USE CASES
Improve the laser process quality and productivity
Developing a closed-loop system including AI based on machine learning
Increase productivity by 35% in 3 years (expectations)
Improve quality
Identifying root causes of variation thanks to operators participation
Better management of product quality
Optimize energy consumption
Identifying root causes of variations thanks to operators participation
500 000 €/year savings
Process efficiency optimization
Improve production quality and process efficiency
Finding the optimal presetting for the new plate leveler
Reduce variability in energy and performance
Schneider Electric APS USING DATAMAESTRO ANALYTICS
Savings of 142 000 € / year
Improve production energy and maintenance efficiency
Advanced Analytics to understand variability root causes
Savings > 56 000 € per year
