During the stay, two main endeavours has taken place:
• Preliminarily testing of the proposed Digital twin reference architecture, to implement and validate it and to eventually refine eventual inconsistencies.
• Explore the adoption of Augmented Reality as a technology to put in place a Human-Machine Interaction mode within the proposed architecture.
To achieve the first goal of the project, a mobile training unit has been employed as starting point for the development of the case study. On top of the existing mobile training unit, a small-sized collaborative robot and a desktop 3D printer have been mounted. Thanks to this arrangement, I was able to design an exemplary work-cycle that foresee the 3D printer to produce a component, and the robot to detach it from the printing plate and extract it from the printing chamber. This cycle could be repeated as a continuous cycle. The proposed architecture previously developed in cooperation with Prof Chag-Tsun Li has been deployed here for the first time in its simplest form. It proved its validity in the efficient orchestration of tasks, and it proved its flexibility after the inclusion of an Augmented Reality application as an entity of the overall ecosystem.
The collaboration led to the composition of a manuscript reporting the work done, in view of the inclusion of human being in Digital Twin applications, with an eye on the upcoming Industry 5.0 era. The article has been presented by Prof. Emmanuel Francalanza in the context of the 17th CIRP Conference on Intelligent Computation in Manufacturing Engineering, entitled “A Digital Twin for SMEs in the Context of Industry 5.0”.
The work done in the context of this secondment supports the development of DT technology withing SMEs by replicating a first use case that involves the inclusion of DT-oriented solutions, to simplify the sharing of data among heterogenous systems of physical and virtual entities. This represent a first step in the direction of standardized DT technology to be seamlessly adopted by SMEs, as well as from large industrial settings.
