EFFRA recommendations on Factories 4.0 and Beyond (Sept 2016) clearly stated the need for development of large scale experimentation and demonstration of data-driven “connected smart” Factories 4.0, to retain European manufacturing competitiveness. BOOST 4.0 will address this need, by demonstrating in a measurable and replicable way, an open standardised and transformative shared data-driven Factory 4.0 model through 10 lighthouse factories. BOOST 4.0 will also demonstrate how European industry can build unique strategies and competitive advantages through big data across all phases of product and process lifecycle (engineering, planning, operation, production and after-market services) building upon the connected smart Factory 4.0 model to meet the Industry 4.0 challenges (lot size one distributed manufacturing, operation of zero defect processes & products, zero break down sustainable operations, agile customer-driven manufacturing value network management and human centred manufacturing). Our chief objectives include: (1) Establish 10 big data lighthouse smart connected factories (VW, FILL, AutoEuropa, +GF+, FIAT, Phillips, Volvo, GESTAMP, Benteler, Whirlpool). (2) Provide the RAMI 4.0 and IDS based BOOST 4.0 open EU framework and governance model, for both services and data assets. (3) Put together methodologies, assets, models and communities in order to maximise visibility, mobilization, replication potential, and impact (business, financial, standardization) of BOOST 4.0 The investment leveraging factor of BOOST 4.0 will be well above the 4:1 ratio, up to 10:1. In terms of exploitation, in 5-years horizon after the project end, just only the participating lighthouse factories will make a direct follow-on investment above 33Meuro (ROI 10,61), while the commercialisation of the BOOST 4.0 products in the market is expected to generate some 96Meuro cumulative profits (ROI 4,73) for the rest of the partners.

SimInSitu is aiming to develop a sophisticated in-silico method to predict the short- and long-term behavior of in-situ tissue engineered heart valves by combing advanced tissue remodeling algorithms with a personalized virtual heart modelling approach. The method will be specifically developed to predict the complex transformation process of biodegradable heart valves from the initially synthetic scaffold into a fully remodeled & functional valve. This transformation process, named ETR for Endogenous Tissue Restoration, is the core technology for a new generation of very promising biodegradable vascular device currently developed by Xeltis. ETR makes the use of animal derived tissue, which is used in the majority of commercially available bioprosthetic heart valves, obsolete and avoids thereby durability related issues and potentially minimized the need for reoperations. Though, significant progress was made during the past years in developing ERT based devices, it remains very challenging, costly, time-consuming, and rich with obstacles. New knowledge can only be generated through a tedious trial & error process (requiring preclinical and clinical studies), since the restorative process cannot be replicated in an in-vitro environment. Advanced Computer Modelling & Simulation technologies have the potential to overcome this limitation by allowing to test new designs, modified scaffold compositions, or other applications in a virtual patient-specific environment – in-silico. SimInSitu will not only develop such a computer model, but will also verify and validate it thoroughly by making use of the extensive in-vitro and in-vivo data available and where necessary will generate new data to support the credibility of this in-silico method. The availability of this computer model could contribute significantly to an acceleration of especially the ETR-device development and accelerate their translation into the clinic and market.