Simulation-based Digital Twin of a Complex Shop-Floor Logistics System
| Autor: | Botond Kádár, David Czirko, Júlia Bergmann, Attila Lengyel, Dávid Gyulai |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
business.industry Computer science QA75 Electronic computers. Computer science / számítástechnika számítógéptudomány 02 engineering and technology Manufacturing engineering 020901 industrial engineering & automation Capacity planning Analytics Manufacturing 0202 electrical engineering electronic engineering information engineering Robot Factory (object-oriented programming) 020201 artificial intelligence & image processing Representation (mathematics) business Digitization Pace |
| Zdroj: | WSC |
| Popis: | Digital analytics tools have been at the forefront of innovation in manufacturing industry in recent years. To keep pace with the demands of industrial digitization, companies seek opportunities to streamline processes and enhance overall efficacy, opting to replace conventional engineering tools with data-driven models. In a high-tech factory, detailed data is collected about the products, processes, and assets in near-real time, providing a basis to build trustworthy analytical models. In this paper, a novel discrete-event simulation (DES) model is proposed for the detailed representation of a complex shop-floor logistics system, employing automated robotic vehicles (AGV). The simulation model is applied to test new AGV management policies, involving both vehicle capacity planning and dispatching decisions. In order to illustrate the usefulness of the model and the effectiveness of the selected policy, numerical results of a case-study are presented, in which the selected policy was realized in a real manufacturing environment. |
| Databáze: | OpenAIRE |
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