Living Lab #6: Data driven production process control
Data driven production process control
Processes in the poultry industry can be optimized to minimize food loss. This is being tested in this Living Lab by implementing portable Near Infrared Spectroscopy (NIR) technology and intelligent data analysis.
Recent studies have shown the digitalisation status of food processing within SMEs is closer to Industry 2.0 than the targeted 5.0.
Nowadays, the calculation of food losses is really qualitative, due the lack of data available at the required level. The main barrier observed for calculating accurately, is the absence of adequate (data-driven) monitoring and control measures in food SMEs.
There are several reasons for this:
- Continuous control of food products is difficult as well as time and resource consuming. The current main practice is the analysis of food in the lab, one by one, through a method partly destroying the observed object (destructive).
Conversion happening during food processing (heating, cooling, drying, etc.) is not fully understood at a micro-level and the interdependencies between varying raw material quality, process settings and end product quality are more or less a “black box” from a digital model perspective.
‘Legacy machines’ are common in the food industry and they complicate the digitalisation process further.
Interoperability and integration of current IT systems is generally difficult as they belong to different brands.
Better IT systems provide better control
- A chemometric model based on portable NIR technology (Near Infrared Spectroscopy) for the characterization of raw material.
- A NIR chemometric model for the non-destructive analysis of final product.
- An intelligent data analysis tool for the monitoring and optimisation of a key intermediate step.