Utilising Digital Twins to Bolster the Sustainability of Logistics Processes in Industry 4.0
Ladislav Rigó,
Jana Fabianová (),
Milan Lokšík and
Nikoleta Mikušová
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Ladislav Rigó: Institute of logistics and Transport, Faculty of Mining, Ecology, Process Control and Geotechnology, Technical University of Kosice, Letná 9, 042 00 Košice, Slovakia
Jana Fabianová: Institute of logistics and Transport, Faculty of Mining, Ecology, Process Control and Geotechnology, Technical University of Kosice, Letná 9, 042 00 Košice, Slovakia
Milan Lokšík: SOVA Digital a.s., Bojnická 3, 831 04 Bratislava, Slovakia
Nikoleta Mikušová: Institute of logistics and Transport, Faculty of Mining, Ecology, Process Control and Geotechnology, Technical University of Kosice, Letná 9, 042 00 Košice, Slovakia
Sustainability, 2024, vol. 16, issue 6, 1-15
Abstract:
Industry 4.0, characterized by the integration of advanced technologies, has allowed industries to optimise operations, reduce waste, and minimize environmental impact. Digitalization has become a cornerstone for achieving sustainability goals, and one of the key enablers of Industry 4.0 is the digital twin. The digital twin provides real-time insights and simulations to optimise processes. Organizations can thus optimise not only their operations but also contribute to a more resilient global supply chain. The aim of the paper is to present a comprehensive methodology for implementing the digital twin principle in the Tecnomatix environment. The Tecnomatix model is connected to Siemens PLC SIMATIC S7-1200 utilizing the OPC UA (Unified Architecture) method and through KEPServerEX, V6.14.263.0. The described approach enables continuous monitoring of critical indicators to optimise production efficiency and address downtime issues.
Keywords: Industry 4.0; digital twin; Tecnomatix plant simulation; PTC Kepware; KEPServerEX (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:6:p:2575-:d:1361073
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