Process Energy Optimization AI
Xylo-Saver
Overview
Xylo-Saver is an optimization AI solution that analyzes energy inefficiency by equipment and process.
It connects PLC, MES, power, and production data to estimate energy use patterns and identify areas for improvement.
Field challenges
Total plant electricity use does not identify losses in individual equipment or processes. Teams need a basis for prioritizing improvements before setting savings targets.
How it works
We organize equipment tags and operating data, then connect PLC, MES, power, and production sources. The system estimates use by operating state, visualizes process-level consumption, and identifies inefficient segments and savings priorities.
- Signals
- PLC, MES, power use, equipment operation, sensors, and process production data
- Deployment
- Data integration with equipment/process energy views, reports, and FEMS integration
Key capabilities
- Equipment tag and operating data organization
- PLC, MES, and power-data integration
- Energy-use estimation by equipment
- Operating-state energy models
- Process-level consumption visualization
- Inefficiency reports and savings priorities
Deployment goals
- Energy use patterns by equipment
- Inefficiency identification
- Improvement priorities
Frequently asked questions
- Does every machine need its own power meter?
- We review available metering and PLC/MES data to determine the appropriate mix of direct measurement and estimation from operating data.
- Can it connect to an existing FEMS?
- Yes. We review the FEMS data interface and define how equipment- and process-level results should feed into it.