ERCIM News 115
October 2018
Special theme Digital Twins
Guest editors Benjamin Sanderse (CWI) and Edgar Weippl (SBA)
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by Edgar Weippl (SBA) and Benjamin Sanderse (CWI)
This special issue addresses the current state of digital twin research, illustrating the many facets of this growing scientific field. The contributions collected here give insight in ongoing projects and allow for a glimpse into the future of digital twin technology.
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by Stefan Boschert and Roland Rosen (Siemens AG)
Railroad switches, also called turnouts or points, are a key element of the rail network infrastructure. They are distributed all over the network and their maintenance is crucial to guarantee safety and undisturbed operation. Within a railway network, the turnouts are responsible for a high amount of the operational costs as monitoring and maintenance is mainly manual. Using a combination of measurement data and physics-based simulations – a typical Digital Twin application – has a high potential to identify failures before they become critical. Defining a general methodology to derive such solutions which make use of all the relevant information created along the lifecycle is the subject of our current research.
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by Christophe Ponsard, Renaud De Landtsheer and Birgit Palm (CETIC)
Reflecting the state of a complex physical asset or process into its digital twin cannot be a perfect process. However, accurate reasoning must stay possible on a digital twin even in case of partial or temporary degradation of its connection with its physical counterpart. In the scope of an Industry 4.0 project, we are investigating how to deal with such a challenge for the optimised operation of a steel factory.
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by Jacques Verriet, Jack Sleuters and Richard Doornbos (TNO-ESI)
Modern smart systems are incredibly complicated. Building a digital twin of the system allows engineers to ensure that it works correctly and root out many problems before it is installed.
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by Felix Strohmeier, Christoph Schranz and Georg Güntner (Salzburg Research)
The i-Maintenance toolset is a messaging system that constitutes the technical foundation for digital twins of industrial assets by collecting, monitoring and analysing life cycle data. The messaging solution can be used in an innovative way to set up a prototypical digital twin of a production asset by integrating maintenance management, condition monitoring, IoT and predictive analytics solutions.
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by Cor van Kruijsdijk (Shell Global Solutions International bv)
Shell is using Digital Twin applications to improve operation, maintenance and safety, for example in chemical plants and offshore platforms.
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by Gerardo Santillán Martínez (Aalto University), Tommi Karhela (Aalto University), Reino Ruusu (Semantum Ltd), and Juha Kortelainen (VTT)
Simulation-based digital twins (SBDTs) of process plants can be used for a number of important industrial applications. They have various advantages compared to digital twins based on data-driven models. However, wider industrial adoption of SBDTs is hindered by laborious development of their underlying simulation model as well as by the lack of integration methods with the operational process. The Engineering Rulez research project has tackled these issues by developing a novel automatic model generation method as well as a simulation architecture based on OPC UA, a well-established industrial interoperability standard. The proposed SBDT automatic generation method aims to enable a wider industrial adoption of digital twins based on first principle models.
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by Gábor Závodszky, Alfons G. Hoekstra (University of Amsterdam)
In-silico models of human physiology and pathology are aimed at progressing and complementing medicine in several ways. These models can reproduce physiological processes and events on multiple scale levels. The goal of the individual models is to help predict the outcome of a specific disease or to support the decision-making process during treatment.
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by Vagelis Harmandaris (UOC & IACM-FORTH), Evangelia Kalligiannaki (IACM-FORTH) and Markos A. Katsoulakis (UMass Amherst, USA)
The development of novel materials with desirable properties, such as nanocomposites, polymers, colloids and biomolecular systems, relies heavily on the knowledge of their structure-property relationships. The prediction of such relationships is the subject of computational materials design. Molecular dynamics (MD) simulations at the atomistic level can provide quantitative information about structural and dynamical properties of molecular systems. The recent enormous advances in computational power allow us to perform intense atomistic-level simulations. However, the broad range of length and time scales appearing in such complex (e.g., macromolecular) materials still presents significant computational challenges, especially in tackling engineering and design tasks.
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by Jannis Teunissen (CWI and KU Leuven) and Ute Ebert (CWI and TU/e)
We have developed a framework for efficient 2D and 3D computations on adaptively refined grids, which can be used on shared-memory computers. By using efficient methods, we aim to make interactive (quick!) simulations possible on modest hardware.
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by Matthias Eckhart (TU Wien) and Andreas Ekelhart (SBA Research)
In recent years, the concept of digital twins has received increasing attention. Virtual replicas of cyber-physical systems (CPSs) can be leveraged for monitoring, visualising and predicting states of CPSs, leading to new possibilities to enhance industrial operations. Yet, the benefit of this concept goes beyond typical Industry 4.0 use cases, such as predictive maintenance. Recent efforts explore how digital twins can increase the security of CPSs.
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by Markus Tauber (FH Burgenland) and Christoph Schmittner (AIT)
The digital twin of a system should contain not only the existing information but also an up-to-date picture of the current status. While this is easy with physical properties, which can be measured by sensors, it is more challenging to measure and to provide an up-to-date picture of properties like security and safety. We have investigated the modelling of such dependencies in use cases related to transparency as well as to self-adaptability. Based on our experience we propose further extensions of domains like reliability. This also has the potential to provide legal support to Industry 4.0 use cases when required.
