Teng C.,3DSIM LLC |
Pal D.,University of Louisville |
Gong H.,Georgia Southern University |
Zeng K.,3DSIM LLC |
And 3 more authors.
Additive Manufacturing | Year: 2017
Thermomechanical modeling of laser material processing in general, and defect modeling in particular, has raised attention in both academia and industry for the last twenty years. Additive manufacturing (aka, 3D printing) is increasingly studied and utilized by researchers and engineers. Defects created during a part building process are costly to identify and could cause premature part failure, and thus numerous studies and research projects have been conducted in order to predict and analyze defects in laser material processing. The available information for defect modeling is scattered widely in the literature and mostly dedicated to very small and specific areas of focus, making it difficult for others to follow, even though the quantity of information is not small. In this work, a review of defect modeling which focuses specifically on the defect types existing in additive manufacturing industry has been carried out, including over 140 referenced articles. © 2017 Elsevier B.V.
Teng C.,3DSIM LLC |
Gong H.,Georgia Southern University |
Szabo A.,General Electric |
Dilip J.J.S.,University of Louisville |
And 5 more authors.
Journal of Manufacturing Science and Engineering, Transactions of the ASME | Year: 2017
Cobalt chromium is widely used to make medical implants and wind turbine, engine and aircraft components because of its high wear and corrosion resistance. The ability to process geometrically complex components is an area of intense interest to enable shifting from traditional manufacturing techniques to additive manufacturing (AM). The major reason for using AM is to ease design modification and optimization since AM machines can directly apply the changes from an updated STL file to print a geometrically complex object. Quality assurance for AM fabricated parts is recognized as a critical limitation of AM processes. In selective laser melting (SLM), layer by layer melting and remelting can lead to porosity defects caused by lack of fusion, balling, and keyhole collapse. Machine process parameter optimization becomes a very important task and is usually accomplished by producing a large amount of experimental coupons with different combinations of process parameters such as laser power, speed, hatch spacing, and powder layer thickness. In order to save the cost and time of these experimental trial and error methods, many researchers have attempted to simulate defect formation in SLM. Many physics-based assumptions must be made to model these processes, and thus, all the models are limited in some aspects. In the present work, we investigated single bead melt pool shapes for SLM of CoCr to tune the physics assumptions and then, applied to the model to predict bulk lack of fusion porosity within the finished parts. The simulation results were compared and validated against experimental results and show a high degree of correlation. © Copyright 2017 by ASME.
News Article | February 15, 2017
The Additive Manufacturing Users Group (AMUG) today announced the recipients of its scholarships. Dr. Haijun Gong, an assistant professor at Georgia Southern University (Statesboro, Ga.), has been awarded the Randy Stevens Scholarship. Claire Belson, a chemical engineering student at the University of Alabama (Tuscaloosa, Ala.), has been awarded the Guy E. Bourdeau Scholarship. With these recognitions, Ms. Belson and Dr. Gong will attend and participate in the AMUG Conference, which will be held in Chicago, Illinois, from March 19-23, 2017. Steve Deak, AMUG president, stated, “We are very excited to have Dr. Gong and Ms. Belson attend the 2017 conference as scholarship recipients, selected from a strong field of candidates. These individuals are extremely dynamic in their pursuit of additive manufacturing applications and represent the future of our industry. AMUG members will certainly benefit from learning about their vision for AM, while both scholarship recipients will gain industry-specific application perspectives from conference participants.” The AMUG Scholarship Committee selected Dr. Haijun Gong for his extensive experience, current research, and transfer of that knowledge to the students that he teaches. “Dr. Gong is well-versed in the area of additive manufacturing and has the skills to apply that experience to research and education at the intersection of unique materials and AM [additive manufacturing] processes,” said Dr. Daniel Cox, professor and founding chair of the Department of Manufacturing Engineering at Georgia Southern University. Dr. Cox added, “Dr. Gong is also a great teacher and has shown excellent mentoring and teaching skills. He has what it takes to succeed in the three areas of faculty scholarship: research, teaching and service.” He continued, “Dr. Gong is well-prepared to lead a successful research program in AM as he knows how to conceive and prepare research proposals, and he has successfully turned his research into numerous publications.” Dr. Gong’s attention focuses on additive manufacturing with metallic materials. He stated, “In my opinion, AM is not only a manufacturing method for complex metal parts, but also a metallurgy technique of exploring new alloys.” Currently he is conducting research, in partnership with 3DSIM LLC, on the simulation, optimization, and physical phenomena of laser melting processes. Dr. Gong also contributes to standards development through ASTM’s F42 committee. Additionally, he has completed an NSF proposal to acquire a metal additive manufacturing machine to further research and education at the