Digital Twin
The real system in our experiment comprises four production stations: Pick and place, assembly, muscle compressing and sorting. These modular stations are controlled by Siemens PLC. This is the data gathered from a real manufacturing system and its Digital Twin data when under the denial of service attacks.
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A CNC adapter was utilized together with the software established as part of the GRBL project to operate the CNC adapter, and two data sets were produced for the physical model in order to build the linear and circular motion models. The parameters for motion quantity, motion duration, and feed rate are in the data set.
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This dataset contains multimodal sensor data collected from side-channels while printing several types of objects on an Ultimaker 3 3D printer. Our related research paper titled "Sabotage Attack Detection for Additive Manufacturing Systems" can be found here: https://doi.org/10.1109/ACCESS.2020.2971947. In our work, we demonstrate that this sensor data can be used with machine learning algorithms to detect sabotage attacks on the 3D printer.
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The dataset corresponds the measurement that was implemented on the control accuracy of a mixed reality application for digital twin based crane.
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323 Views
This dataset contains requests execution times for comparison of direct requests and requests via API gateway to test API.
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408 Views
The Here East Digital Twin was a six month trial of a real-time 3D data visualisation platform, designed for the purpose of supporting operational management in the built environment.
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715 Views