IoTwins: Toward Implementation of Distributed Digital Twins in Industry 4.0 Settings

Abstract

While the digital twins paradigm has attracted the interest of several research communities over the past twenty years, it has also gained ground recently in industrial environments, where mature technologies such as cloud, edge and IoT promise to enable the cost-effective implementation of digital twins. In the industrial manufacturing field, a digital model refers to a virtual representation of a physical product or process that integrates data taken from various sources, such as application program interface (API) data, historical data, embedded sensor data and open data, and that is capable of providing manufacturers with unprecedented insights into the product’s expected performance or the defects that may cause malfunctions. The EU-funded IoTwins project aims to build a solid platform that manufacturers can access to develop hybrid digital twins (DTs) of their assets, deploy them as close to the data origin as possible (on IoT gateway or on edge nodes) and take advantage of cloud-based resources to off-load intensive computational tasks such as, e.g., big data analytics and machine learning (ML) model training. In this paper, we present the main research goals of the IoTwins project and discuss its reference architecture, platform functionalities and building components. Finally, we discuss an industry-related use case that showcases how manufacturers can leverage the potential of the IoTwins platform to develop and execute distributed DTs for the the predictive-maintenance purpose.

Towards a Distributed Digital Twin Framework for Predictive Maintenance in Industrial Internet of Things (IIoT)

“…On the distributed digital twin concept, work by [ 18 ] presented the concept of “IoTwins”, in which the authors argue that the best strategy for implementing DTs is to deploy them close to the data sources to leverage IoT gateway on edge nodes and use the cloud for heavier computational task such as machine learning model training. In their reference architecture, the authors outline how the edge-fog-cloud paradigm can allow a distributed DT to leverage the needed layers of computing and interfaces that are suitable for real-time applications.…”

Metaverse for Cultural Heritages

“…Jwo et al [19] came up with a concept of DT based deployable service, Data Twin Service (DTS), to support simulation for Industry 4.0. Costantini et al [20] studied the IoTwins to develop and execute distributed DTs for predictive maintenance purposes. Alizadehsalehi & Yitmen [21] presented a framework for an automated construction progress monitoring system that integrates BIM, various reality capturing technologies, DT and XR technologies (VR, AR and MR), arraying the steps in how these technologies work collaboratively to create, capture, generate, analyze, manage and visualize construction progress data, information and reports.…”

Enhancing and securing cyber‐physical systems and Industry 4.0 through digital twins: A critical review

“…Digital twins consist of a physical part, a virtual part and the interaction between them 85 . Additionally, they are heavily associated with the development of Industry 4.0 and its automation processes 86,87 as they can be integrated throughout the product life‐cycle, 9 can capture the past and present and predict the future state and behaviors of physical assets, systems, and services 88 and offer insights into the product and service expected performance and results as well as identifying potential threats and defects that might bring about malfunctions in real time 89 …”

“…85 Additionally, they are heavily associated with the development of Industry 4.0 and its automation processes 86,87 as they can be integrated throughout the product life-cycle, 9 can capture the past and present and predict the future state and behaviors of physical assets, systems, and services 88 and offer insights into the product and service expected performance and results as well as identifying potential threats and defects that might bring about malfunctions in real time. 89 In general, a digital twin can be regarded as a service architecture for cyber-physical manufacturing systems, consists of models and software services and consists of various models that utilize multiple information and data aspects. 90 Digital twins are in unison with physical systems and include and map cross-domain models of physical assets.…”