also their interactions and coupled impacts are essential to process optimization which requires huge efforts to be made. Therefore, numerical simulation can be an effective tool that facilities the evaluation of the AM processes principles. Selective Laser Melting (SLM) is a widespread Powder Bed Fusion (PBF) AM process that due to its superior advantages, such as capability to print complex and highly customized components, which leads to an increasing attention paid by industries and academia. Temperature distribution and melt pool dynamics have paramount importance to be well simulated and correlated by part quality in terms of surface finish, induced residual stress and microstructure evolution during SLM. Summarizing numerical simulations of SLM in this survey is pointed out as one important research perspective as well as exploring the contribution of adopted approaches and practices. This review survey has been organized to give an overview of AM processes such as extrusion, photopolymerization, material jetting, laminated object manufacturing, and powder bed fusion. And in particular is targeted to discuss the conducted numerical simulation of SLM to illustrate a uniform picture of existing nonproprietary approaches to predict the heat transfer, melt pool behavior, microstructure and residual stresses analysis.

Complex Solutions for Complex Problems? Exploring the Role of Design Task Choice on Learning, Design for Additive Manufacturing Use, and Creativity

2019 ◽  
Vol 142 (3) ◽  
Author(s):  
Rohan Prabhu ◽  
Scarlett R. Miller ◽  
Timothy W. Simpson ◽  
Nicholas A. Meisel
Keyword(s):  
Additive Manufacturing ◽  
Self Efficacy ◽  
Engineering Students ◽  
Educational Interventions ◽  
Problem Statement ◽  
Design Task ◽  
Complex Solutions ◽  
Future Work ◽  
Am Processes

Abstract The integration of additive manufacturing (AM) processes in many industries has led to the need for AM education and training, particularly on design for AM (DfAM). To meet this growing need, several academic institutions have implemented educational interventions, especially project- and problem-based, for AM education; however, limited research has explored how the choice of the problem statement influences the design outcomes of a task-based AM/DfAM intervention. This research explores this gap in the literature through an experimental study with 175 undergraduate engineering students. Specifically, the study compared the effects of restrictive and dual (restrictive and opportunistic) DfAM education, when introduced through design tasks that differed in the explicit use of design objectives and functional and manufacturing constraints in defining them. The effects of the intervention were measured through (1) changes in participant DfAM self-efficacy, (2) participants' self-reported emphasis on DfAM, and (3) the creativity of participants' design outcomes. The results show that the choice of the design task has a significant effect on the participants' self-efficacy with, and their self-reported emphasis on, certain DfAM concepts. The results also show that the design task containing explicit constraints and objectives results in participants generating ideas with greater uniqueness compared with the design task with fewer explicit constraints and objectives. These findings highlight the importance of the chosen problem statement on the outcomes of a DfAM educational intervention, and future work is also discussed.

Comparing the Sustainability Performance of Metal-Based Additive Manufacturing Processes

2017 ◽  
Author(s):  
Rothanak Chan ◽  
Sriram Manoharan ◽  
Karl R. Haapala
Keyword(s):  
Additive Manufacturing ◽  
Evaluation Method ◽  
Bottom Line ◽  
Powder Bed ◽  
Sustainability Performance ◽  
Quantitative Metrics ◽  
Direct Energy ◽  
Approach Method ◽  
Am Processes ◽  
Wire Feed

While there have been many advancements in additive manufacturing (AM) technologies for metal products, there has not been a great deal of attention paid toward developing an understanding of the relative sustainability performance of various AM processes for production of aerospace components, such as wire feed and powder bed fusion processes. This research presents a method to calculate and compare quantitative metrics for evaluating metal AM process on a basis of sustainability performance. The process-level evaluation method encompasses a triple bottom line analysis for low volume part production. A representative aerospace titanium alloy (Ti-6Al-4V) component is considered for the study and the production of the part is modeled using direct energy deposition (DED) as the representative wire feed AM process and selective laser melting (SLM) as the representative powder bed AM process. The results indicate that DED has a superior sustainability performance to SLM, mainly due to the relatively slower deposition rate and higher cost of material for SLM than DED. This research provides decision makers an approach method and a demonstrated case study in comparing DED and SLM AM processes. This understanding reveals advantages between the two options and offers avenues of future investigation for these technologies for further development and larger scale use.

scholarly journals A functional modeling approach for quality assurance in metal additive manufacturing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gijeong Seo ◽  
Md. RU Ahsan ◽  
Yousub Lee ◽  
Jong-Ho Shin ◽  
Hyungjun Park ◽  
...  
Keyword(s):  
Quality Assurance ◽  
Additive Manufacturing ◽  
Functional Design ◽  
Holistic View ◽  
Design Models ◽  
Content Type ◽  
Powder Bed ◽  
Critical Issues ◽  
New Research ◽  
Am Processes

