IIoT-Supported Manufacturing-Material-Flow Tracking in a DES-Based Digital-Twin Environment
Author(s): |
Gergő Dávid Monek
(Central Campus Győr, Széchenyi István University, H-9026 Győr, Hungary)
Szabolcs Fischer (Central Campus Győr, Széchenyi István University, H-9026 Győr, Hungary) |
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Medium: | journal article |
Language(s): | English |
Published in: | Infrastructures, April 2023, n. 4, v. 8 |
Page(s): | 75 |
DOI: | 10.3390/infrastructures8040075 |
Abstract: |
Manufacturing processes can be cited as significant research areas when examining infrastructure systems and infrastructure, as they are inextricably linked to both. Examples include automobile manufacturing, the production of traffic signs, etc. Connecting and utilizing Industry 4.0 technologies and processing simulation solutions to address industry challenges, such as process optimization and fault detection, are gaining in popularity. Cyber-physical systems and digital twins connect the physical and cyber worlds to enable intelligent manufacturing capabilities, increased system flexibility, decreased manufacturing-cycle times, and improved quality. This paper presents a solution that improves the synchronization between the real (physical) and simulation (digital) layers, using discrete-event-driven simulations to create more efficient and accurate digital-twin environments. Using a combination of inexpensive commercial microcontrollers and an inertial-measurement-unit sensor to enhance a standard programmable logic controller process, a discrete-event-simulation-based digital layer is updated in real time to produce a live digital twin. The system can accurately identify and track products throughout the production cycle while simultaneously updating the digital twin in real time. Even independently, the algorithm running on the microcontroller can be used to gather the input parameters required for the simulation of production processes. The implemented environment can serve as a suitable testing ground for investigating the practical applicability of digital-twin solutions. |
Copyright: | © 2023 the Authors. Licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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data sheet - Reference-ID
10722696 - Published on:
22/04/2023 - Last updated on:
10/05/2023