Clawdite published in Procedia CIRP
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2 minute read
In the context of the Industry 4.0 approach, applications and solutions supporting monitoring, simulation, optimisation, and decision-making in production systems are exponentially growing.
Digital twins are the silver bullet for these solutions, given their capability of providing comprehensive digital representations of production systems, which are continuously updated by leveraging IIoT (Industrial Internet of Things) systems.
However, digital twins designed for Industry 4.0 applications are limited in representing human operators, which instead are a key component in the emerging Industry 5.0 paradigm.
Cognitive automation is spreading increasingly, and it becomes essential to have a digital representation of humans for improving their well-being and performance, but also to monitor and simulate their interactions with the factory.
A standardised solution for creating digital twins is currently missing. Industrial solution architects are forced to resort to ad-hoc implementations and models, which lack re-usability, scalability and extensibility. These limitations prevent a smooth introduction of a human digital representation in existing digital twins, so hindering the complete shift to the new Industry 5.0 paradigm.
The SPS Lab worked on a solution to bridge the existing gaps with current digital twins, by introducing Clawdite, an extensible and flexible IIoT-based platform for creating Human Digital Twins. Clawdite supports the creation of customised data representations of production systems, including machines, devices, and humans. Moreover, Clawdite has been designed to be modular, so that to ease the integration of new components (e.g., for simulations), the digital twin instantiation, and the system ramp-up.
Clawdite has been tested in different projects (STAR, SCOUT), showing its capability to fit different applications and laboratory settings. The resource is publicly available in GitLab.
Want to know more about Clawdite, its architecture and flexible data model? Checkout our paper! If you have any questions, contact us (project key people: Andrea Bettoni, Elias Montini).