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    Computational Fluid Dynamics Modeling and Online Monitoring of Aerosol Jet Printing Process

    Source: Journal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 002::page 21015
    Author:
    Salary, Roozbeh (Ross)
    ,
    Lombardi, Jack P.
    ,
    Samie Tootooni, M.
    ,
    Donovan, Ryan
    ,
    Rao, Prahalad K.
    ,
    Borgesen, Peter
    ,
    Poliks, Mark D.
    DOI: 10.1115/1.4034591
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The objectives of this paper in the context of aerosol jet printing (AJP)—an additive manufacturing (AM) process—are to: (1) realize in situ online monitoring of print quality in terms of line/electronic trace morphology; and (2) explain the causal aerodynamic interactions that govern line morphology based on a two-dimensional computational fluid dynamics (2D-CFD) model. To realize these objectives, an Optomec AJ-300 aerosol jet printer was instrumented with a charge coupled device (CCD) camera mounted coaxial to the nozzle (perpendicular to the platen). Experiments were conducted by varying two process parameters, namely, sheath gas flow rate (ShGFR) and carrier gas flow rate (CGFR). The morphology of the deposited lines was captured from the online CCD images. Subsequently, using a novel digital image processing method proposed in this study, six line morphology attributes were quantified. The quantified line morphology attributes are: (1) line width, (2) line density, (3) line edge quality/smoothness, (4) overspray (OS), (5) line discontinuity, and (6) internal connectivity. The experimentally observed line morphology trends as a function of ShGFR and CGFR were verified with computational fluid dynamics (CFD) simulations. The image-based line morphology quantifiers proposed in this work can be used for online detection of incipient process drifts, while the CFD model is valuable to ascertain the appropriate corrective action to bring the process back in control in case of a drift.
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      Computational Fluid Dynamics Modeling and Online Monitoring of Aerosol Jet Printing Process

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4234682
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    contributor authorSalary, Roozbeh (Ross)
    contributor authorLombardi, Jack P.
    contributor authorSamie Tootooni, M.
    contributor authorDonovan, Ryan
    contributor authorRao, Prahalad K.
    contributor authorBorgesen, Peter
    contributor authorPoliks, Mark D.
    date accessioned2017-11-25T07:17:37Z
    date available2017-11-25T07:17:37Z
    date copyright2016/3/10
    date issued2017
    identifier issn1087-1357
    identifier othermanu_139_02_021015.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4234682
    description abstractThe objectives of this paper in the context of aerosol jet printing (AJP)—an additive manufacturing (AM) process—are to: (1) realize in situ online monitoring of print quality in terms of line/electronic trace morphology; and (2) explain the causal aerodynamic interactions that govern line morphology based on a two-dimensional computational fluid dynamics (2D-CFD) model. To realize these objectives, an Optomec AJ-300 aerosol jet printer was instrumented with a charge coupled device (CCD) camera mounted coaxial to the nozzle (perpendicular to the platen). Experiments were conducted by varying two process parameters, namely, sheath gas flow rate (ShGFR) and carrier gas flow rate (CGFR). The morphology of the deposited lines was captured from the online CCD images. Subsequently, using a novel digital image processing method proposed in this study, six line morphology attributes were quantified. The quantified line morphology attributes are: (1) line width, (2) line density, (3) line edge quality/smoothness, (4) overspray (OS), (5) line discontinuity, and (6) internal connectivity. The experimentally observed line morphology trends as a function of ShGFR and CGFR were verified with computational fluid dynamics (CFD) simulations. The image-based line morphology quantifiers proposed in this work can be used for online detection of incipient process drifts, while the CFD model is valuable to ascertain the appropriate corrective action to bring the process back in control in case of a drift.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleComputational Fluid Dynamics Modeling and Online Monitoring of Aerosol Jet Printing Process
    typeJournal Paper
    journal volume139
    journal issue2
    journal titleJournal of Manufacturing Science and Engineering
    identifier doi10.1115/1.4034591
    journal fristpage21015
    journal lastpage021015-21
    treeJournal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 002
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian