Stacker Crane Management: Consumption Analysis and Regenerative Savings in Sustainable Warehouses

This thesis stems from the need of System Logistics S.p.A. to provide its customers with a reliable estimate of the energy consumption of automated warehouses, an aspect that is becoming increasingly relevant in both technical and economic evaluations. The focus has been placed on stacker cranes, which are key components in storage systems, and on the potential benefits of adopting regenerative technologies. To address this need, a calculation model was developed. Starting from the machine specifications, the warehouse layout, and the classification of pallets into A–B–C categories, the model generates optimized mission cycles that minimize time and maximize throughput. Based on these cycles, it estimates energy consumption both in traditional operation and with regeneration, combining Excel sheets with Python scripts in a single integrated tool. After a phase of experimental validation on real stacker cranes, the model was applied to a concrete industrial project. In this context, the activities carried out as a Project Engineer made it possible to integrate customer-specific data into the model, thus obtaining tangible and comparable consumption estimates. These results allowed the company to clearly quantify the potential savings achievable with regeneration and to provide the customer with a reliable reference for decision-making. The results confirm that regenerative technology can significantly reduce electricity consumption, with direct benefits on operational costs and CO₂ emissions, while also facilitating access to energy-related incentives and certifications.