FANVIS

Project "FANVIS" data sheet

The following table provides information about the project.

 Partnership

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Map

 Project objective

Technology and design improvements in Night Vision Imaging Systems (NVIS) have led to important price reductions in these equipment, so their use is growing in the civil segments, such as commercial aviation, law enforcement agencies, guard coasts, emergency medical services, forestry services, wildlife observers, etc. All illuminated panels within the cockpit in land/sea/air vehicles must integrate NVIS-compatible filters to enable the use of Night Vision Goggles (NVG). Filters’ suppliers are currently scarce and impose their unilateral selling conditions to manufacturers, integrators, adaptors and retrofitters of NVIS equipment. These suppliers come from outside EU market (mainly USA and Japan), so European industry is completely dependent on them as any change in trade regulations would have a negative impact, leading to stock disruption and costs increases. GRABISUR is a European leader in the design and manufacture of Human Machine Interfaces (HMI) systems in aviation, naval and land vehicle industries. The FANVIS project is the result of an R&D project, which has developed a cost-effective NVIS-compatible Green-A type absorptive filter (TRL6 prototype) that outperforms the technical features of current solutions. The FANVIS filters will be internationally patented and will allow the non-dependence on external suppliers, strengthening European industry. Our filters are suitable for aircrafts, vehicles, ships, simulators and, to a lesser extent, other civil equipment (personal equipment, radios, laptops, etc.). Our main target customers are Original Equipment Manufacturers (OEMs), platform manufacturers and organizations performing NVIS upgrading/repairing. Just considering the civil helicopters’ segment, we have estimated a yearly Total Addressable Market of €7.7M. This project aims at analysing the technical, economic and commercial feasibility of this new product that, according to our preliminary data, presents a ROI of 1.9.