PERFoRM - Production harmonizEd Reconfiguration of Flexible Robots and Machinery aims to the conceptual transformation of existing Production Systems towards plug&produce production systems in order to achieve a flexible manufacturing environments based on rapid and seamless reconfiguration of machinery and robots as response to operational or business events. These objectives require research activities to implement a solid Manufacturing middleware based on encapsulation of production resources and assets according existing paradigms (e.g. CPS, Service based architectures, Cloud services, etc.), the development of advanced and modular global monitoring and optimization algorithms for reconfiguration of machinery, robots and processes and, finally, to ensure the full interoperability, the harmonization and standardization of methods and protocols to enable the plug-and-produce readiness in heterogeneous environments. On the other hand, real industrial and business impacts, can be achieved by careful consideration of migration of legacy environments to the new approach and, where standard devices and/or applications remain, the coexistence and integration of existing systems. Implementing a robust and consistent KPI based operational and performance measuring approach, to really drive the behavior of the system according to the business and operational objectives, will ensure the achievement of measurable results. To such purpose PERFoRM project will deploy in four industrial testbeds belonging to different industrial domains to ensure a broad and sound validation of the concept and the platform. A successful deployment will be achieved not only by focusing on migration planning and deployment, but will also encompass the deployment in at least two designated industry driven experimental testbeds to optimize the deployment strategy and so minimize risks.

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.

Current practice is such that a production system is designed and optimized to execute the exact same process over and over again. The planning and control of production systems has become increasingly complex regarding flexibility and productivity, as well as the decreasing predictability of processes. The full potential of open CPS has yet to be fully realized in the context of cognitive autonomous production systems. SMEs face additional challenges to the implementation of “cloudified” automation processes. While the building blocks for digital automation are available, it is up to the SMEs to align, connect and integrate them together to meet the needs of their individual advanced manufacturing processes. Moreover, SMEs face difficulties to make decisions on strategic automation investments that will boost their business strategy. AUTOWARE objective is to build three distinct pillars to form a multi-sided ecosystem. (1) From the BeinCPPS, leverage a reference architecture (fully aligned with CRYSTAL and EMC2 CPS design practices and ARROWHEAD cloudification approach) across I4MS competence domains (cloud,CPPS, robotics), acting as a glue that will attract potential users and developers to a friendly ecosystem for business development, more efficient service development over harmonized architectures (smart machine, cloudified control, cognitive planning- app-ized operation). (2) To leverage a number of SME enablers; e.g. augmented virtuality, reliable wireless communications, CPPS trusted auto-configuration, smart data distribution and cognitive planning to ease cognitive autonomous systems. Finally, to leverage digital automation investments. AUTOWARE brings together the best of breed ARTEMISIA/ECSEL platforms, I4MS innovation, SAFIR business platforms and neutral experimental sites (robotics & process). AUTOWARE assets will be evaluated in two industrial pilots, PWR and SCM, and will offer well established industry and start-ups new business opportunities.

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.