Using Rapid Manufacturability Analysis Tools to Enhance Design-for-Manufacturing Training in Engineering Education

2016 ◽  
Author(s):  
Roby Lynn ◽  
Kathryn Jablokow ◽  
Nithin Reddy ◽  
Christopher Saldana ◽  
Tommy Tucker ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Software Package ◽  
High Performance ◽  
Engineering Students ◽  
Design For Manufacturability ◽  
Manufacturing Processes ◽  
Analysis Tool ◽  
Planning Software ◽  
Subtractive Manufacturing ◽  
Performance Computing

Engineering students are often unaware of manufacturing challenges introduced during the design process. Students tend to design parts that are either very difficult or impossible to manufacture because they are unaware of the intricacies and limitations of the manufacturing processes available. Design for manufacturability (DFM) education must be improved to help address this issue. This work discusses a vision for the implementation of a rapid method for facilitating DFM education in terms of subtractive and additive manufacturing processes. The goal is to teach students about how their designs impact the ease and cost of manufacturing, in addition to giving them knowledge and confidence to move fluidly between additive and subtractive manufacturing mindsets. For subtractive manufacturing, this is accomplished through a high-performance-computing accelerated and parallelized trajectory planning software package that enables students to visualize the subtractive manufacturability of the parts they design as rapidly as they get feedback when using additive manufacturing processes. Implementation of the subtractive manufacturability analysis tool in a sophomore-level design class is presented, along with the assessment of the students’ conceptual manufacturing-related understanding.

scholarly journals Функционирование бортовой интеллектуальной системы на основе комплекса управляемого дистанционного эксперимента

2020 ◽  
Author(s):  
Yu.I. Nechaev ◽  
O.N. Petrov
Keyword(s):  
Physical Modeling ◽  
Software Package ◽  
High Performance ◽  
Emergency Situation ◽  
Operational Control ◽  
Intellectual System ◽  
Physical Effects ◽  
Modeling Data ◽  
Urgent Computing ◽  
Performance Computing

Рассматривается повышение эффективности функционирования бортовой интеллектуальной системы (ИС) при использовании комплекса управляемого дистанционного эксперимента (УДЭ). Такая технология интеллектуальной поддержки обеспечивают анализ и прогноз развития экстремальных ситуаций на основе данных физического моделирования и динамической модели современной теории катастроф (СТК), интегрирующей интеллектуальных технологии и высокопроизводительные вычисления. Особенности построения комплекса УДЭ связаны с развитием новых подходов к интеграции знаний сложных систем в эволюционирующей нестационарной среде. Программный комплекс УДЭ представляет собой активную динамическую систему (АДС), обеспечивающую оперативный контроль динамики судна на основе взаимодействия динамической базы знаний бортовой ИС и комплекса УДЭ в режиме экстренных вычислений (Urgent Computing UC) 1 8. Динамика взаимодействия имитируется с помощью системы управления, реализующей физические эффекты в процессе развития аварийной ситуации. Приведены примеры реализации разработанной стратегии при контроле экстремальных ситуаций в бортовых ИС новых поколений.An increase in the functioning efficiency of an onboard intellectual system (IS) when using a complex of controlled remote experiment (CRE) is considered. Such intellectual support technology provides analysis and forecast of the development of extreme situations on the basis of physical modeling data and a dynamic model of modern catastrophe theory (MCT), integrating intellectual technologies and high-performance computing. The features of constructing the CRE complex are associated with the development of new approaches to the integration of knowledge of complex systems in an evolving non-stationary environment. The CRE software package is an active dynamic system (ADS) that provides operational control of the vessels dynamics based on the interaction of the onboard intellectual system dynamic knowledge base and the CRE complex in urgent computing mode (Urgent Computing - UC) 1 - 8. The dynamics of interaction is simulated using a control system that implements physical effects in the process of emergency situation evolution. Examples of the implementation of the developed strategy for the control of extreme situations in the onboard intellectual systems of new generations are given.

scholarly journals Upgrading a high performance computing environment for massive data processing

