Abstract
The topic of this paper represents our research in the process of creating a virtual model (digital twin) for a fast-food company production chain starting with the moment when a customer launches an order, following with the processing of that order, until the customer receives it. The model will describe elements that are included in this process such as equipment, human resources and the necessary space that is needed to host this layout. The virtual model created in a simulation platform will be a replicate of a real fast-food company, thus helping us observe the real time dynamic of this production system. Using WITNESS HORIZON 23 we will construct the model of the layout based on real time data received from the fast-food company. This digital twin will be used to manage the production chain material flow, evaluating the performance of the system architecture in various scenarios. In order to obtain a diagnosis of the system’s performance we will simulate the workflow running through preliminary architecture in compliance with the real time behaviour to identify the bottlenecks and blockages in the flow trajectory. In the end we will propose two different optimised architectures for the fast-food company production chain.
Highlights
The topic of this paper represents our research in the process of creating a virtual model for a fast-food company production chain starting with the moment when a customer launches an order, following with the processing of that order, until the customer receives it
Based on the technological flow model and the structural elements presented above we created a digital twin of the preliminary manufacturing architecture model using as a flow simulator WITNESS Horizon software
The accent is put on exploring different possibilities to increase productivity and profit in fast food production architectures using an approach based on virtual modelling and simulation
Summary
The first restaurant with automatic serving system was opened in Moscow. The clients no longer interact with the employees which makes it ideal to keep the safety measures during the pandemic. A video camera reads the biometric data of the customer at the pick-up point the system recognizes the customer and his order. A robotic arm places on an automatic band the products, which are picked up by the customer at the collection point. Disadvantages: workflow stops if the robot does not work properly, does not replace the human resource, products are still processed by humans. Analysing that we consider that this model can definitely be improved, as the robot is quite slow, takes a lot of space and should be fixed on the wall rather than on the ground
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