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Agri-food

Our goal:
reduce your raw material losses and optimise your processes

Optimisation of feed formulation, reduction of overdoses, tailor-made tools for decision support, automatic sorting by artificial vision … Put digital tools at your service!

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The thorns in your side

  • excessive loss of raw materials
  • non-constant production
  • increase in musculoskeletal disorders (MSDs)
  • complex decision making
  • complicated quality control
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Your major challenges

  • reducing costs
  • saving on raw materials
  • facilitating maintenance
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What you will experience

  • sharing your challenges and your needs
  • collecting the “right” data without interrupting your activities
  • simulating your proocess thanks to modelling
  • using algorithms to optimise your process
  • taking advantage of a custom-developed tool
  • validating the gains made
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Our references

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Our jargon

  • applied mathematics, ergonomic interfaces,
  • artificial intelligence, decision-support tools,
  • industry 4.0, predictive maintenance,
  • process optimisation, big data,
  • Matlab, Python, R.

In practice

Meal preparation to the nearest gram!

In the agri-food industry, the weight displayed on the packaging must meet specific requirements (TU1, TU2, etc.) in accordance with the regulations

Machine learning thanks to neural networks

The principle of a neural network is to schematically reproduce the human brain and its way of associating items so as to automatise the process into a machine : it is commonly called artificial intelligence.