January 2023
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59 Reads
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4 Citations
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January 2023
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59 Reads
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4 Citations
November 2021
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976 Reads
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86 Citations
IEEE Software
Digital Twins are an emerging concept which is gaining importance in several fields. It refers to a comprehensive software representation of an actual system, which includes structures, properties, conditions, behaviours, history and possible futures of that system through models and data to be continuously synchronized. Digital Twins can be built for different purposes, such as for the design, development, analysis, simulation, and operations of non-digital systems in order to understand, monitor, and/or optimize the actual system. To realize Digital Twins, data and models originated from diverse engineering disciplines have to be integrated, synchronized, and managed to leverage the benefits provided by software (digital) technologies. However, properly arranging the different models, data sources, and their relations to engineer Digital Twins is challenging. We, therefore, propose a conceptual modeling framework for Digital Twins that captures the combined usage of heterogeneous models and their respective evolving data for the twin’s entire life-cycle.
October 2021
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12 Reads
October 2020
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206 Reads
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77 Citations
Communications in Computer and Information Science
Digital Twins have emerged since the beginning of this millennium to better support the management of systems based on (real-time) data collected in different parts of the operating systems. Digital Twins have been successfully used in many application domains, and thus, are considered as an important aspect of Model-Based Systems Engineering (MBSE). However, their development, maintenance, and evolution still face major challenges, in particular: (i) the management of heterogeneous models from different disciplines, (ii) the bi-directional synchronization of digital twins and the actual systems, and (iii) the support for collaborative development throughout the complete life-cycle. In the last decades, the Model-Driven Engineering (MDE) community has investigated these challenges in the context of software systems. Now the question arises, which results may be applicable for digital twin engineering as well.
... In [46] we have coined the term Deep Software Variability to refer to the interaction of all external layers modifying the behavior or non-functional properties of a software. Deep software variability challenges practitioners and researchers: the combinatorial explosion of the epistemic and aleatory variability causes complicates the understanding, and thus the design, the configuration, the maintenance, the debug, and the test of software systems [40]. ...
January 2023
... Implementing a Digital Twin infrastructure is a non-trivial task [19,26]. Despite the emergence of various implementations from both research and practical applications [17,26], no single solution can be considered a silver bullet for implementing a full-fledged Digital Twin [19]. A Digital Twin environment typically includes a collection of interconnected models and data that replicate a realworld system [19]. ...
November 2021
IEEE Software
... The interaction between DPT and DT is one of these challenges to generate comprehensive monitoring within a company to optimize performance and sustainability. Moreover, there is a lack of a flexible framework as a central hub for collecting and processing sustainability data in a unified manner (Bordeleau et al., 2020). DT technology can support sustainability management in the PLC and already integrates sustainability assessment aspects. ...
October 2020
Communications in Computer and Information Science