Simulation-based logistics optimisation in automotive manufacturing: from route rationalisation to smart agv implementation

In modern automotive manufacturing, intralogistics systems play a critical role in ensuring production continuity, energy efficiency, and workforce safety. Increasing demand variability, layout constraints, and sustainability requirements challenge traditional material handling strategies, particularly in Body Shop environments characterised by high takt time rigidity and limited buffer capacity. This study presents a structured decision-support framework for intralogistics optimisation based on a two-phase approach. First, an analytical workload-based route rationalisation method is applied to rebalance material supply routes and identify critical saturation conditions. Second, a discrete event simulation (DES) model is developed to validate the proposed configuration and evaluate operational performance under realistic system interactions. The methodology is applied to an industrial case study within the Body Shop department of a leading automotive manufacturer, focusing on the transition from manual logistics to automated guided vehicle (AGV) supply. Key performance indicators, including route saturation, AGV utilisation, travel time, energy consumption, and economic impact, are quantitatively assessed. Results demonstrate that the proposed framework enables a reduction in non-value-adding movements, a decrease in operator workload, and measurable improvements in energy and operational efficiency, while maintaining service reliability. Rather than proposing a new automation technology, the contribution of this work lies in a transferable hybrid analytical-simulation framework that supports energy-aware intralogistics decision-making in complex manufacturing environments.