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How do we Engineer Trustworthy Digital Twins?

July 2023
Research Directions Cyber-Physical Systems 1:1-6

DOI:10.1017/cbp.2023.3

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CC BY 4.0

Authors:

Peter Gorm Larsen

Aarhus University

Jim Woodcock

University of York

There has been a rapid rise of interest in the potential of digital twins to transform a vast range of Cyber-Physical System (CPS) applications, from national infrastructure to surgical robots. But what frameworks, methods and tools are needed to create and maintain digital twins on which we can depend?

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How do we Engineer Trustworthy Digital Twins?

Peter Gorm Larsen1, John Fitzgerald2, and Jim Woodcock3

1Aarhus University Faculty of Health Sciences, Aarhus, Denmark

2Newcastle University, Newcastle upon Tyne, United Kingdom of Great Britain and Northern

Ireland

3University of York, York, United Kingdom of Great Britain and Northern Ireland

Context

There has been a rapid rise of interest in the potential of Digital Twins to transform a vast

range of Cyber-Physical System (CPS) applications, from national infrastructure to surgical

robots. But what frameworks, methods and tools are needed to create and maintain Digital

Twins on which we can depend?

Digital Twins are virtual replicas of real-world systems. Unlike traditional models, data and

control flows couple a digital twin to the CPS of interest and must remain up to date as the

CPS evolves. The twin can influence or control the CPS itself. It is not a substitute for the

CPS. However, it adds value by providing analytics, visualisation or other capabilities,

allowing the twin’s users to make better-informed decisions about interventions. These

include preventive maintenance, response to accidental or malicious events, and

reconfiguration and redesign.

https://doi.org/10.1017/cbp.2023.3 Published online by Cambridge University Press

Accepted Manuscript

This digital twin vision is attractive. However, for a twin to merit the reliance we place on it,

we need frameworks, methods, and tools that systematically address the full range of systems

engineering activities. We must produce evidence that adds to our confidence that a twin is fit

for purpose. Digital twins for CPSs need multi-disciplinary models and analytic services,

raising significant challenges: maintaining sufficient fidelity to the evolving CPS, time

delays, noise in communications to and from the twin, interactions with other systems and

human operators, and the need for CPS elements and environments to evolve.

In this research question, we welcome contributions to the systematic engineering of

trustworthy digital twins supporting CPSs to provide additional value for their users.

Examples include, but are not limited to, frameworks, methods, and tools for the following:

 Systems engineering for dependable digital twins of CPSs.

 Architectures for dependable digital twins.

 Support for CPS operation in environments outside our control.

 CPS anomaly detection in digital twins.

 Addressing noise and timing delays in twin-CPS communications.

 Composing diverse digital twins in systems-of-systems and their impact on

dependability.

 Ensuring dependability, including security and safety, of digital twins and digital

twin-enabled systems.

 Determining when to enable a CPS to be autonomous and when to rely on humans to

take decisions.

 Coping with real-time data for simulation when carrying out “what-if” scenarios.

 Ensuring consistency between models of CPSs at different levels of abstraction inside

a DT and automatically choosing the best one for the desired analysis.

We want to measure progress in answering this question. We welcome suggestions from the

community for a set of public CPS case studies as benchmark problems. As a starting point

we propose a simple “hello world” case study that has proved helpful in illustrating digital

twin features: an incubator. We believe the CPS community will benefit from arranging a

scientific event to discuss how to establish additional and more complex curated CPS case

studies to measure progress.

https://doi.org/10.1017/cbp.2023.3 Published online by Cambridge University Press

Accepted Manuscript

How to contribute to this Question

If you believe you can contribute to answering this Question with your research outputs find

out how to submit in the Instructions for authors

(https://www.cambridge.org/core/journals/research-directions-cyber-physical-

systems/information/author-instructions/preparing-your-materials).

This journal publishes Results, Analyses, Impact papers and additional content such as

preprints and “grey literature”. Questions will be closed when the editors agree that enough

has been published to answer the Question so before submitting, check if this is still an active

Question. If it is closed, another relevant Question may be currently open, so do review all

the open Questions in your field. For any further queries check the information pages

(https://www.cambridge.org/core/journals/research-directions-cyber-physical-

systems/information/about-this-journal) or contact this email (cps@cambridge.org).