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Lucas M. Ponce ◽  
Walter dos Santos ◽  
Wagner Meira ◽  
Dorgival Guedes ◽  
Daniele Lezzi ◽  
...  
Keyword(s):  
Big Data ◽  
Data Processing ◽  
High Performance Computing ◽  
High Performance ◽  
Data Access ◽  
Massive Data ◽  
Analysis Tool ◽  
Data Framework ◽  
Performance Computing ◽  
Massive Data Processing

Abstract High-performance computing (HPC) and massive data processing (Big Data) are two trends that are beginning to converge. In that process, aspects of hardware architectures, systems support and programming paradigms are being revisited from both perspectives. This paper presents our experience on this path of convergence with the proposal of a framework that addresses some of the programming issues derived from such integration. Our contribution is the development of an integrated environment that integretes (i) COMPSs, a programming framework for the development and execution of parallel applications for distributed infrastructures; (ii) Lemonade, a data mining and analysis tool; and (iii) HDFS, the most widely used distributed file system for Big Data systems. To validate our framework, we used Lemonade to create COMPSs applications that access data through HDFS, and compared them with equivalent applications built with Spark, a popular Big Data framework. The results show that the HDFS integration benefits COMPSs by simplifying data access and by rearranging data transfer, reducing execution time. The integration with Lemonade facilitates COMPSs’s use and may help its popularization in the Data Science community, by providing efficient algorithm implementations for experts from the data domain that want to develop applications with a higher level abstraction.

scholarly journals The high-throughput gene prediction of more than 1,700 eukaryote genomes using the software package EukMetaSanity

2021 ◽  
Author(s):  
Christopher J Neely ◽  
Sarah K Hu ◽  
Harriet Alexander ◽  
Benjamin J Tully
Keyword(s):  
Software Package ◽  
High Performance ◽  
Gene Locus ◽  
State Of The Art ◽  
Gene Prediction ◽  
Large Data ◽  
Protein Database ◽  
Single Target ◽  
Performance Computing ◽  
Eukaryotic Genomes

Gene prediction and annotation for eukaryotic genomes is challenging with large data demands and complex computational requirements. For most eukaryotes, genomes are recovered from specific target taxa. However, it is now feasible to reconstruct or sequence hundreds of metagenome-assembled genomes (MAGs) or single-amplified genomes directly from the environment. To meet this forthcoming wave of eukaryotic genome generation, we introduce EukMetaSanity, which combines state-of-the-art tools into three pipelines that have been specifically designed for extensive parallelization on high-performance computing infrastructure. EukMetaSanity performs an automated taxonomy search against a protein database of 1,482 species to identify phylogenetically compatible proteins to be used in downstream gene prediction. We present the results for intron, exon, and gene locus prediction for 112 genomes collected from NCBI, including fungi, plants, and animals, along with 1,669 MAGs and demonstrate that EukMetaSanity can provide reliable preliminary gene predictions for a single target taxon or at scale for hundreds of MAGs. EukMetaSanity is freely available at https://github.com/cjneely10/EukMetaSanity.

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

2017 ◽  
Vol 139 (10) ◽  
Author(s):  
Nicholas A. Meisel ◽  
Matthew R. Woods ◽  
Timothy W. Simpson ◽  
Corey J. Dickman
Keyword(s):  
Additive Manufacturing ◽  
Attitude Control ◽  
Manufacturing Processes ◽  
Development Effort ◽  
Design For Additive Manufacturing ◽  
Powder Bed ◽  
Subtractive Manufacturing ◽  
End Use ◽  
Manufacturing Time

Prior research has shown that powder-bed fusion (PBF) additive manufacturing (AM) can be used to make functional, end-use components from powdered metallic alloys, such as Inconel® 718 superalloy. However, these end-use components and products are often based on designs developed for more traditional subtractive manufacturing processes and do not take 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) identify the need for and use of both opportunistic and restrictive design for additive manufacturing (DfAM) concepts and considerations in redesigning the thruster for fabrication with PBF AM and (b) compare the resulting DfAM thruster with a parallel development effort redesigning the original thruster to be manufactured more effectively using subtractive manufacturing processes. The results from this case study show how developing end-use AM components using specific DfAM guidelines can significantly reduce manufacturing time and costs while enabling new and novel design geometries.

