3D modelling of warehouse logistics in FlexSim software: Optimisation of logistics processes and resource management

Abstract

The purpose of the study was to theoretically substantiate the potential of FlexSim software for threedimensional modelling of warehouse logistics, improving warehouse processes, and providing analytical support for resource management in warehouse logistics systems. The study was theoretical and analytical in nature and was based on the systematisation of structural components of the composition, areas of three-dimensional modelling, FlexSim functionality, and resource balancing methods. The results showed that a warehouse should be viewed not as a static space for storing goods, but as a process-based system in which goods receipt, identification, storage, replenishment of picking zones, order picking, internal transport, packaging, dispatch, and stock control form a single operational chain. It was established that the three-dimensional model in FlexSim should combine the physical components of the warehouse – zones, racks, routes, workstations, equipment, conveyors, and automated vehicles – with logical components: queues, buffers, routing rules, service priorities and resource usage modes. Systematisation of 3D modelling areas has shown that optimisation of warehouse processes was formed at the spatial, process, and resource levels. The spatial level was estimated through average storage capacity utilisation ≥90% and peak capacity utilisation ≥100%; process level through time product acceptance to placement <3.5 h, internal order processing cycle <3.36 h, and full order processing cycle <6 h; resource level through ion and shipment performance ≥70 order lines/man-hour, overtime share <1.88%, average waiting time, maximum queue length, and resource utilisation level. The practical significance of the study is to form an integral conceptual model that is valuable for logistics managers, warehouse managers, and supply chain analysts, as it allows them to pre-identify bottlenecks, queues, downtime, resource imbalances, and risks of disrupting the rhythm of warehouse operations.