Mundt, ChristopherChristopherMundtLödding, HermannHermannLödding2026-09-292026-09-292026-0945th International Conference on Advances in Production Management Systems, APMS 2026https://hdl.handle.net/11420/65092Production Planning and Control (PPC) procedures are very important for a stable production performance but are traditionally evaluated under the assumption of good input data quality. This reliance creates a vulnerability, as industrial environments frequently suffer from high uncertainties and systematic parameter biases that cause continuous, cumulative deviations from logistical target achievement. To address this research gap, this paper introduces a three-step evaluation framework to assess the structural robustness of PPC procedures. The proposed framework combines qualitative analysis, empirical stress testing via discrete event simulation, and mathematically sound analytical modelling using the throughput diagram. The methodology is successfully applied to evaluate the Planned Output Control (POC) procedure. The results show mathematically and empirically that closed-loop control architectures possess a fundamental advantage over open-loop systems in autonomously mitigating parameter drift. This framework enables researchers and practitioners to systematically benchmark and design robust PPC procedures prior to industrial implementation.enTechnology::600: TechnologyConference Paper10.1007/978-3-032-38606-9_23