#6 DATADRIVEN PRODUCTION PROCESS CONTROL

Living Lab #6: Datadriven production process control

Datadriven production process control

Processes in the poultry industry can be optimized to minimize food losses. 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 digitalization 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.Several reasons are behind this barrier, these are:

  • Continuous control of food products is difficult as well as time and resource consuming. Current main practice is the analysis of food in the lab, one by one, through a destructive method (a method partly destroying the observed object)

  • 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 difficult additionally the digitalization process
     
  • Interoperability and integration of current IT systems, are generally difficult, often as they belong to different brands

 

 

Better IT systems provide better control

Our proposal within this Living Lab is the development of an advanced IT system for the control and optimization of the productive process linked to breaded chicken products. This integral IT tool will merge three main modules:
  • A chemometric model based on portable NIR technology (Near Infrared Spectroscopy) for the characterization of raw material.
     
  • In a similar way, a NIR chemometric model for the non-destructive analysis of final product.
     
  • An intelligent data analysis tool for the monitoring and optimization of a key intermediate step.
All three components will be integrated in a way that will optimize the reduction of the current food losses generated in the target process.

 

Partners & objective

ASINCAR, Food Technology Centre, Aldelís (a large Enterprise producing poultry processed products).
 
The main objective of this Living Lab is to validate all three IT developed tools in the production facilities provided by Aldelís, proving the upscaling of TRL levels for proposed solutions, starting from TRL5 to a final TRL7.

 

Who will benefit? 

Main benefit will be for Food processing companies. They will get a relevant reduction of current food losses. Key associated KPI were described above. Other positive impacts are expected from this implementation as the reduction of other inputs, as raw material, ingredients or energy, or the diminution of operators for the supervision of the line.
 
We expect the first results for month 24, after the first implementation round

Contact

Roberto Morán
ASINCAR
Spain

robertomr@asincar.com

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