Quality Modeling of Printed Electronics in Aerosol Jet Printing Based on Microscopic ImagesSource: Journal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 007::page 71012DOI: 10.1115/1.4035586Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Aerosol jet printing (AJP) is a direct write technology that enables fabrication of flexible, fine scale printed electronics on conformal substrates. AJP does not require the time consuming mask and postpatterning processes compared with traditional electronics manufacturing techniques. Thus, the cycle time can be dramatically reduced, and highly personalized designs of electronics can be realized. AJP has been successfully applied to a variety of industries, with different combinations of inks and substrates. However, the quality of the printed electronics, such as resistance, is not able to be measured online. On the other hand, the microscopic image sensors are widely used for printed circuit boards (PCBs) quality quantification and inspection. In this paper, two widely used quality variables of printed electronics, resistance and overspray, will be jointly modeled based on microscopic images for fast quality assessment. Augmented quantitative and qualitative (AUGQQ) models are proposed to use features of microscopic images taken at different locations on the printed electronics as input variables, and resistance and overspray as output variables. The association of resistance and overspray can be investigated through the AUGQQ models formulation. A case study for fabricating silver lines with Optomec® aerosol jet system is used to evaluate the model performance. The proposed AUGQQ models can help assess the printed electronics quality and identify important image features in a timely manner.
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contributor author | Sun, Hongyue | |
contributor author | Wang, Kan | |
contributor author | Li, Yifu | |
contributor author | Zhang, Chuck | |
contributor author | Jin, Ran | |
date accessioned | 2017-11-25T07:17:50Z | |
date available | 2017-11-25T07:17:50Z | |
date copyright | 2017/10/4 | |
date issued | 2017 | |
identifier issn | 1087-1357 | |
identifier other | manu_139_07_071012.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4234789 | |
description abstract | Aerosol jet printing (AJP) is a direct write technology that enables fabrication of flexible, fine scale printed electronics on conformal substrates. AJP does not require the time consuming mask and postpatterning processes compared with traditional electronics manufacturing techniques. Thus, the cycle time can be dramatically reduced, and highly personalized designs of electronics can be realized. AJP has been successfully applied to a variety of industries, with different combinations of inks and substrates. However, the quality of the printed electronics, such as resistance, is not able to be measured online. On the other hand, the microscopic image sensors are widely used for printed circuit boards (PCBs) quality quantification and inspection. In this paper, two widely used quality variables of printed electronics, resistance and overspray, will be jointly modeled based on microscopic images for fast quality assessment. Augmented quantitative and qualitative (AUGQQ) models are proposed to use features of microscopic images taken at different locations on the printed electronics as input variables, and resistance and overspray as output variables. The association of resistance and overspray can be investigated through the AUGQQ models formulation. A case study for fabricating silver lines with Optomec® aerosol jet system is used to evaluate the model performance. The proposed AUGQQ models can help assess the printed electronics quality and identify important image features in a timely manner. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Quality Modeling of Printed Electronics in Aerosol Jet Printing Based on Microscopic Images | |
type | Journal Paper | |
journal volume | 139 | |
journal issue | 7 | |
journal title | Journal of Manufacturing Science and Engineering | |
identifier doi | 10.1115/1.4035586 | |
journal fristpage | 71012 | |
journal lastpage | 071012-10 | |
tree | Journal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 007 | |
contenttype | Fulltext |