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Bayesian Strategy for the Volume Accuracy of Ink Droplets Continuous Estimation during Printing Based on Prior Knowledge with Earth Mover’s Distance

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Abstract:

Monitoring the volume accuracy of ink droplets during printing is important for OLED panel production. This article uses data from ink droplet observation volumes before printing to build a membership distribution histogram and intuitively describes the volume status of multiple nozzles. A histogram in conjunction with the Earth Mover’s Distance (EMD) indicator is used to design prior knowledge, which describes a subjective estimate of ink droplet volume distribution based on experimental data. And using the likelihood function, combining the sampled data of the ink droplets observation volume, obtains the volume accuracy estimate of the ink droplets during printing. This article proposes a Bayesian strategy for the volume accuracy of ink droplet continuous estimation during printing based on prior knowledge with EMD. This strategy can randomly inspect any number of samples of nozzles in the production process and get a reasonable estimate of volume after each sampling observation, which can realize continuous estimation and adjustment for the volume accuracy of ink droplets during printing.

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Engineering Innovations Vol. 19 Read eBook

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Periodical:

Engineering Innovations (Volume 19)

Pages:

101-106

DOI:

https://doi.org/10.4028/p-JOBaY6

Citation:

Cite this paper

Online since:

June 2026

Authors:

Deyi Kong*, Jian Kui Chen, Jia Cong Xiong

Keywords:

Bayes Inference, Continuous Evaluation, IJP OLED, Volume Accuracy

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Creative Commons CC BY 4.0

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* - Corresponding Author

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