Competing interests: The authors declare none.

https://doi.org/10.1017/cbp.2023.3 Published online by Cambridge University Press

Accepted Manuscript

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Sustainable Intelligent Transportation Systems via Digital Twins: A Contextualized Survey

Article

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Jan 2025

Intelligent transportation systems (ITS) have been attracting the attention of industry and academia alike for addressing issues raised by the 2030 agenda for sustainable development goals (SDG) approved by the United Nations. However, the diversity and dynamics of present-day transportation scenarios are already very complex, turning the management of ITS into a virtually impossible task for conventional traffic control centers. Recently, the digital twin (DT) paradigm has been presented as a modern architectural concept to tackle complex problems, such as the ones faced by ITS. This survey aims to provide a piece-wise approach to introducing DTs into sustainable ITS by addressing the following cornerstone aspects: i) Why should one consider DTs in ITS applications? ii) What can DTs represent from ITS’ new physical environments? And iii) How can one use DTs to address ITS SDG related to efficiency, safety, and ecology? Our methodological approach for surveying the literature addresses these questions by categorizing contributions and discriminating their ITS elements and agents against the SDG they addressed. Thus, this survey provides an in-depth and contextualized overview of the challenges when approaching ITS through DTs, including scenarios involving autonomous and connected vehicles, ITS infrastructure, and traffic agents’ behavior. Moreover, we propose a functional reference framework for developing DTs of ITS. Finally, we also offer research challenges regarding standardization, connectivity infrastructure, security and privacy aspects, and business management for properly developing DTs for sustainable ITS.

Fluidware Meets Digital Twins

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The rapid progress in digital technologies has opened up opportunities for creating and using Digital Twins, which facilitate and advance the connection between physical systems and their virtual counterparts. In this chapter we report an overview on the topic of Digital Twins which is gaining importance especially in the design and implementation of complex IoT and cyber-physical systems. In particular, we describe the contributions of the Fluidware project that relate to Digital Twins and discuss remaining challenges and emerging concepts that enhance the one of Digital Twin.

Cyber‐physical‐based welding systems: Components and implementation strategies

Article

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The conditions for a feasible Cyber‐Physical System (CPS) in a welding environment are explored for the manufacturing technology components while also focusing on machine learning tools. Increasing manufacturing efficiency means making digitalisation feasible for all technologies, including welding, given today's challenges. Early versions of manufacturing management, such as Computer Integrated Manufacturing, are already leading the way, and one of the latest milestones in these developments is CPS. It can be shown that the digital migration of specific sub‐domains (e.g. visual inspection of the weld seam during quality assurance) is significantly more challenging and unimaginable without artificial intelligence applications. However, it is also true that the full integration needed to achieve autonomous manufacturing has yet to be fully achieved, although there is a strong demand in the industry for these CPS to work. In some areas, the digital switchover has already been prepared. However, the interconnection of these subsystems requires modern information systems or, in the case of existing ones, their upgrading to the appropriate level. This research area is set to be addressed comprehensively by initiating several projects. In the initial phase, the aim is to develop an architecture that integrates the various Information Technology applications. In this work, the digital manufacturing environment under CPS is studied, the relevant components are explored, the conditions for the transition from traditional to CPS‐based manufacturing are examined and examples of planned further specific studies on the components are listed.

Design and Development of a Digital Twin Prototype for the SAFE Project

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The rapid advancements in digital technologies have paved the way for the development and utilization of digital twins that allow bridging the gap between physical systems and their virtual representations. This digital twin concept is gaining importance especially in the design of complex IoT and Cyber-Physical systems. At design time a digital twin can in fact be used to represent the to-be system reflecting its characteristics in the digital world and especially to conduct simulations before the system is actually implemented. This paper reports about an approach for the design and implementation of a Digital Twin Prototype for a project involving an IoT life-saving system designed to support the rescue operation of people during a seismic event. The approach as well as the software tool can be adopted to other IoT or Cyber-Physical systems.

