Modeling an Industrial Revolution: How to Manage Large-Scale, Complex IoT Ecosystems?

Advancements around the modern digital industry gave birth to a number of closely interrelated concepts: in the age of the Internet of Things (IoT), System of Systems (SoS), CyberPhysical Systems (CPS), Digital Twins and the fourth industrial revolution, everything revolves around the issue of designing wellunderstood, sound and secure complex systems while providing maximum flexibility, autonomy and dynamics. The aim of the paper is to present a concise overview of a comprehensive conceptual framework for integrated modeling and management of industrial IoT architectures, supported by actual evidence from the Arrowhead Tools project; in particular, we adopt a three-dimensional projection of our complex engineering space, from modeling the engineering process to SoS design and deployment. In particular, we start from modeling principles of the the engineering process itself. Then, we present a design-time SoS representation along with a toolchain concept aiding SoS design and deployment. This brings us to reasoning about what potential workflows are thinkable for specifying comprehensive toolchains along with their data exchange interfaces. We also discuss the potential of aligning our vision with RAMI4.0, as well as the utilization perspectives for real-life engineering use-cases.

[1]  Andrew Y. C. Nee,et al.  Digital Twins and Cyber–Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison , 2019, Engineering.

[2]  Fei Tao,et al.  Make more digital twins , 2019, Nature.

[3]  Géza Kulcsár,et al.  Toolchain Modeling: Comprehensive Engineering Plans for Industry 4.0 , 2020, IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society.

[4]  Pál Varga,et al.  From Models to Management and Back: Towards a System-of-Systems Engineering Toolchain , 2020, NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium.

[5]  Jerker Delsing,et al.  The Arrowhead Framework architecture , 2017 .

[6]  Felix Larrinaga,et al.  Dynamic Multilevel Workflow Management Concept for Industrial IoT Systems , 2021, IEEE Transactions on Automation Science and Engineering.

[7]  Enrico Macii,et al.  An Engineering Process model for managing a digitalised life-cycle of products in the Industry 4.0 , 2020, NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium.

[8]  Patrice Micouin.  Model Based Systems Engineering: Fundamentals and Methods , 2014 .

[9]  Azad M. Madni,et al.  Leveraging Digital Twin Technology in Model-Based Systems Engineering , 2019, Syst..

[10]  Dániel Kozma,et al.  Supporting Digital Production, Product Lifecycle and Supply Chain Management in Industry 4.0 by the Arrowhead Framework – a Survey , 2019, 2019 IEEE 17th International Conference on Industrial Informatics (INDIN).

[11]  Sandro Wartzack,et al.  Shaping the digital twin for design and production engineering , 2017 .

[12]  C.J.H. Mann,et al.  A Practical Guide to SysML: The Systems Modeling Language , 2009 .