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Automated real-time production forecasting for industry

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.""
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Field of science

  • /social sciences/economics and business/economics/production economics
  • /natural sciences/computer and information sciences/artificial intelligence
  • /social sciences/economics and business/business and management/business model
  • /natural sciences/computer and information sciences/data science/big data
  • /social sciences/economics and business/business and management/commerce
  • /natural sciences/chemical sciences/inorganic chemistry/inorganic compounds

Call for proposal

H2020-SMEINST-1-2015
See other projects for this call

Funding Scheme

SME-1 - SME instrument phase 1

Coordinator

VEIGALAN ESTUDIO 2010
Address
Askatasun Etorbidea 16
48200 Durango
Spain
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
EU contribution
€ 50 000