The ONE4ALL project is on track to reinforce the manufacturing industries' resiliency and flexibility, with a special focus on SMEs and labour-intensive manufacturing industries. ONE4ALL tackles the problem from multiple perspectives and is reflected in its technical and scientific advances:
1) The reconfigurable cyber-physical production module (RCPM) based on collaborative robotic technologies, as well as completed the development of the first operational prototype. The RCPM developed will perform several supportive activities within the manufacturing line. Furthermore, thanks to the interchangeable end-effector, it enables the handling of a variety of products and on-demand reconfiguration, quickly responding to rapid changes in production. Lastly, it can be accessed and controlled remotely thanks to the Intelligent Orchestration Platform modules.
2) Data-driven Digital Twins (DTs) + Distributed Decision Support Systems (DDSS). The data-driven DTs have been designed, prioritising a modular and reconfigurable architecture. The flexibility of those technologies enables their adaptation to a dynamic environment, as presented by the labour-intensive manufacturing sites of the demonstration sites. The DTs aim to simulate the production of the manufacturing lines considering multiple aspects (internal and external), in order to anticipate and forecast potential risks. Once identified, the DDSS come up with a strategy both at the management and operation level to mitigate it, taking advantage of the production recofngiruability and modularity reinforced through technologies such as the RCPM. Furthermore, the review also tackles the integration of those technologies with the DTs, identifying the current challenges and opportunities in the field. In the next stage of the project those challenges will be surpassed.
3) Intelligent Orchestration Platform (IOP). Significant advances have been made in designing and constructing the architecture of the IOP. At this stage, the IOP architecture has been built, and all that remains is to fill the slots with the ONE4ALL technologies to bring it to life. In particular, simply configuring the external-connector of the data fusion pipeline enables the connection of the IOP and all its modules to any other data sources, manufacturing MES or ERP systems, new production processes and digital modules.
4) AI-based vision system for collaborative robots. Significant advancements in AI-based vision systems for robots have been achieved during the first period of the project. An AI-based system, open-source in its entirety, has been developed within the WP3 activities and as part of the IOP processing layer. At this stage, the AI-based vision system enables the identification and positioning of different objects in space. The stable and operative version is currently trained with pharmaceutical products. Another version will be adapted for the agri-food sector. Furthermore, the MLOps methodology will enable fast reconfiguring for any product type. As a result, the advances in the AI-based vision system will imply significant progress in robotics.
5) Digital Maturity and Sustainability Assessment module (DMSA). One of the main objectives during this reporting period has been to identify the SMEs and industrial users' baseline understanding and their goals concerning the I5.0 transformation. Several surveys and interviews have been conducted at the demonstration sites. The survey results were analysed in terms of work safety, wellbeing and skills. Besides the results of the surveys, the main outcome in this regard is the preliminary version of the DMSA and its core tools. The DMSA aims to close the gap between SME industries and the I5.0 transformation.
