Featured cases · Industrial · Pulp & paper
Santher integrates IoT and AI for predictive maintenance and OEE growth
Raw-material variability became a controllable variable: +10 basis points of OEE on the deployed line.
Predictive maintenanceIndustrial operations
About the client
Through Trinity Business Group, Santher operates large-scale tissue and paper production lines under high variability in raw-material quality.
The challenge
- Cellulose quality variability affecting stability and output
- Reactive maintenance cycles
- Inconsistent throughput
- Manual, trial-and-error machine setup
What Grand Thera deployed
TheraOS
- Raw-material quality, machine telemetry and production metrics unified
- Fragmented industrial data standardized
- One view across production, maintenance and quality
Specialized AITs
- Production potential from cellulose inputs
- Maintenance anticipated before degradation
- Recommended machine setup
- Stability across shifts
- Cellulose quality variability affecting stability and output
- Reactive maintenance cycles
- Inconsistent throughput
- Manual, trial-and-error machine setup
What was at stake.
Results
Results
- 01
+10 basis points of OEE on the deployed production line
- 02
Less unplanned downtime through predictive maintenance
- 03
More stable throughput and quality
- 04
Data-driven setup replacing trial and error
“Performance became predictable, and maintenance became strategic rather than reactive.”
Source: original case publication
