Simulation Of An Order Picking System In A Manufacturing Supermarket Using Collaborative Robots

Abstract

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.

Modelling time efficiency of cobot-supported kit preparation

“…The results from the paper align well with previous studies that have considered cobots applied to kit preparation [e.g. 7,8]. An important contribution made by this paper is the model for how a cobot can support kit preparation by sorting components into a batch of kits.…”

“…From the above, it can be seen that cobots applied with kit preparation have not received much attention in previous research, Fager et al [10] and Coelho et al [8] marking exceptions. It can also be seen that there have been a few reports of robot arms applied for carrying out component picking in kit preparation activities [e.g.…”

“…Among all their possible applications, cobots can also be used to support kit preparation, for example, by helping the operator in sorting the items, reducing picking errors, and guaranteeing more stable cycle times [7,8]. Coelho et al [8] developed a simulation model and compared various kitting applications, some of which involved cobots. Their results suggest that human workers are associated with higher productivity, but that the cobots are better at dealing with uncertainty and for reducing output variability.…”

“…7,9] and that there are vision systems capable of supporting this task [14]. While literature that considers applications of kit preparation that involve cobots is scant, the available literature suggests there is a potential of better dealing with uncertainty and reduced variability of outputs [8,10]. However, no studies exist that can account for the effects of using cobots to support the sorting of components into kit containers when order batching is applied, accounting for production system characteristics and decision variables associated with cobot application.…”

“…Moreover, manual kit prepara-tion is prone to human errors that lead to errors in kits, which are disruptive and costly at assembly processes [5,6]. Recent research has shown that robots can support time-efficient kit preparation by relieving pickers of some of the tasks in kit preparation while simultaneously supporting kit quality by removing the risk of human errors [7][8][9]. However, kit preparation supported by cobotsthat is, collaborative robots that share workspaces with pickershas so far received less attention, and there is considerable confusion in industry with regard to how cobots can be used in kit preparation.…”