Resilience learning through self adaptation in digital twins of human-cyber-physical systems

Digital twins (DT) are emerging as an extremely promising paradigm for run-time modelling and performability prediction of cyber-physical systems (CPS) in various domains. Although several different definitions and industrial applications of DT exist, ranging from purely visual three-dimensional models to predictive maintenance tools, in this paper, we focus on data-driven evaluation and prediction of critical dependability attributes such as safety. To that end, we introduce a conceptual framework based on autonomic systems to host DT run-time models based on a structured and systematic approach. We argue that the convergence between DT and self-adaptation is the key to building smarter, resilient and trustworthy CPS that can self-monitor, self-diagnose and—ultimately—self-heal. The conceptual framework eases dependability assessment, which is essential for the certification of autonomous CPS operating with artificial intelligence and machine learning in critical applications. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

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Using AutomationML and Graph-Based Design Languages for Automatic Generation of Digital Twins of Cyber-Physical Systems

Advances in Transdisciplinary Engineering - Transdisciplinary Engineering for Complex Socio-technical Systems – Real-life Applications ◽

10.3233/atde200070 ◽

2020 ◽

Author(s):

Nicolai Beisheim ◽

Markus Kiesel ◽

Markus Linde ◽

Tobias Ott

Keyword(s):

Development Process ◽

Cyber Physical Systems ◽

Production Equipment ◽

Manufacturing Processes ◽

Reference Architecture ◽

Physical Systems ◽

Cross Domain ◽

Digital Twins ◽

Process Simulations ◽

Design Languages

The interdisciplinary development of smart factories and cyber-physical systems CPS shows the weaknesses of classical development methods. For example, the communication of the interdisciplinary participants in the development process of CPS is difficult due to a lack of cross-domain language comprehension. At the same time, the functional complexity of the systems to be developed increases and they act operationally as independent CPSs. And it is not only the product that needs to be developed, but also the manufacturing processes are complex. The use of graph-based design languages offers a technical solution to these challenges. The UML-based structures offer a cross-domain language understanding for all those involved in the interdisciplinary development process. Simulations are required for the rapid and successful development of new products. Depending on the functional scope, graphical simulations of the production equipment are used to simulate the manufacturing processes as a digital factory or a virtual commissioning simulation. Due to the high number of functional changes during the development process, it makes sense to automatically generate the simulation modelling as digital twins of the products or means of production from the graph-based design languages. The paper describes how digital twins are automatically generated using AutomationML according to the Reference Architecture Model Industry 4.0 (RAMI 4.0) or the Industrial Internet Reference Architecture (IIRA).

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