Objective """Workshop managers face daily the challenge to execute their production plans at the lowest product rejection rates and costs. Rejections can be due to multiple kinds of defects in the manufactured piece. Each kind of defect is co-related to the particular parameters of production and the surrounding environment that have converged during the manufacturing process of the defective piece. At modern workshops the number of converging parameters during production can range from several hundreds to thousands. In serial production, defects are more prevalent at the beginning of the production of each new reference, until all production parameters are correctly set-up, but it’s also frequent to suffer involuntary, environmental or unavoidable modifications of parameters that also cause defective production.The problem of defective production is particularly relevant the higher the value of the workpieces produced and the shorter the production series. The evolution of the industrial production worldwide, and specially in advanced economies like Europe, tend towards a higher customization of products, thus to shorter series of higher cost and value pieces, making the problem of defective production a increasingly relevant issue for the competitiveness of industry.VEIGALAN has developed WORKSHOP4.0 a tool based on big data and artificial intelligence technologies that forecasts in real time the optimum working conditions for production processes involving material melting or fluency. WORKSHOP4.0 is capable to forecast the optimum production parameters at the beginning of a new series and re-calculate the new optimum parameters when unexpected, even un-noticed, defect producing events happen.""" Fields of science natural sciencescomputer and information sciencesartificial intelligenceengineering and technologymechanical engineeringmanufacturing engineeringnatural sciencescomputer and information sciencesdata sciencebig datanatural scienceschemical sciencesinorganic chemistrypost-transition metalssocial scienceseconomics and businessbusiness and managementbusiness models Programme(s) H2020-EU.2.1.2. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies – Nanotechnologies Main Programme H2020-EU.2.3.1. - Mainstreaming SME support, especially through a dedicated instrument Topic(s) NMP-25-2015-1 - Accelerating the uptake of nanotechnologies, advanced materials or advanced manufacturing and processing technologies by SMEs Call for proposal H2020-SMEInst-2014-2015 See other projects for this call Sub call H2020-SMEINST-1-2015 Funding Scheme SME-1 - SME instrument phase 1 Coordinator VEIGALAN ESTUDIO 2010 Net EU contribution € 50 000,00 Address ASKATASUN ETORBIDEA 16 48200 DURANGO Spain See on map SME The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed. Yes Region Noreste País Vasco Bizkaia Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 71 429,00