Optimal food production based on Big Data

The industry is still largely based on tradition and craftsmanship. Skilled professionals often judge raw material quality manually, and processes are controlled by experience and intuition. These are valuable skills, but the industry needs to move towards more objective and modern processing practices. There is a need for digitalization of the food industry, including on-line measurement technology, data acquisition and analysis, and automated process control.

Most food companies collect and store big amounts of data through the production process, but currently these data are not exploited fully. OPTIMAT will use Big Data Analytics to identify important relationships between raw material quality, processing and end-product quality. This will provide new knowledge about the process, and enable a shift from end-product control to continuous measurement of raw materials and intermediate products. Based on new knowledge and data, we can design a control system that automatically adjusts the process towards an optimal quality.

This is, however, not a trivial task for the food industry. Raw material quality is often not clearly defined, and it is not always known which parameters that are important and how they should be measured. Analysis of such complex systems require tailored and robust statistical methodology, and interdisciplinary expertise to understand how data and models can be used to control the process. The three Norwegian research institute Nofima, Tel-Tek and SINTEF have expertise in data analysis, food chemistry, measurement systems and process control. OPTIMAT will modernize the food companies’ production and demonstrate to the rest of the industry the great potential of Big Data Analytics.