Digital twin of electric vehicle battery systems: Comprehensive review of the use cases, requirements, and platforms

Article

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RENEW SUST ENERG REV

Transportation electrification has been fueled by recent advancements in the technology and manufacturing of battery systems, but the industry yet is facing serious challenges that could be addressed using cutting-edge digital technologies. One such novel technology is based on the digital twining of battery systems. Digital twins (DTs) of batteries utilize advanced multi-layer models, artificial intelligence, advanced sensing units, Internet-of-Things technologies, and cloud computing techniques to provide a virtual live representation of the real battery system (the physical twin) to improve the performance, safety, and cost-effectiveness. Furthermore, they orchestrate the operation of the entire battery value chain offering great advantages, such as improving the economy of manufacturing, re-purposing, and recycling processes. In this context, various studies have been carried out discussing the DT applications and use cases from cloud-enabled battery management systems to the digitalization of battery testing. This work provides a comprehensive review of different possible use cases, key enabling technologies, and requirements for battery DTs. The review inclusively discusses the use cases, development/integration platforms, as well as hardware and software requirements for implementation of the battery DTs, including electrical topics related to the modeling and algorithmic approaches, software architec-tures, and digital platforms for DT development and integration. The existing challenges are identified and circumstances that will create enough value to justify these challenges, such as the added costs, are discussed.

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Digital Twin was introduced over a decade ago, as an innovative all-encompassing tool, with perceived benefits including real-time monitoring, simulation, optimisation and accurate forecasting. However, the theoretical framework and practical implementations of digital twin (DT) are yet to fully achieve this vision at scale. Although an increasing number of successful implementations exist in research and industrial works, sufficient implementation details are not publicly available, making it difficult to fully assess their components and effectiveness, to draw comparisons, identify successful solutions, share lessons, and thus to jointly advance and benefit from the DT methodology. This work first presents a review of relevant DT research and industrial works, focusing on the key DT features, current approaches in different domains, and successful DT implementations, to infer the key DT components and properties, and to identify current limitations and reasons behind the delay in the widespread implementation and adoption of digital twin. This work identifies that the major reasons for this delay are: the fact the DT is still a fast evolving concept; the lack of a universal DT reference framework, e.g. DT standards are scarce and still evolving; problem- and domain-dependence; security concerns over shared data; lack of DT performance metrics; and reliance of digital twin on other fast-evolvingtechnologies. Advancements in machine learning, Internet of Things (IoT) and big data have led to significant improvements in DT features such as real-time monitoring and accurate forecasting. Despite this progress and individual company-based efforts, certain research and implementation gaps exist in the field, which have so far prevented the widespread adoption of the DT concept and technology; these gaps are also discussed in this work. Based on reviews of past work and the identified gaps, this work then defines a conceptualisation of DT which includes its components and properties; these also validate the uniqueness of DT as a concept, when compared to similar concepts such as simulation, autonomous systems and optimisation. Real-life case studies are used to showcase the application of the conceptualisation. This work discusses the state-of-the-art in DT, addresses relevant and timely DT questions, and identifies novel research questions, thus contributing to a better understanding of the DT paradigm and advancing the theory and practice of DT and its allied technologies.

Digital Twin Technology Challenges and Applications: A Comprehensive Review

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Full-text available

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A digital twin is a virtual representation of a physical object or process capable of collecting information from the real environment to represent, validate and simulate the physical twin’s present and future behavior. It is a key enabler of data-driven decision making, complex systems monitoring, product validation and simulation and object lifecycle management. As an emergent technology, its widespread implementation is increasing in several domains such as industrial, automotive, medicine, smart cities, etc. The objective of this systematic literature review is to present a comprehensive view on the DT technology and its implementation challenges and limits in the most relevant domains and applications in engineering and beyond.

Improving Digital Twin Experience Reports

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Full-text available

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Digital twins (DTs) are prevalent throughout industrial domains as evidenced by the rapid pace of experience reports in the literature. However, there remains disagreement about the precise definition of a DT and the essential characteristics in the DT paradigm, such as the scope of the system-under-study and the time-scale of its communication with the DT. These experience reports could therefore be hampering further classification and research insights by not reporting all of these relevant details about the DT solutions. We address these concerns by providing a conceptual structure for DTs as a common understanding and checklist for researchers and practitioners to precisely describe the characteristics and capabilities of their DT solutions. We express five experience reports using our structure to demonstrate its applicability and role as a guideline to improve the reporting of characteristics and increase the clarity of future experience reports.

