model-based digital twin of a heavy duty machinery

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Sähkötekniikan korkeakoulu | Master's thesis
Control, Robotics and Autonomous Systems
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AEE - Master’s Programme in Automation and Electrical Engineering (TS2013)
62 + 2
The industrial world is moving towards digitization since the mid twentieth century and the latest industrial evolution is called Industry 4.0. The advancing technologies like big data, industrial internet of things (IoT), cloud and cognitive computing, predictive analytics are the key enablers of Industry 4.0. One of such advancing technologies is digital twin which is considered to be the backbone of today’s industry. The conventional method of heavy duty machinery development is time consuming, costly and require a highly skilled and trained professional. Leveraging the digital twin solution in such cases helps in all the phases of a product lifecycle from the design phase to the maintenance phase and increase the productivity and efficiency of the product. Digital twin approach also advances the industry towards sustainable manufacturing by reducing the carbon footprint which is specially required for heavy duty machinery like Dolores, the test rig used for the research. The work done for the thesis covers the initial part of the process involved in developing the digital twin. This thesis develops a multibody dynamic based mechanical model of a heavy duty machinery present in the Mechanical laboratory of Aalto University. The behavior of the developed model is then compared to the real-time system. A digital twin must have a interface between the real-time system and the virtual system. The link between the physical real-time system and the virtual system is created via Simulink. In this thesis work, only the external interface between the virtual system and Simulink is developed, the external interface between the physical real-time system and Simulink is out of the scope. The results indicate that the developed model behaves as desired and closely follows the behavior of the physical real-time system. The external socket interface developed shows that the connection is robust and the data flow between the two software is accurate with no latency.
Pietola, Matti
Thesis advisor
Heikkinen, Jani
Minav, Tatiana
digital twin, multibody systems, real-time simulation, model-based system modeling
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