Perfect Quality
Process Optimization
Reduce variability, eliminate losses, and improve operational flexibility
Ideal for Manufacturers
Stabilize and improve quality performance with less experienced operating teams.

Achieve Significant Value
          25% - 50%
        
        
          CpK Improvement
        
      
          1% - 3%
        
        
          Material Loss Reduction
        
      Automation
 
              Model for Startup and 
 In-Run ideal conditions
 
              Identification of non-conformance 
 to quality standards
 
              Alerts for unfavorable 
 run-to-run trends
 
              Autonomous recommendations 
 to optimize quality
 
              Identification of quality 
 anomalies and drivers
 
              Models auto-personalized 
 by product / SKU
How Colgate Optimized Quality
“The goal was to convert out of the black book and into prescribed startup conditions based on the algorithms within the Digital Twin.”
— Darren Haverkamp - Technical Director, Colgate
 
     
    