Leveraging Digital Twins for Enhanced PLC Performance and Maintenance in Industrial Automation
This study analyzes the new use of digital twins technology in programmable logic controllers (PLC) within the scope of industrial automation. The goal of this work is to show the possibilities of applying digital twins in conjunction with PLCs for industrial purposes. The integration of digital twins with PLCs may provide substantial benefits in operational efficiency, predictive maintenance, process optimization, and innovation across various sectors. Following the methodology of bibliographic survey, which is rather limited due to the novelty of the topic, several examples have been spotted. Through these examples, the impact of digital twins on production optimization, maintenance, monitoring, remote operation, and virtual commissioning are examined. The case examples also address challenges related to guaranteeing the quality of data constraining scalability, and issues of security in the implementation of digital twins and PLCs. The paper explores future directions, such as advanced analytics, IoT applications, virtual reality, and standardized interface metrology. The development of digital twins in regards to PLCs has enormous potential and can help organizations to become more efficient, optimized, and competitive in industrial automation. Embracing this technology provides new opportunities for organizational operations and drives improvement on a continuous basis.
Authors
- Ioannis Giachos
- Ευάγγελος Χρήστος Παπακίτσος (ORCID: https://orcid.org/0000-0002-0218-489X)
- Nikolaos Laskaris (ORCID: https://orcid.org/0000-0002-1960-394X)
- Kentaro Mita
- Michail Papoutsidakis (ORCID: https://orcid.org/0000-0001-8338-7690)
- Christos Drosos (ORCID: https://orcid.org/0000-0001-8068-8885)
Institutions
- University of West Attica (GR)
Publication Details
- Journal
- International Journal of Electrical Engineering and Computer Science
- Published
- 2025-09-09
- DOI
- https://doi.org/10.37394/232027.2025.7.13
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.00