Current Trends in Digital Twin Development, Maintenance, and Operation: An Interview Study
June 16, 2023 Β· Declared Dead Β· π Journal of Software and Systems Modeling
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Authors
Hossain Muhammad Muctadir, David A. Manrique Negrin, Raghavendran Gunasekaran, Loek Cleophas, Mark van den Brand, Boudewijn R. Haverkort
arXiv ID
2306.10085
Category
cs.SE: Software Engineering
Citations
35
Venue
Journal of Software and Systems Modeling
Last Checked
4 months ago
Abstract
Digital twins (DT) are often defined as a pairing of a physical entity and a corresponding virtual entity (VE), mimicking certain aspects of the former depending on the use-case. In recent years, this concept has facilitated numerous use-cases ranging from design to validation and predictive maintenance of large and small high-tech systems. Various heterogeneous cross-domain models are essential for such systems and model-driven engineering plays a pivotal role in the design, development, and maintenance of these models. We believe models and model-driven engineering play a similarly crucial role in the context of a VE of a DT. Due to the rapidly growing popularity of DTs and their use in diverse domains and use-cases, the methodologies, tools, and practices for designing, developing, and maintaining the corresponding VEs differ vastly. To better understand these differences and similarities, we performed a semi-structured interview research with 19 professionals from industry and academia who are closely associated with different lifecycle stages of digital twins. In this paper, we present our analysis and findings from this study, which is based on seven research questions. In general, we identified an overall lack of uniformity in terms of the understanding of digital twins and used tools, techniques, and methodologies for the development and maintenance of the corresponding VEs. Furthermore, considering that digital twins are software intensive systems, we recognize a significant growth potential for adopting more software engineering practices, processes, and expertise in various stages of a digital twin's lifecycle.
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