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Manufacturing industries depend on robust internal logistics operations that enable efficient production strategies, as is the case of an assembly line feed by an internal logistics supermarket. Agile decision making in flexible manufacturing elevates the need for planning the overall shop-floor operations and controlling them. This work explores the existing literature regarding the operation of manufacturing supermarkets and proposes a simulation tool that analyses the order picking activity in a logistics supermarket where the usage of robots is explored in order to feed flexible manufacturing assembly lines efficiently leading to economic savings. This is done using Simio-simulation modelling framework based on intelligent objects. The model outputs suggest that the system performance increases with humans. Although, when uncertainty is considered, the collaborative robots are more flexible, which leads to lower variations of performance.