Deep Koopman-based Control of Quality Variation in Multistage Manufacturing Systems

This paper presents a modeling-control synthesis to address the quality control challenges in multistage manufacturing systems (MMSs). A new feedforward control scheme is developed to minimize the quality variations caused by process disturbances in MMSs. Notably, the control framework leverages a s...

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Bibliographic Details
Published inarXiv.org
Main Authors Chen, Zhiyi, Maske, Harshal, Upadhyay, Devesh, Huanyi Shui, Huan, Xun, Ni, Jun
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 24.07.2024
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Summary:This paper presents a modeling-control synthesis to address the quality control challenges in multistage manufacturing systems (MMSs). A new feedforward control scheme is developed to minimize the quality variations caused by process disturbances in MMSs. Notably, the control framework leverages a stochastic deep Koopman (SDK) model to capture the quality propagation mechanism in the MMSs, highlighted by its ability to transform the nonlinear propagation dynamics into a linear one. Two roll-to-roll case studies are presented to validate the proposed method and demonstrate its effectiveness. The overall method is suitable for nonlinear MMSs and does not require extensive expert knowledge.
ISSN:2331-8422