scholarly journals Multifractal Analysis of Image Profiles for the Characterization and Detection of Defects in Additive Manufacturing

2018 ◽  
Vol 140 (3) ◽  
Author(s):  
Bing Yao ◽  
Farhad Imani ◽  
Aniket S. Sakpal ◽  
E. W. Reutzel ◽  
Hui Yang
Keyword(s):  
Additive Manufacturing ◽  
Powder Bed ◽  
Sensing Systems ◽  
Sensing Technology ◽  
Subtractive Manufacturing ◽  
Fractal Patterns ◽  
And Control ◽  
Monitoring Quality ◽  
Am Processes ◽  
Detection Of Defects

Metal-based powder-bed-fusion additive manufacturing (PBF-AM) is gaining increasing attention in modern industries, and is a promising direct manufacturing technology. Additive manufacturing (AM) does not require the tooling cost of conventional subtractive manufacturing processes, and is flexible to produce parts with complex geometries. Quality and repeatability of AM parts remain a challenging issue that persistently hampers wide applications of AM technology. Rapid advancements in sensing technology, especially imaging sensing systems, provide an opportunity to overcome such challenges. However, little has been done to fully utilize the image profiles acquired in the AM process and study the fractal patterns for the purpose of process monitoring, quality assessment, and control. This paper presents a new multifractal methodology for the characterization and detection of defects in PBF-AM parts. Both simulation and real-world case studies show that the proposed approach effectively detects and characterizes various defect patterns in AM images and has strong potential for quality control of AM processes.

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 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.

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.

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.

Redesigning a Reaction Control Thruster for Metal-Based Additive Manufacturing: A Case Study in Design for Additive Manufacturing

2016 ◽  
Author(s):  
Matthew R. Woods ◽  
Nicholas A. Meisel ◽  
Timothy W. Simpson ◽  
Corey J. Dickman
Keyword(s):  
Additive Manufacturing ◽  
Attitude Control ◽  
Development Effort ◽  
Design For Additive Manufacturing ◽  
Powder Bed ◽  
Subtractive Manufacturing ◽  
End Use ◽  
Manufacturing Time ◽  
Novel Design

Prior research has shown that powder bed fusion additive manufacturing (AM) can be used to make functional, end-use components from powdered metallic alloys, such as Inconel® 718 super alloy. However, these end-use products are often based on designs developed for more traditional subtractive manufacturing processes without taking advantage of the unique design freedoms afforded by AM. In this paper, we present a case study involving the redesign of NASA’s existing “Pencil” thruster used for spacecraft attitude control. The initial “Pencil” thruster was designed for, and manufactured using, traditional subtractive methods. The main focus in this paper is to (a) review the Design for Additive Manufacturing (DfAM) concepts and considerations used in redesigning the thruster and (b) compare it with a parallel development effort redesigning the original thruster to be manufactured more effectively using subtractive processes. The results from this study show how developing end-use AM components using DfAM guidelines can significantly reduce manufacturing time and costs while introducing new and novel design geometries.

scholarly journals A Preliminary Design of a Hybrid Machine for Additive and Subtractive Manufacturing

2020 ◽  
Vol 5 (1) ◽  
pp. 48
Author(s):  
Nanang Ali Sutisna
Keyword(s):  
Additive Manufacturing ◽  
Structural Design ◽  
Control Design ◽  
Preliminary Design ◽  
Forming Process ◽  
Initial Shape ◽  
Subtractive Manufacturing ◽  
Hybrid Machine ◽  
And Control ◽  
Subtractive Machining

<p>Additive manufacturing (AM) or commonly called 3D printing (3DP) and rapid prototyping (RP) is a  technique of blending materials by either fusion, binding, or solidifying materials. Despite many advantages of AM, there is a drawback  of AM such as the surface quality may not be as good as subtractive machining  (SM) process, therefore it will be better to have the initial shape forming process with AM and then finishing the required surface with SM process within a single setup. This paper presents the preliminary design of hybrid AM-SM machine to process a resin based material. The design includes structural design and control design of the machine using the material and firmware widely available in the market.</p><p align="center"><strong> </strong></p><strong>Keyword: </strong>Additive, Subtractive,  Manufacturing,  Hybrid  Machine

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.

Application of Machine Learning Techniques in Additive Manufacturing: A Review

2022 ◽  
pp. 1-24
Author(s):  
Amithkumar Gajakosh ◽  
R. Suresh Kumar ◽  
V. Mohanavel ◽  
Ragavanantham Shanmugam ◽  
Monsuru Ramoni
Keyword(s):  
Machine Learning ◽  
Additive Manufacturing ◽  
Manufacturing Process ◽  
Control Process ◽  
Machine Learning Techniques ◽  
Review Of The Literature ◽  
Learning Techniques ◽  
Manufactured Products ◽  
And Control ◽  
Monitoring Quality

This chapter provides an analysis of the state-of-the-art in ML applications for optimizing the additive manufacturing process. This chapter primarily presents a review of the literature on the use of machine learning (ML) in optimizing the additive manufacturing process at various stages. The chapter identifies ML-researched areas in which ML can be used to optimize processes such as process design, process plan and control, process monitoring, quality enhancement of additively manufactured products, and so on. In addition, general literature on the intersection of additive manufacturing and machine learning will be presented. The benefits and drawbacks of ML for additive manufacturing will be discussed, as well as existing obstacles that are currently limiting applications.

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.

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