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.
@article{arxiv.2407.16933,
title = {Deep Koopman-based Control of Quality Variation in Multistage Manufacturing Systems},
author = {Zhiyi Chen and Harshal Maske and Devesh Upadhyay and Huanyi Shui and Xun Huan and Jun Ni},
journal= {arXiv preprint arXiv:2407.16933},
year = {2025}
}
Comments
The paper was in the proceeding of 2024 American Control Conference. This submitted version addresses a minor correction to one equation (Eq. 14), while the results and conclusions remain the same