Objective:

To develop an intelligent process control strategy for a twin screw  cooking extruder to deliver high quality processed food with optimum utilization of resources.

• An intelligent process control algorithm based on a Neural Network approach using CAFT’s previously developed extrusion process simulations and selected on-line sensors;
  
  
• Transfer functions relating extruder operating conditions and die geometry to product characteristics using numerical simulation;
  
  
• A sampling system to measure ingredient moisture using CAFT’s patented thermomoisture sensing system;
  
  
• Adaptation of CAFT’s helical barrel rheometer to measure viscosity of the extruder melt before the die;
  
  
• A flavor sensor to measure pyrazines in gaseous and solid phases at the extruder die.