Digital Twin models in industrial operations: State‐of‐the‐art and future research directions

Abstract

A Digital Twin is a virtual representation of a physical product, asset, process, system, or service that allows us to understand, predict, and optimise their performance for better business outcomes. Recently, the use of Digital Twin in industrial operations has attracted the attention of many scholars and industrial sectors. Despite this, there is still a need to identify its value in industrial operations mainly in production, predictive maintenance, and after-sales services. Similarly, the implementation of a Digital Twin still faces many challenges. In response, a systematic literature review and analysis of 41 papers published between 2016 and 11 July 2020 have been carried out to examine recently published works in the field. Future research directions in the area are also highlighted. The result reveals that, regardless of the challenges, the role of Digital Twin in the advancement of industrial operations, especially production and predictive maintenance is highly significant. However, its role in after-sales services remains limited. Insights are offered for research scholars, companies, and practitioners to understand the current state-of-the-art and challenges, and to indicate future research possibilities in the field. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

A Discrete Process Modelling and Simulation Methodology for Industrial Systems within the Concept of Digital Twins

“…As already mentioned, with the advanced capabilities arising from Industry 4.0, sensors and Internet of Things, process models can be used online as part of a digital twin. In this case, process models can be treated as living models of a system under study that can continually be updated with incoming data from the operating environment (through sensors or data feeds) to monitor and mirror the current status and evaluate its performance [33]. In addition, the projection on the future of the current state of the system process model can be efficient in predicting the future behaviour of a physical system in conjunction with big data management, analytics, artificial intelligence and optimisation techniques and tools using real-time data and certain types of information (such as historical and strategic).…”

“…This new use of process modelling and simulation aims to aid and improve the efficiency of engineering support, the decision-making process, and evaluation of the impact of production changes by providing fast reaction on time [33]. This procedure in the context of a digital twin is continuous, so there is no meaning in defining a specific scenario or the duration of a simulation.…”

Digitale Abbilder als Basis Digitaler Zwillinge im Anlagenbau: Besonderheiten, Herausforderungen und Lösungsansätze

“…werden können [3]. Im Produktionskontext stellt der DZ ein Grundpfeiler Cyber-Physischer Produktionssysteme dar und steigert Transparenz sowie Reproduzierbarkeit der Produktion [4].…”

Digital Twin-Based Monitoring System of Induction Motors Using IoT Sensors and Thermo-Magnetic Finite Element Analysis

“…Other recent works using DT and IoT for fault prediction are [28] and [29]. At [28] introduces a system capable of identifying combined faults of a rotating machine and predicting faults, in a non-invasive machine manner.…”