Despite the proclaimed benefits (i.e. scalability, reliability, cost-effectiveness) of Future Internet (FI) technologies (i.e. edge & cloud computing, IoT/CPS) for factory automation, their adoption from manufacturers remains low for various reasons, including technology issues (e.g., poor situation awareness, limited deployments, no standards-based reference implementations) and the lack of a smooth migration path from legacy systems. FAR-EDGE is a joint effort of leading experts in manufacturing, industrial automation and FI technologies towards the smooth and wider adoption of virtualized factory automation solutions based on FI technologies. It will research a novel factory automation platform based on edge computing architectures and IoT/CPS technologies. FAR-EDGE will provide a reference implementation of emerging standards-based solutions for industrial automation (RAMI 4.0, Industrial Internet Consortium reference architecture), along with simulation services for validating automation architectures and production scheduling scenarios. FAR-EDGE will lower the barriers for manufacturers to move towards Industrie 4.0, as a means of facilitating mass-customization and reshoring. Emphasis will be paid in the study of migration options from legacy centralized architectures, to emerging FAR-EDGE based ones. FAR-EDGE will be validated in real-life plants (VOLVO, WHIRLPOOL) in the scope of user-driven scenarios (business-cases) for mass-customization and reshoring, where tangible improvements relating to reliability, productivity increase, quality cost, reduction in adaptation effort/costs will be measured and evaluated. Also, a wide range of migration scenarios will be evaluated in the scope of a CPS manufacturing testbed. FAR-EDGE will also establish a unique ecosystem for FI factory automation solutions, which will bring together the FoF and FI communities (e.g., EFFRA, Industrie 4.0, AIOTI, ARTEMIS JU) and will ensure sustainability of FAR-EDGE results.

Individualised production is an emerging trend in manufacturing. Laser-based Additive Manufacturing (LBAM) fits well with this trend, due to its capability of transforming digital designs directly into physical products. LBAM is not yet competitive for a widespread industrial adoption: post-processing operations are necessary and they are not currently integrated, human intervention is needed to overcome technology gaps, and a poor integration with production planning systems hinders process traceability and resource optimisation. HyProCell proposes the combination of available cutting-edge LBAM machines and ICT innovations within an integrated multiprocess production cell, which will include at least LBAM and subtractive manufacturing machine/s, in order to ensure a fully finished product from the incoming raw material. The general objective of HyProCell is to implement and validate this concept in real settings, manufacturing real parts and measuring obtained benefits. HyProCell is expected to produce a sound impact on all the stakeholders of LBAM-related industry: - Making feasible a demand-driven LBAM production process supported on fast manufacturing procedure development capacities; - Creating highly automated and integrated multiprocess production cells, thus reducing dramatically downtime. - Enabling the rapid reconfiguration of the production cells, for scalability and/or new product demands, thanks to their modular architecture. - Fully enabling end-users to address new production trends. Relevant technological impacts are expected on hardware and software levels. A well-balanced consortium representing from machine manufacturers and end-users to Photonics experts, industrial automation specialist, ICT for smart manufacturing providers and technical services assures to meet project goals. Heavy involvement of SMEs (50% of the budget) guarantees an outstanding innovation push.

HyperCOG project “HYPERCONNECTED ARCHITECTURE FOR HIGH COGNITIVE PRODUCTION PLANTS” addresses the full digital transformation of the process industry and cognitive process production plants through an innovative Industrial Cyber-Physical System (ICPS). It is based on commercially available advanced technologies, that will enable the development of a hyper-connected network of digital nodes. The nodes can catch outstanding streams of data in real-time, which together with the high computing capabilities available nowadays, provide sensing, knowledge and cognitive reasoning to the industrial business. Furthermore, HyperCOG is deeply grounded in the last advances in Artificial Intelligence such as modelling for twin factories, decision-support systems for human-machine interaction and augmented reality for industrial processes visualization. It pursues self-learning from the process in order to deal with the typical dynamic fluctuations of the industrial processes and global optimization. The objective is to increase the production performance while reducing the environmental impact by reducing the energy consumption and the CO2 emissions thereof. Society will get profit of this project not only throughout the environmental impact, but through the lifelong learning of workers and vocational training for digitisation, and the available training modules for youth at schools such as ESTIA technological institute or U-PEC University. The breaking-edge system proposed in HyperCOG project will be validated on the productivity and environmental impacts, replicability and usability aspects on three use cases belonging to the SPIRE scope such us SIDENOR (steel making), CIMSA (cement), and SOLVAY (chemical) use cases.