university. The AMUG Scholarship Committee selected Claire Belson for her passion, professionalism, skills and willingness to share her knowledge. In her application, Ms. Belson said, “Attending AMUG 2017 would be an awesome opportunity for me because I would be able to pass on all the knowledge that I would gain to my university, my future employers and to the next generation of additive manufacturing engineers.” Ms. Belson is pursuing a dual degree, both a B.S. and M.S. in chemical engineering, and has participated as an undergraduate researcher, a sub-team leader of the university’s EcoCAR team, and a student employee in the College of Engineering’s innovation area known as the Cube. Dr. Yonghyun (John) Kim, assistant professor in the Department of Chemical and Biological Engineering, stated, “Claire has also worked as an engineering co-op student at Emerson, where she was entrusted to spearhead a $50,000+ project to develop new additive manufacturing processes in foundries.” As an Emerson co-op, Ms. Belson attended the 2016 AMUG Conference. “The AMUG Conference helped me to evaluate companies and equipment in order to make wise recommendations to senior management regarding potential purchases and what would be best for their needs,” she said. Rebecca Rutishauser, manager of manufacturing innovation and technology for Emerson Automation Solutions, said, “This was by far the most complex and comprehensive co-op project from 2016, and Claire completed it with a well thought out final recommendation and still had time to help with several other projects.” Ms. Rutishauser continued, “I could not be more proud of the work Claire completed. Everyone who worked with her or attended her presentations has told me how impressed they were with her, and as a result, Emerson is pleased to have Claire come back for an internship during the summer of 2017. This is the first time the Fisher division has ever had an intern as we normally only run a co-op program, but we had to make an exception to have Claire come back since her work was exemplary.” The Guy E. Bourdeau Scholarship, founded by Guy's wife, Renee Bourdeau, is awarded annually to one college student. The Randy Stevens Scholarship, founded by Randy's employer, In'Tech Industries, is awarded annually to one educator that emphasizes or focuses on additive manufacturing. ABOUT ADDITIVE MANUFACTURING USERS GROUP (AMUG) AMUG is an organization that educates and advances the uses and applications of additive manufacturing technologies. AMUG members include those with any commercial additive manufacturing/3D printing technologies from companies such as Stratasys, 3D Systems, Concept Laser, SLM Solutions, EOS, ExOne, Renishaw, HP, EnvisionTEC and Carbon. AMUG meets annually to provide education and training through technical presentations on processes and new technologies. This information addresses operation of additive manufacturing equipment and the applications that use the parts they make. Online at http://www.am-ug.com.
Gong H.,University of Louisville |
Rafi K.,UL International Singapore Pte Ltd |
Gu H.,North Carolina State University |
Janaki Ram G.D.,Indian Institute of Technology Madras |
And 2 more authors.
Materials and Design | Year: 2015
This study evaluates the mechanical properties of Ti-6Al-4 V samples produced by selective laser melting (SLM) and electron beam melting (EBM). Different combinations of process parameters with varying energy density levels were utilized to produce samples, which were analyzed for defects and subjected to hardness, tensile, and fatigue tests. In SLM samples, small pores in amounts up to 1 vol.% resulting from an increase in energy density beyond the optimum level were found to have no major detrimental effect on the mechanical properties. However, further increase in the energy density increased the amount of porosity to 5 vol.%, leading to considerable drop in tensile properties. Samples produced using lower-than-optimum energy density exhibited unmelted powder defects, which, even at 1 vol.% level, strongly affected both tensile and fatigue properties. In EBM, insufficient energy input was found to result in large, macroscopic voids, causing serious degradation in all mechanical properties. These findings are helpful in process optimization and standardization of SLM and EBM processes. © 2015 Elsevier Ltd.
Pal D.,University of Louisville |
Patil N.,3DSIM LLC |
Zeng K.,3DSIM LLC |
Zeng K.,University of Louisville |
And 2 more authors.
Metallurgical and Materials Transactions A: Physical Metallurgy and Materials Science | Year: 2015
In this study, an overview of the computational tools developed in the area of metal-based additively manufactured (AM) to simulate the performance metrics along with their experimental validations will be presented. The performance metrics of the AM fabricated parts such as the inter- and intra-layer strengths could be characterized in terms of the melt pool dimensions, solidification times, cooling rates, granular microstructure, and phase morphologies along with defect distributions which are a function of the energy source, scan pattern(s), and the material(s). The four major areas of AM simulation included in this study are thermo-mechanical constitutive relationships during fabrication and in-service, the use of Euler angles for gaging static and dynamic strengths, the use of algorithms involving intelligent use of matrix algebra and homogenization extracting the spatiotemporal nature of these processes, a fast GPU architecture, and specific challenges targeted toward attaining a faster than real-time simulation efficiency and accuracy. © 2015, The Minerals, Metals & Materials Society and ASM International.
