Paper ID: 2407.16933

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

Zhiyi Chen, Harshal Maske, Devesh Upadhyay, Huanyi Shui, Xun Huan, Jun Ni

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.

Submitted: Jul 24, 2024