VanRijsingen Green partnered with Cboost to optimize their decanter machine operations. The project focused on improving juice yield and fiber dryness while reducing energy consumption. The collaboration involved data collection, data analysis and iterative testing to establish the best way to adjust machine settings dynamically.  

Identified five critical machine settings that impact juice output through data analysis
Developed dynamic adjustment protocols for decanter operations based on real-time data
Established a framework for future AI automation implementation

The challenge

VanRijsingen Green wanted to optimize the performance of their decanter machine to simultaneously maximize juice extraction and minimize moisture in residual fibers, while being more energy efficient and reducing waste. 

The solution

  • First, Cboost visited the plants to map processes and assess data availability 
  • Three potential use cases were evaluated, after which the decanter optimization was prioritized based on a cost-benefit analysis 
  • Data analysis was conducted to identify optimal parameters contributing to the production process 
  • An AI solution and a continuous monitoring system were proposed to automate setting adjustments 

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