Purpose Due to the complexity of and variations in additive manufacturing (AM) processes, there is a level of uncertainty that creates critical issues in quality assurance (QA), which must be addressed by time-consuming and cost-intensive tasks. This deteriorates the process repeatability, reliability and part reproducibility. So far, many AM efforts have been performed in an isolated and scattered way over several decades. In this paper, a systematically integrated holistic view is proposed to achieve QA for AM. Design/methodology/approach A systematically integrated view is presented to ensure the predefined part properties before/during/after the AM process. It consists of four stages, namely, QA plan, prospective validation, concurrent validation and retrospective validation. As a foundation for QA planning, a functional workflow and the required information flows are proposed by using functional design models: Icam DEFinition for Function Modeling. Findings The functional design model of the QA plan provides the systematically integrated view that can be the basis for inspection of AM processes for the repeatability and qualification of AM parts for reproducibility. Research limitations/implications A powder bed fusion process was used to validate the feasibility of this QA plan. Feasibility was demonstrated under many assumptions; real validation is not included in this study. Social implications This study provides an innovative and transformative methodology that can lead to greater productivity and improved quality of AM parts across industries. Furthermore, the QA guidelines and functional design models provide the foundation for the development of a QA architecture and management system. Originality/value This systematically integrated view and the corresponding QA plan can pose fundamental questions to the AM community and initiate new research efforts in the in-situ digital inspection of AM processes and parts.

Powder-Scale Meshfree Simulations of Powder Bed Fusion Based Additive Manufacturing Processes

2019 ◽  
Author(s):  
Zongyue Fan ◽  
Hao Wang ◽  
Bo Li
Keyword(s):  
Additive Manufacturing ◽  
Optimal Transportation ◽  
The Novel ◽  
Powder Bed Fusion ◽  
Computational Framework ◽  
Powder Bed ◽  
Materials Behaviors ◽  
Melt Pool ◽  
Powder Particles ◽  
Am Processes

Abstract We present a powder-scale meshfree direct numerical simulation (DNS) capability for the powder bed fusion (PBF) based additive manufacturing (AM) processes using the novel Hot Optimal Transportation Meshfree (HOTM) method. The HOTM method is an incremental Lagrangian meshfree computational framework for materials behaviors under extreme thermomechanical loading conditions, which combines the Optimal Transportation Meshfree (OTM) method and the variational thermomechanical constitutive updates. The realistic multi-layer powder bed geometry is modeled explicitly in the HOTM simulations based on experimental data. A phase-aware constitutive model is developed to predict the phase change and multiphase mixing during the PBF AM processes automatically. The governing equations including the linear momentum and energy conservation equations are solved for the multiphase flow simultaneously to predict the deformation, temperature and local state of the powder particles. The powder-scale DNS is employed to study the influence of various laser powers on the melt pool thermodynamics.

Functional Performance Tailoring of Additively Manufactured Components via Topology Optimization

2017 ◽  
Author(s):  
John C. Steuben ◽  
John G. Michopoulos ◽  
Athanasios P. Iliopoulos ◽  
Andrew J. Birnbaum
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
High Performance ◽  
Functional Performance ◽  
Underwater Vehicle ◽  
Length Scale ◽  
Hand Tool ◽  
Component Shape ◽  
Future Work ◽  
Am Processes

The freedom of design that is afforded by Additive Manufacturing (AM) processes opens exciting possibilities for the production of lightweight, high performance components and structures. Consequently, in recent years the development of software tools to enable engineering design methods that exploit the unique features of AM has become a subject of increased research interest. In this paper we explore the use of Topology Optimization (TO) algorithms to tailor component shape in order to achieve the intended functionality of additively manufactured components at the macro length scale. We present two case studies: the first concerns the hierarchical nesting of functions in a hand tool, while the second covers the development of a metamaterial component substructure for an Uninhabited Underwater Vehicle (UUV) hull. We offer conclusions regarding the usefulness of TO techniques for the design of AM components, and a summary of future work, which we feel is necessary to improve such methodologies.

Fundamental Requirements for Data Representations in Laser-Based Powder Bed Fusion

2015 ◽  
Author(s):  
Shaw C. Feng ◽  
Paul W. Witherell ◽  
Gaurav Ameta ◽  
Duck Bong Kim
Keyword(s):  
Additive Manufacturing ◽  
Heterogeneous Systems ◽  
Powder Bed Fusion ◽  
Process Data ◽  
Data Interoperability ◽  
Powder Bed ◽  
Related Data ◽  
Data Representations ◽  
Am Processes

Additive Manufacturing (AM) processes intertwine aspects of many different engineering-related disciplines, such as material metrology, design, in-situ and off-line measurements, and controls. Due to the increasing complexity of AM systems and processes, data cannot be shared among heterogeneous systems because of a lack of a common vocabulary and data interoperability methods. This paper aims to address insufficiencies in laser-based Powder Bed Fusion (PBF), a specific AM process, data representations to improve data management and reuse in PBF. Our approach is to formally decompose the processes and align PBF process-specifics with information elements as fundamental requirements for representing process-related data. The paper defines the organization and flow of process information. After modeling selected PBF processes and sub-processes as activities, we discuss requirements for the development of more advanced process data models that provide common terminology and process knowledge for managing data from various stages in AM.

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