Ziel
Due to the manufacturing process and the special requirements in the aerospace industry for the parts produced, usually there are some parameters out of tolerance, defects produced on the handling or transportation of the parts. These defects are highly common, leading a high percentage of discarded parts, i.e 5 - 10% of the total produced parts, or repair processes - between 10 to 20% of the parts have non-conformities - that are time and cost consuming. Similar situation occurs with in-services airplanes, where maintenance is a crucial activity and the ground time is highly important factor for the viability of the airline.
Reducing the percentage of scrapped parts, the non-conformities solving time on the manufacturing or reducing the on-the-ground time for airline fleets becomes one of the main objectives of the engineering support teams. The average cost of per unit of non-conformity, considering an average lead-time of 6 days, will be 1.140€. It is estimated that the annual management cost for one of these non-conformities is around 350 million € per year in Europe.
ZinkCloud, through its ZinkOn product, provides a solution (based on Artificial Intelligence and other cutting edge technologies) to eliminate the bottleneck processes related to the engineering tasks, addressing especially the non-conformities, and providing recommendations on how to repair some defects based on previous experiences, applicable documentation and regulations. Our product, validated as beta version in Spain by Airbus and other relevant players in the aerospace industry, is revolutionizing the way of managing nonconformities.
ZinkOn is becoming a breakthrough innovation with potential to change the associated costs and managing times of these unavoidable manufacturing defects, in line with strategic objectives in the industry regarding a reduction on the production costs . We foresee an important growth: 40 new jobs and over 4,2M€ turnover by 2020.
Wissenschaftliches Gebiet
- natural sciencescomputer and information sciencesartificial intelligence
- engineering and technologymechanical engineeringmanufacturing engineering
- natural sciencescomputer and information sciencessoftware
- natural sciencescomputer and information sciencesdata sciencebig data
- social scienceseconomics and businessbusiness and managementbusiness models
Programm/Programme
Aufforderung zur Vorschlagseinreichung
Andere Projekte für diesen Aufruf anzeigenUnterauftrag
H2020-SMEINST-1-2015
Finanzierungsplan
SME-1 - SME instrument phase 1Koordinator
28223 POZUELO DE ALARCON MADRID
Spanien
Die Organisation definierte sich zum Zeitpunkt der Unterzeichnung der Finanzhilfevereinbarung selbst als KMU (Kleine und mittlere Unternehmen).