Teng C.,3DSIM LLC |
Ashby K.,3DSIM LLC |
Phan N.,U.S. Navy |
Pal D.,3DSIM LLC |
Stucker B.,3DSIM LLC
Measurement Science and Technology | Year: 2016
The objective of this study was to provide guidance on material specifications for powders used in laser powder bed fusion based additive manufacturing (AM) processes. The methodology was to investigate how different material property assumptions in a simulation affect meltpool prediction and by corrolary how different material properties affect meltpool formation in AM processes. The sensitvity of meltpool variations to each material property can be used as a guide to help drive future research and to help prioritize material specifications in requirements documents. By identifying which material properties have the greatest affect on outcomes, metrology can be tailored to focus on those properties which matter most; thus reducing costs by eliminating unnecessary testing and property charaterizations. Futhermore, this sensitivity study provides insight into which properties require more accurate measurements, thus motivating development of new metrology methods to measure those properties accurately. © 2016 IOP Publishing Ltd.
Agency: Department of Defense | Branch: Navy | Program: SBIR | Phase: Phase I | Award Amount: 79.77K | Year: 2015
Additive Manufacturing (AM) is of increasing interest for production of Naval aircraft components. The geometric complexity, mechanical properties, and cost competitiveness for small lot production make AM techniques particularly suited for Ti-6Al-4V aircraft applications. However, microstructural and material property variability issues inherent to AM make rapid qualification of metal AM parts difficult. 3DSIM has significant experience with thermal modeling of metal laser sintering of Ti64, including prediction of Ti64 phases and phase transitions. These models have been validated experimentally over several years of research at the University of Louisville. To fully predict microstructural evolution in Ti64, accurate prediction of the initial crystal microstructure and subsequent solid state phase transitions is required. However, accurate prediction of initial microstructure is difficult to validate using Ti64 due to solid state phase transformations. To address Phase I objectives, 3DSIM proposes to: develop algorithms which predict microstructural characteristics, including phase evolution, grain size and grain orientation, from metal AM thermal histories; conduct validation of the predicted microstructural characteristics by comparison with as-built microstructures for metal laser sintered CoCrMoC parts; and conduct validation of the predicted microstructural characteristics by comparison with as-built microstructures for LENS-deposited Ti64 parts.
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase I | Award Amount: 149.73K | Year: 2015
ABSTRACT:Additive Manufacturing (AM) technologies are bringing significant new capabilities to manufacturing. However, a number of technical challenges remain before these capabilities can be fully exploited. The design, modeling and data management tools developed for subtractive, formative and mold-based manufacturing are not well suited for additive processes that allow pointwise and layerwise specification and control of 3D part fabrication. Specific challenges remain in specifying and designing material variations within a part, in utilizing process model information during the design process, in transmitting design decisions to various commercial AM machines, and in capturing process monitor data for part qualification. Currently there is no single integrated software solution to capture and manage large volumes of complex AM data. 3DSIM will leverage our knowledge, experience, and understanding to synthesize a comprehensive AM data management tool to capture, manage, and manipulate AM data sets. Specifically, 3DSIM proposes to develop a AM data management tool that would bridge the gap between existing CAD tools and proprietary AM planning and processing software, incorporate process modeling and process monitoring data, and further enable the potential of AM technologies.BENEFIT:An effective AM data management strategy will encompass all types and ranges of data that may be required for current and future AM processes. Such a strategy will fundamentally prescribe part shape, and will also provide a format for specifying location-specific properties of the part. The AM data management tool will support the expanding qualification, certification, simulation and design capabilities of AM users.
Agency: Department of Commerce | Branch: National Institute of Standards and Technology | Program: SBIR | Phase: Phase II | Award Amount: 300.00K | Year: 2016
Additive manufacturing lacks efficient, composable physics-based computational frameworks to predict quality and performance for arbitrary geometry, orientation, location and process parameter combinations. A new set of composable computational tools capable of accurately predicting the geometrical accuracy, residual stress and microstructure of the parts made using metal based AM has been developed. The tool(s) demonstrate scaling and composability of models to support geometry-independent reusability while providing a range of parameter values (e.g. user-defined build orientation, laser power, scan speed, hatch pattern, recoat time, material properties, powder layer thickness, choice of mesh motifs, and more) supporting reliability and accuracy.
3Dsim Llc | Date: 2016-07-06
Computer application software for additive manufacturing processes, namely, software for predicting solidified microstructure and resultant properties by modeling the underlying physical behaviors that are closely linked to process parameters.