Ionic Liquids As Additives to Cutting Fluids to Reduce Machine Tool Friction and Wear

2018 ◽  
Author(s):  
Chris Ferri ◽  
Sydney Lizarazo ◽  
Michael Troise ◽  
Patricia Iglesias
Keyword(s):  
Ionic Liquid ◽  
Ionic Liquids ◽  
High Performance ◽  
Large Scale ◽  
Minimum Quantity Lubrication ◽  
Molecular Structures ◽  
Effect Of Temperature ◽  
Wear Volume ◽  
Manufacturing Processes ◽  
Subtractive Manufacturing

In manufacturing processes, the cost of tooling contributes to a significant portion of operating costs. Several papers have been dedicated to various improvements on tool life, including monitoring the effect of temperature conditions and flood cooling. Flood cooling is not economical, so research has also been done to investigate minimum quantity lubrication and the effects of different additives, such as nanofluids. Another additive, ionic liquids, have become popular in tribological studies because they have unique properties that allow them to form ordered molecular structures, which is ideal in lubrication. Research has proven ionic liquids to be effective in reducing wear and friction coefficients. Currently, utilizing ionic liquids specifically to reduce tool wear has been almost exclusively limited to titanium and steel applications. The goal of this study is to improve tribological performance of the subtractive manufacturing process using ionic liquid add-ins to widely available machine shop coolants and oils. A series of reciprocating ball-on-flat experiments will be conducted using a 1.5mm diameter 250 Chrome Steel G25 ball and 6061-T6 aluminum disk to simulate cutting conditions often seen in manufacturing processes. 6061 Aluminum is an alloy commonly seen in machine shops and large-scale manufacturing scenarios because of its versatile material properties and wide availability. The tests were run at constant sliding distance, velocity and load. The lubricating mixtures were prepared by adding 5 wt % of a phosphonium based ionic liquid, Trihexyltetradecylphosphonium bis(trifluoromethylsulfonyl)amide ([THTDP][NTf2]), to the base fluids Trim Sol™ emulsion fluid and Mobilmet™ 766 high performance neat cutting oil. The addition of the ionic liquid to both base lubricants (oil and coolant) increased the friction coefficient (18.60% and 4.89%, respectively) while the wear volume was reduced (28.75% and 7.84%, respectively). The results for the oil provided evidence that the ionic liquid did have an effect to reduce wear, however, the same conclusion could not be drawn for the coolant.

scholarly journals Numerical prediction of process-dependent properties of high-performance Ti6Al4 in LS-DYNA

2021 ◽  
Author(s):  
Johannes Buhl ◽  
Thomas Klöppel ◽  
Mathias Merten ◽  
Andre Haufe ◽  
Israr Rameez ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Additive Manufacturing ◽  
High Performance ◽  
Evolution Equations ◽  
Material Model ◽  
Structure Evolution ◽  
Internal Variables ◽  
Manufacturing Processes ◽  
Workpiece Material ◽  
Microstructural Parameters

In modern manufacturing processes such as hot forming or additive manufacturing, the workpiece material undergoes very complex thermomechanical load cycles. The local mechanical properties in the component are process-dependent and the result of the different micro-structure evolution mechanisms in the material. Numerical process simulation tools aim to include more and more of these mechanisms in order to improve the accuracy of the simulations. The mechanical strength of high-performance materials such as Ti-6Al-4V depends on microstructural parameters, which are influenced by the temperature and strain histories. This contribution puts forward an implementation of a new generalized internal variables material model *MAT_GENERALIZED_PHASECHANGE in LS-DYNA. The evolution of internal variables such as phase fractions, grain size and dislocation densities can be predicted by evolution equations, and combined with yield stress models taking the contribution of the phases, grain sizes (Hall-Petch effect), and the dislocation density into account to predict the resulting mechanical properties of the processed material. The benefits of the implementation in the commercial software LS-DYNA is the possibility to solve complex coupled problems. For example, the new material law can be used to simulate hybrid manufacturing processes like forging and an additional additive manufacturing process, where changes in microstructure are highly coupled and important for the part properties.

