Improvements of the overall sustainability of process industries from an economic, environmental and social point of view require the adoption of a new industrial symbiosis paradigm - the human-mimetic symbiosis - where critical resources (materials, energy, waste and by-products) are coordinated among multiple autonomous Production Units organized in industrial clusters. SYMBIOPTIMA will improve European process industry efficiency levels by: (a) developing a cross-sectorial energy & resource management platform for intra- and inter-cluster streams, characterized by a holistic model for the definition, life-cycle assessment and business management of a human-mimetic symbiotic cluster. The platform multi-layer architecture integrates process optimization and demand response strategies for the synergetic optimization of energy and resources within the sectors and across value chains. (b) Developing extensive, multi-disciplinary, modular and “plug&play” monitoring and elaboration of all relevant information flows of the symbiotic cluster. (c) Integrating all thermal energy sources, flows and sinks of the cluster into a systemic unified vision, as nodes of smart thermal energy grid. (d) Taking into account disruptive increase of cross-sectorial re-use for particularly impacting waste streams, proposing advanced WASTE2RESOURCE initiatives for PET. The development of such a holistic framework will pave the way for future cross-sectorial interactions and potentialities. Furthermore, the adoption of available LCSA and interoperability standards will grant easy upgradability of legacy devices and a large adoption by device producers. Modularity, extendibility and upgradability of all developed tools will improve scalability and make the SYMBIOPTIMA approach suitable both at small and large scale. Rapid transfer from lab-scale to testing at demonstration sites will be eased by the presence of industrial partners and end-users, as Bilfinger, Siemens, SXS, and Neo Group.

Waste heat recovery systems can offer significant energy savings and substantial greenhouse gas emission reductions. The waste heat recovery market is projected to exceed €45,0 billion by 2018, but for this projection to materialise and for the European manufacturing and user industry to benefit from these developments, technological improvements and innovations should take place aimed at improving the energy efficiency of heat recovery equipment and reducing installed costs. The overall aim of the project is to develop and demonstrate technologies and processes for efficient and cost effective heat recovery from industrial facilities in the temperature range 70°C to 1000°C and the optimum integration of these technologies with the existing energy system or for over the fence export of recovered heat and generated electricity if appropriate. To achieve this challenging aim, and ensure wide application of the technologies and approaches developed, the project brings together a very strong consortium comprising of RTD providers, technology providers and more importantly large and SME users who will provide demonstration sites for the technologies. The project will focus on two-phase innovative heat transfer technologies (heat pipes-HP) for the recovery of heat from medium and low temperature sources and the use of this heat for; a) within the same facility or export over the fence; b) for generation of electrical power; or a combination of (a) and (b) depending on the needs. For power generation the project will develop and demonstrate at industrial sites the Trilateral Flash System (TFC) for low temperature waste heat sources, 70°C to 200°C and the Supercritical Carbon Dioxide System (sCO2) for temperatures above 200°C. It is projected that these technologies used alone or in combination with the HP technologies will lead to energy and GHG emission savings well in excess of 15% and attractive economic performance with payback periods of less than 3,0 years.

MAYA aims at developing simulation methodologies and multidisciplinary tools for the design, engineering and management of CPS-based (Cyber Physical Systems) Factories, in order to strategically support production-related activities during all the phases of the factory life-cycle, from the integrated design of the product-process- production system, through the optimization of the running factory, till the dismissal/reconfiguration phase. The concurrence and the cross-combination of the Cyber and the Physical dimensions with the Simulation domain is considered as cornerstone in MAYA innovations, to successfully address a new generation of smart factories for future industry responsiveness. MAYA finds complete validation in one of the most competitive, advanced and complex industrial sector in Europe, the automotive, where it will accomplish reduced time to production & reduced time to optimization within two use-cases (Volkswagen and FinnPower). In order to realize such a vision, MAYA addresses actual technological constraints through research and development activities focusing on the following three high level objectives: - MAYA for Digital Continuity; - MAYA for the Synchronization of the Digital and Real Factory; - MAYA for Multidisciplinary integrated simulation and modelling. MAYA’s concept and motivation have been born within the framework set by the Pathfinder initiative, and represent a concrete first step to empower the vision there drafted, and consolidated thanks to the contribution of several academic experts and industrial key-players (http://www.pathfinderproject.eu/contributors.asp).

Manufacturing and logistics companies are subject to unforeseen events that disrupt the supply chain, causing production slowdowns, reduced output, and increased costs, making it difficult to meet customer demand. To mitigate these risks, manufacturers must build resilience across entire value chains. NARRATE will develop a sophisticated tool using AI, Digital Twin, and IoT technologies allowing end-to-end visibility and control over supply chain operations to monitor and predict potential disruptions, enabling supply chains to achieve improved resilience. The Intelligent Manufacturing Custodian (IMC) will leverage data from various production sources to enable proactive decision-making and act as a nerve centre for a supply-chain network, providing real-time monitoring and coordination of intelligent production processes and logistics. Integrating an IMC into a supply-chain will evolve its operations into Smart Manufacturing Network (SMN): a connected and self-orchestrated ecosystem linked end-to-end with programmable Manufacturing-as-a-Service capabilities that can withstand disruptions. A Digital Twin will provide a reliable model to represent production and operational data of an SMN to unlock deeper IMC intelligence. Collected data will train machine learning models to predict potential disruptions, such as natural disasters or delayed shipments. AI algorithms will analyse the data and provide real-time reporting and visualization on a dashboard. The IMC and Digital Twin interaction will generate powerful insights and self-adapting abilities that support an SMN to evolve under human supervision by switching services between multiple external partners to respond to risks and disruptions and improve energy efficiency, product circularity and environmental sustainability across the entire production process. The effectiveness of NARRATE will be evaluated by testing the IMC in real production environments in quite diverse industry sectors.

Borealis project presents an advanced concept of machine for powder deposition additive manufacturing and ablation processes that integrates 5 AM technologies in a unique solution. The machine is characterized by a redundant structures constituted by a large portal and a small PKM enabling the covering of a large range of working cube and a pattern of ejective nozzles and hybrid laser source targeting a deposition rate of 2000cm3/h with 30 sec set-up times. The machine is enriched with a software infrastructure which enable a persistent monitoring and in line adaptation of the process with zero scraps along with number of energy and resource efficiency optimization policies and harvesting systems which make the proposed solution the less environmental invasive in the current market. Borealis idea results from a consortium composed by the excellence of developers of worldwide recognized laser machines and advanced material processing together with the highly precision and flexible mechatronic designers. These two big clusters decided to join their expertise and focus on new manufacturing challenges coming from complex product machining in the field of aerospace, medtech and automotive represented by major partners in the market. Borealis project targets a TRL 6 and will provide as outcome of three years work two complete Borealis machine in two dimensions – a lab scale machine and a full size machine – which are foreseen to be translated into industrial solution by 2019.