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The Printing of Highly Uniform Display Device by Graph Convolutional Neural Network-Based Manufacturing

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Abstract:

The field of print display manufacturing still faces the challenge of uneven volume printing. This paper proposes an integer programming framework tailored to the printing process for volume optimisation, alongside a mimetic solving algorithm based on a graph convolutional neural network. These methods enable the accurate resolution of models and achieve volume uniformity with an error margin of less than 2%, effectively addressing inconsistencies in pixel pit printing. Simulation and experimental results validate the efficacy of the approach.

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Engineering Innovations Vol. 19 Read eBook

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Periodical:

Engineering Innovations (Volume 19)

Pages:

107-113

DOI:

https://doi.org/10.4028/p-D1g7wK

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Cite this paper

Online since:

June 2026

Authors:

Jia Cong Xiong*, Jian Kui Chen, Zi Wei Zhao

Keywords:

Graph Neural Network, High Uniformity Manufacturing, Integer Planning, Organic Light-Emitting Diode, Print Manufacturing

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Creative Commons CC BY 4.0

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* - Corresponding Author

References

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