scholarly journals Examination of Aerofoil Blade Fabricated by Additive Manufacturing Process

2019 ◽  
Vol 8 (2S11) ◽  
pp. 889-893
Keyword(s):  
Additive Manufacturing ◽  
Structural Analysis ◽  
Physical Object ◽  
Adaptive Method ◽  
Thin Layers ◽  
Manufacturing Processes ◽  
Extreme Conditions ◽  
Original Material ◽  
Ansys Fluent ◽  
Subtractive Manufacturing

ADDITIVE MANUFACTURING is a method which involves formation of a physical object from a virtual 3D model, usually by numerous successive thin layers of a substance. Traditional design and manufacturing processes have a variety of undesirable limitations in many applications, including expensive tooling, fixtures and assembly of complex parts. However, as in machining, the subtractive manufacturing processes can result in the loss of up to 90% of the original material block. On considering the accuracy, functionality, high end products, material used and typical layer thickness FDM is the most appropriate and adaptive method for manufacturing the 3D printing objects. The Scope of the work is to design the 4515 airfoil to work without fail under extreme conditions. Analyzing the airfoil at a given inlet speed of 138 m / s in ANSYS FLUENT and a structural analysis to determine if it is structurally stable under extreme conditions using ANSYS STRUCTURAL ANALYSIS. In this work ,the analysis is carried out by stream of fluid (air) over NACA 4515 Airfoil and its structural analysis. The values obtained are within the desired limits according to NACA, hence the design is structurally safe.

Fresh in My Mind! Investigating the Effects of the Order of Presenting Opportunistic and Restrictive Design for Additive Manufacturing Content on Creativity

2020 ◽  
Author(s):  
Rohan Prabhu ◽  
Scarlett R. Miller ◽  
Timothy W. Simpson ◽  
Nicholas A. Meisel
Keyword(s):  
Additive Manufacturing ◽  
Self Efficacy ◽  
Engineering Students ◽  
Manufacturing Processes ◽  
Design For Additive Manufacturing ◽  
Undergraduate Engineering ◽  
Traditional Manufacturing ◽  
Order Of Presentation ◽  
Am Processes ◽  
Design For Am

Abstract Additive manufacturing (AM) processes present designers with creative freedoms beyond the capabilities of traditional manufacturing processes. However, to successfully leverage AM, designers must balance their creativity against the limitations inherent in these processes to ensure the feasibility of their designs. This feasible adoption of AM can be achieved if designers learn about and apply opportunistic and restrictive design for AM (DfAM) techniques at appropriate stages of the design process. Researchers have demonstrated the effect of the order of presentation of information on the learning and retrieval of said information; however, there is a need to explore this effect within DfAM education. In this paper, we explore this gap through an experimental study involving 195 undergraduate engineering students. Specifically, we compare two variations in DfAM education: (1) opportunistic DfAM followed by restrictive DfAM, and (2) restrictive DfAM followed by opportunistic DfAM, against only opportunistic DFAM and only restrictive DfAM training. These variations are compared through (1) differences in participants’ DfAM self-efficacy, (2) their self-reported DfAM use, and (3) the creativity of their design outcomes. From the results, we see that only students trained in opportunistic DfAM, with or without restrictive DfAM, present a significant increase in their opportunistic DfAM self-efficacy. However, all students trained in DfAM — opportunistic, restrictive, or both — demonstrated an increase in their restrictive DfAM self-efficacy. Further, we see that teaching restrictive DfAM first followed by opportunistic DfAM results in the generation of ideas with greater creativity — a novel research finding. These results highlight the need for educators to account for the effects of the order of presenting content to students, especially when educating students about DfAM.

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