FEATURES
Predictive model capable of determining the optimal factory settings according to the analysis of historical production data.
IMPACT
Reduction of mill adjustment time and improvement of transformation performance.
ACHIEVEMENTS
Improvement of the factory production process by basing decision-making on objective data and advanced algorithm.
BUSINESS PROBLEM
The Norman project is transforming the milling industry, a key sector in the agri-food chain, thanks to the implementation of advanced technologies such as artificial intelligence. This initiative seeks to maximize efficiency, reduce environmental impact and ensure the quality of the final product.
DRIBIA’S SOLUTION
Led by the Digital Cluster of Catalonia and with the support of companies such as Farinera Coromina and AETECH, Norman applies predictive algorithms to optimize the process of transforming wheat into flour. Through models that connect the characteristics of the grain with the operational parameters, variables are adjusted in real time, ensuring optimal use of resources.
This technological innovation allows:
- Real-time optimization of the milling process, increasing production yield.
- Constant improvement of the quality of the final product through the automatic adjustment of variables
- Implementation of predictive maintenance systems that minimize downtime and reduce waste.
- Reduction of energy consumption, with savings in operational costs.
The impact of the Norman project, funded within the framework of the AEI 2024 call, extends beyond flour production. This initiative transforms not only the milling process but also the entire agri-food value chain, demonstrating the potential of technology to combine operational efficiency and respect for the environment.
