Automated stacker crane warehouse expansion: logistics and energy efficiency study aligned with “Piano Transizione 5.0”

The adoption of integrated automation systems for managing logistics flows is now a strategic lever to improve production efficiency, reduce energy consumption and meet the current goals in sustainability and industrial digitization. In this context, this thesis has been developed in collaboration with GAI Macchine Imbottigliatrici S.p.A., a leading company in the beverage sector, with the aim of analyzing and optimizing the logistical and energy performance of an ASRS (Automated Storage and Retrieval System) system subject to an expansion intervention. The activity involved an in-depth study of the main components of the automated stacker crane warehouse – stacker cranes, shuttles and automated guided vehicles – aimed at developing a reliable and replicable energy model. This model allows to estimate the percentage reduction in energy demand (expressed in kWh) following the planned expansion, a necessary condition for accessing tax credit incentives under the Italian “Piano Transizione 5.0”. To ensure the validity of the comparison between the pre- and post-expansion configurations, the adopted methodology is based on the simulation of operating cycles, through the correlation of key parameters such as the number and type of missions, the meters travelled and the specific consumption for each handling system. The modelling, structured in several phases, led to the creation of a flexible parametric model that integrates the management logic of the WMS (Warehouse Management System), considering the current and future plant configuration, using energy data collected through advanced monitoring systems. Particular attention has been given to the most influential variables – such as travel distances and mission distribution – and to the handling of edge cases (e.g. absence of missions) trough the use of conditional functions, to guarantee the stability of the model. The results show a significant alignment across the simulated scenarios, validating the adopted methodology. The average energy efficiency detected, also obtained thanks to the introduction of regenerative inverters on future stacker cranes, exceeds the 5% threshold, meeting the regulatory requirements. Finally, the proposed model has been designed to be reusable over time, through the definition of fixed consumption parameters for each user, thus allowing the energy efficiency of the system to be continuously monitored even in the five years following the intervention, in line with the requirements for the reporting required by the Transition Plan 5.0.