IoTwins: Implementing Distributed and Hybrid Digital Twins in Industrial Manufacturing and Facility Management Settings

Paolo Bellavista and Giuseppe Di Modica ()
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Paolo Bellavista: Dipartimento di Informatica, Scienza e Ingegneria, Università di Bologna, Via Risorgimento 2, 40136 Bologna, Italy
Giuseppe Di Modica: Dipartimento di Informatica, Scienza e Ingegneria, Università di Bologna, Via Risorgimento 2, 40136 Bologna, Italy

Future Internet, 2024, vol. 16, issue 2, 1-18

Abstract: A Digital Twin (DT) refers to a virtual representation or digital replica of a physical object, system, process, or entity. This concept involves creating a detailed, real-time digital counterpart that mimics the behavior, characteristics, and attributes of its physical counterpart. DTs have the potential to improve efficiency, reduce costs, and enhance decision-making by providing a detailed, real-time understanding of the physical systems they represent. While this technology is finding application in numerous fields, such as energy, healthcare, and transportation, it appears to be a key component of the digital transformation of industries fostered by the fourth Industrial revolution (Industry 4.0). In this paper, we present the research results achieved by IoTwins, a European research project aimed at investigating opportunities and issues of adopting DTs in the fields of industrial manufacturing and facility management. Particularly, we discuss a DT model and a reference architecture for use by the research community to implement a platform for the development and deployment of industrial DTs in the cloud continuum. Guided by the devised architectures’ principles, we implemented an open platform and a development methodology to help companies build DT-based industrial applications and deploy them in the so-called Edge/Cloud continuum. To prove the research value and the usability of the implemented platform, we discuss a simple yet practical development use case.

Keywords: digital twins; Industry 4.0; IoT; IIoT; RAMI 4.0; orchestration; TOSCA; cloud continuum; edge; predictive maintenance (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
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