August 2015: SMD have now completed their first deliverable for the VAMOS (Viable Alternative Mine Operating System) project, finalizing the system architecture on schedule. The consortium made up of 17 project partners, is now progressing to deliver a number of spec documents as well as a project manual.
VAMOS is a 42-month Research & Development Project, which was launched in March this year as part of the Horizon 2020 programme. At an estimated cost of approximately 12.6 milllion Euros, the project will help to provide an opportunity to tap into the wealth of unexploited European mineral resources.
The VAMOS Project team are working towards the design and build of a robotic, underwater mining prototype and associated launch and recovery equipment, which will be used to perform field tests at four EU minesites. Three of these are inland inactive submerged mineral deposits and the other is offshore. The prototype will build on successful deep-sea excavation techniques provide a safer and cleaner option for extracting currently unreachable and/or uneconomic mineral deposits.
SMD are acting as Technical Manager and Work-Package Leader for design/build and site testing, with manufacture of the prototype to take place at SMD’s production site in Wallsend, North East England.
The consortium, with members from nine EU countries, is working under the coordination of BMT Group Ltd. and includes Damen Shipyards Group; Instituto de Engenharia Sistemas e Computadores; Fugro EMU Limited; Zentrum für Telematik e.V.; Montanuniversität Leoben; Minerália, Lda; Marine Minerals Ltd; Empresa de Desenvolvimento Mineiro SA; Sandvik Mining and Construction G.m.b.H; Geological survey of Slovenia; La Palma Research Centre for Future Studies; European Federation of Geologists; Trelleborg Ede Bv; Federalni zavod za Geologijo and Fondacija za obnovu I razvoj regije Vareš.
VAMOS will also look to enhance currently available underwater sensing, spatial awareness, navigational and positioning technology, as well as providing an intergrated solution for efficient real-time monitoring of the parameters associated with potential environmental impacts.
