A Simulation Model of Automated Storage and Retrieval Systems for Long and Heavy Loads

Automated storage and retrieval systems for long and heavy unit loads (LH AS/RSs) are already applied in industrial environments. However, the existing literature does not provide quantitative analyses of how the load-mass distribution influences energy consumption and energy regeneration. The present study addresses this gap by implementing an analytical model and developing an advanced simulation model that evaluates how the mass distribution of transport unit loads (TULs) affects the energy behaviour of LH AS/RSs. The model considers three velocity profiles under two storage strategies: random storage and class-based storage. The class-based storage strategy incorporates vertical mass-based zoning, in which the storage height of each TUL is assigned according to the statistical distribution of TUL masses. The simulation results show that mass-based zoning can reduce energy consumption by up to 9% for the combined movement of the stacker crane and lifting platform and by up to 11% for the vertical movement of the lifting platform alone. In addition, both the random and class-based storage strategies achieve approximately 35% energy regeneration. These findings provide the first explicit quantification of the energy savings achievable through mass-based vertical zoning in LH AS/RSs and offer practical guidance for warehouse designers and managers on how to leverage TUL mass distribution when selecting storage strategies and configuring storage rack layouts to improve energy efficiency, support sustainability goals, and enhance LH AS/RS performance.