Machine Dynamics-Aware CPS Scheduling and Iterative Validation for Industry 4.0

Modern manufacturing demands physically feasible, optimized schedules, but traditional methods often neglect machine dynamics, yielding theoretically optimal yet not robustly feasible plans in practice. This paper presents a comprehensive workflow bridging this gap for cyber-physical production systems. Our first contribution enhances production line schedule synthesis with variable discretization steps for mode sequences, balancing accuracy and efficiency. Second, we propose a novel validation framework using Frost, a deterministic digital twin built on Lingua Franca. This framework models physical dynamics using adaptive ODE solvers and the full software/communication stack. Crucially, significant deviations in Frost simulations trigger an iterative re-synthesis loop. This closed-loop approach, underpinned by Lingua Franca's determinism, ensures schedules are rigorously validated and iteratively improved for practical feasibility in complex cyber-physical settings.