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.
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Achieve Significant Value
25% - 50%
CpK Improvement
1% - 3%
Material Loss Reduction
Automation
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Model for Startup and
In-Run ideal conditions
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Identification of non-conformance
to quality standards
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Alerts for unfavorable
run-to-run trends
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Autonomous recommendations
to optimize quality
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Identification of quality
anomalies and drivers
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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