Computational Fluid Dynamics Modeling and Online Monitoring of Aerosol Jet Printing ProcessSource: Journal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 002::page 21015Author:Salary, Roozbeh (Ross)
,
Lombardi, Jack P.
,
Samie Tootooni, M.
,
Donovan, Ryan
,
Rao, Prahalad K.
,
Borgesen, Peter
,
Poliks, Mark D.
DOI: 10.1115/1.4034591Publisher: 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.
|
Collections
Show full item record
contributor author | Salary, Roozbeh (Ross) | |
contributor author | Lombardi, Jack P. | |
contributor author | Samie Tootooni, M. | |
contributor author | Donovan, Ryan | |
contributor author | Rao, Prahalad K. | |
contributor author | Borgesen, Peter | |
contributor author | Poliks, Mark D. | |
date accessioned | 2017-11-25T07:17:37Z | |
date available | 2017-11-25T07:17:37Z | |
date copyright | 2016/3/10 | |
date issued | 2017 | |
identifier issn | 1087-1357 | |
identifier other | manu_139_02_021015.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4234682 | |
description 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. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Computational Fluid Dynamics Modeling and Online Monitoring of Aerosol Jet Printing Process | |
type | Journal Paper | |
journal volume | 139 | |
journal issue | 2 | |
journal title | Journal of Manufacturing Science and Engineering | |
identifier doi | 10.1115/1.4034591 | |
journal fristpage | 21015 | |
journal lastpage | 021015-21 | |
tree | Journal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 002 | |
contenttype | Fulltext |