Formally Verified Self-adaptation of an Incubator Digital Twin

Chapter

Oct 2022
Lect Notes Comput Sci

The performance and reliability of Cyber-Physical Systems are increasingly aided through the use of digital twins, which mirror the static and dynamic behaviour of a Cyber-Physical System (CPS) in software. Digital twins enable the development of self-adaptive CPSs which reconfigure their behaviour in response to novel environments. It is crucial that these self-adaptations are formally verified at runtime, to avoid expensive re-certification of the reconfigured CPS. In this paper, we demonstrate formally verified self-adaptation in a digital twinning system, by constructing a non-deterministic model which captures the uncertainties in the system behaviour after a self-adaptation. We use Signal Temporal Logic to specify the safety requirements the system must satisfy after reconfiguration and employ formal methods based on verified monitoring over Flow* flowpipes to check these properties at runtime. This gives us a framework to predictively detect and mitigate unsafe self-adaptations before they can lead to unsafe states in the physical system.KeywordsDigital twinSelf-adaptationReachability analysisSignal temporal logicOptimizationCyber-physical system

Under What Conditions Does a Digital Shadow Track a Periodic Linear Physical System?

Chapter

Sep 2022
Lect Notes Comput Sci

The synchronization between a Digital Shadow (DS) and a Cyber-Physical System (CPS) is paramount to enable anomaly detection, predictive maintenance, what-if analysis, etc. Such synchronization means that a simulation reflects, as closely as possible, the states of the CPS. The simulation however, requires the complete initial state of the system to be known, which is often infeasible in real applications. In our work, we study the conditions under which knowing the initial state of the system is irrelevant for a simulation to eventually synchronize with the CPS. We apply traditional stability analysis to answer this question for linear periodic systems. We demonstrate the method using a simple but representative system, an incubator with a periodic control signal.KeywordsDigital ShadowCyber-Physical SystemStabilityTracking

Integration Of The Mape-K Loop In Digital Twins

Conference Paper

Jul 2022

Introduction to Digital Twin Engineering

Conference Paper

Jul 2021

Digital Twin as a Service (DTaaS) in Industry 4.0: An Architecture Reference Model

Article

Jan 2021
ADV ENG INFORM

Recent findings have shown that Digital Twin served multiple constituencies. However, the dilemma between the scope and scale needs a sophisticated reference architecture, a right set of technologies, and a suitable business model. Most studies in the Digital Twin field have only focused on manufacturing and proposed explicit frameworks and architecture, which faced challenges to support different integration levels through an agile process. Besides, no known empirical research has focused on exploring relationships between Digital Twin and mass individualization. Therefore, the principal objective of this study was to identify suitable Industry 4.0 technologies and a holistic reference architecture model to accomplish the most challenging Digital Twin enabled applications. In this study, a Digital Twin reference architecture was developed and applied in an industrial case. Also, Digital Twin as a Service (DTaaS) paradigm utilized for the digital transformation of unique wetlands with considerable advantages, including smart scheduled maintenance, real-time monitoring, remote controlling, and predicting functionalities. The findings indicate that there is a significant relationship between Digital Twin capabilities as a service and mass individualization.

Digital Twin in Industry: State-of-the-Art

Article

Apr 2019

Digital twin (DT) is one of the most promising enabling technologies for realizing smart manufacturing and Industry 4.0. DTs are characterized by the seamless integration between the cyber and physical spaces. The importance of DTs is increasingly recognized by both academia and industry. It has been almost 15 years since the concept of the DT was initially proposed. To date, many DT applications have been successfully implemented in different industries, including product design, production, prognostics and health management, and some other fields. However, at present, no paper has focused on the review of DT applications in industry. In an effort to understand the development and application of DTs in industry, this paper thoroughly reviews the state-of-the-art of the DT research concerning the key components of DTs, the current development of DTs, and the major DT applications in industry. This paper also outlines the current challenges and some possible directions for future work.