A multi-objective optimization framework for aerosol jet customized line width printing via small data set and prediction uncertainty

Aerosol jet printing (AJP) is a promising non-contact writing technology to fabricate customized and conformal microelectronics devices on flexible substrates. However, in recent years, the printed line quality is highlighted as a limitation in the applications of AJP technology. According to previo...

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Main Authors: Zhang, Haining, Choi, Joon Phil, Moon, Seung Ki, Ngo, Teck Hui
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/160966
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1609662022-08-10T00:46:23Z A multi-objective optimization framework for aerosol jet customized line width printing via small data set and prediction uncertainty Zhang, Haining Choi, Joon Phil Moon, Seung Ki Ngo, Teck Hui School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Aerosol Jet Printing Line Morphology Aerosol jet printing (AJP) is a promising non-contact writing technology to fabricate customized and conformal microelectronics devices on flexible substrates. However, in recent years, the printed line quality is highlighted as a limitation in the applications of AJP technology. According to previous researches, a line printed with high edge roughness and low cross-sectional area will reduce the resistance homogeneity and current carrying capacity, respectively. Despite a high line thickness is beneficial to increase the cross-sectional area, it will be in contradiction with a customized line width under a certain mass flow rate, and may lead to an increase in the line edge roughness. Therefore, it is necessary to minimize the inherent contradictions between different printed line features in a design space. In this research, a multi-objective optimization framework is proposed to optimize the overall printing quality of customized line width. In the proposed framework, Latin hyper sampling is utilized for initial experimental design as it could maximize uniformity in a design space with small dataset. Gaussian process regression (GPR) is then adopted for rapid modeling of the printed line morphology due to its capability of providing prediction uncertainty. Following that, GPR models are driven with an efficient multi-objective genetic algorithm to minimize the inherent contradictions of the AJP process. Thus, the optimal process parameters for customized line width printing can be identified systematically and cost-efficiently in a design space. Experimental results indicate the validity of the proposed framework for customized line width printing. Till now, there are few systematic researches on the optimization of printed line morphology, which is an essential component for AJP. This research attempts to contribute to enriching the body of knowledge on printing process optimization. Nanyang Technological University National Research Foundation (NRF) This research work was conducted in the SMRT-NTU Smart Urban Rail Corporate Laboratory with funding support from the National Research Foundation (NRF), SMRT and Nanyang Technological University; under the Corp Lab@University Scheme. 2022-08-10T00:46:22Z 2022-08-10T00:46:22Z 2020 Journal Article Zhang, H., Choi, J. P., Moon, S. K. & Ngo, T. H. (2020). A multi-objective optimization framework for aerosol jet customized line width printing via small data set and prediction uncertainty. Journal of Materials Processing Technology, 285, 116779-. https://dx.doi.org/10.1016/j.jmatprotec.2020.116779 0924-0136 https://hdl.handle.net/10356/160966 10.1016/j.jmatprotec.2020.116779 2-s2.0-85086010270 285 116779 en Journal of Materials Processing Technology © 2020 Elsevier B.V. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
Aerosol Jet Printing
Line Morphology
spellingShingle Engineering::Mechanical engineering
Aerosol Jet Printing
Line Morphology
Zhang, Haining
Choi, Joon Phil
Moon, Seung Ki
Ngo, Teck Hui
A multi-objective optimization framework for aerosol jet customized line width printing via small data set and prediction uncertainty
description Aerosol jet printing (AJP) is a promising non-contact writing technology to fabricate customized and conformal microelectronics devices on flexible substrates. However, in recent years, the printed line quality is highlighted as a limitation in the applications of AJP technology. According to previous researches, a line printed with high edge roughness and low cross-sectional area will reduce the resistance homogeneity and current carrying capacity, respectively. Despite a high line thickness is beneficial to increase the cross-sectional area, it will be in contradiction with a customized line width under a certain mass flow rate, and may lead to an increase in the line edge roughness. Therefore, it is necessary to minimize the inherent contradictions between different printed line features in a design space. In this research, a multi-objective optimization framework is proposed to optimize the overall printing quality of customized line width. In the proposed framework, Latin hyper sampling is utilized for initial experimental design as it could maximize uniformity in a design space with small dataset. Gaussian process regression (GPR) is then adopted for rapid modeling of the printed line morphology due to its capability of providing prediction uncertainty. Following that, GPR models are driven with an efficient multi-objective genetic algorithm to minimize the inherent contradictions of the AJP process. Thus, the optimal process parameters for customized line width printing can be identified systematically and cost-efficiently in a design space. Experimental results indicate the validity of the proposed framework for customized line width printing. Till now, there are few systematic researches on the optimization of printed line morphology, which is an essential component for AJP. This research attempts to contribute to enriching the body of knowledge on printing process optimization.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Zhang, Haining
Choi, Joon Phil
Moon, Seung Ki
Ngo, Teck Hui
format Article
author Zhang, Haining
Choi, Joon Phil
Moon, Seung Ki
Ngo, Teck Hui
author_sort Zhang, Haining
title A multi-objective optimization framework for aerosol jet customized line width printing via small data set and prediction uncertainty
title_short A multi-objective optimization framework for aerosol jet customized line width printing via small data set and prediction uncertainty
title_full A multi-objective optimization framework for aerosol jet customized line width printing via small data set and prediction uncertainty
title_fullStr A multi-objective optimization framework for aerosol jet customized line width printing via small data set and prediction uncertainty
title_full_unstemmed A multi-objective optimization framework for aerosol jet customized line width printing via small data set and prediction uncertainty
title_sort multi-objective optimization framework for aerosol jet customized line width printing via small data set and prediction uncertainty
publishDate 2022
url https://hdl.handle.net/10356/160966
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