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by Violeta Damjanovic-Behrendt (Salzburg Research)
We have designed a digital twin prototype for detecting security, privacy and safety critical issues for the smart automotive sector, based on work done in the ongoing IoT4CPS project (Trustworthy IoT for cyber-physical Systems.
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by Matthias Jarke (Fraunhofer, FIT and RWTH Aachen), Günther Schuh, Christian Brecher, Matthias Brockmann and Jan-Philipp Prote, (RWTH Aachen and Fraunhofer IPT)
Due to highly sophisticated, specialised models and data in production, digital twins, as defined as full digital representations, are neither computationally feasible nor useful. The complementary concept of digital shadows will provide cross-domain data access in real time by combining reduced engineering models and production data analytics.
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by Thomas Usländer (Fraunhofer IOSB)
Representing real world objects as digital models has been a central topic of computer science for many years. However, in order to reduce the complexity and owing to the memory and processing limitations of IT devices, the digital models have always been quite tightly focused. Digital Twins (DT) are about to change this. The DT concept conveys the idea that digital representations should possess many of the essential properties of their real-world counterparts along their whole lifetime and even before and beyond. We propose an engineering methodology that allows an engineer to systematically motivate and derive these properties from use cases, and to deploy a DT as an interacting component in IIoT platforms.
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by Jacopo Parri, Samuele Sampietro and Enrico Vicario (University of Florence)
The JARVIS project (Just-in-time ARtificial Intelligence for the eValuation of Industrial Signals) exploits a domain logic of digital twins to connect the IoT layer with enterprise scale components in a Lambda architecture for Industry 4.0.
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by Olaf Sauer (Fraunhofer IOSB)
Together with colleagues from the Fraunhofer Industrie 4.0-community Fraunhofer IOSB is working on a definition of digital twins and on use cases that show their benefits. A Fraunhofer whitepaper is under work, where we take into account various aspects of digital twins such as material science, product development, manufacturing process development, digital factories, manufacturing operations and reference architectures. In this paper we describe some general aspects of digital twins and illustrate the concept with some examples from companies that have been early to adopt the concepts of digital twins.
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by Tamás Cserteg, Gábor Erdős and Gergely Horváth (MTA SZTAKI)
Multiple, linked research projects on the topic of human-robot collaboration have been carried out in MTA Sztaki with the aim of developing ergonomic, gesture driven, robot control methods. Although robots are already used in many different fields, the next generation of robots will need to work in shared workplaces with human operators complementing and not substituting their work. The implementation of such shared workplaces raises new problems, such as security of the human operator and defining simple and unambiguous communication interface between the human operator and the robot. To overcome these problems a detailed, up-to-date model, i.e., a digital twin, has been created.
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by Bruno Levy (Inria)
Research teams at Inria and University Paris Sud are elaborating new mathematical methods to simulate the physics of fluids. This has the potential to improve a crucial component of digital twin technology.
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by Ludovic Hoyet (Inria)
In years to come, the development of new immersive media (including digitalisation of industries) will lead to a massive spread of avatars, the users’ representation in the virtual world. By leveraging the complementary expertise of six Inria teams, the project “Avatar” aims to design the next generation of avatars for digital worlds in order to reach new levels of user embodiment in and through their virtual replica.
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by Sebastian Haag and Reiner Anderl (Technische Universität Darmstadt)
Digital twins enable the analysis of systems under real world conditions using multiphysics models, sensors and bidirectional data connections between the digital and its physical twin. At the research lab of the Department of Computer Integrated Design (DiK) of Technische Universität Darmstadt, a digital twin demonstrator was developed that enables a real-time motion-structural simulation of a bending beam test bench. The approach provides proof of many of the publicised benefits through a comprehensible digital twin system.
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by Stéphane P.A. Bordas, Sundararajan Natarajan, and Andreas Zilian (University of Luxembourg)
To work with digital twins, researchers must have the skills to select and adapt mathematical models to data as it is being acquired. Luxembourg’s National Research Fund (FNR) finances the first pan-Luxembourg Doctoral Training Centre in Data-DRIVEN Modelling and Discovery [L1], bridging artificial intelligence with modelling from first principles. The Centre will train the next generation researchers at the interface between computational and data science and application areas ranging from social inequalities to neurodegenerative diseases, through psychology and the science of science. These researchers will lay the foundations enabling digital twinning in a variety of application areas.
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by Erik Peeters (TNO ICT Unit)
High-tech equipment companies increasingly use simulations and models to predict the planned requirements of the machines they build. This “digital twin” provides major benefits to the industrial sector, but it seems that model calculations are rarely compared to the end product. The consequence is that development processes and product maintenance are inadequate and that upgrades don’t benefit from existing models. The Netherlands Organisation for Applied Scientific Research (TNO)’s Industry 4.0 ambitions support organisations with effective use of models and virtual representations of physical systems to understand, predict, optimise and upgrade their systems and systems behaviour in the field.