Santher Celulose Integrated IoT and AI for Predictive Maintenance, Driving OEE Growth

How Decision-Grade AI transformed raw material variability into predictive performance and measurable OEE gains.

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About the Company

• Santher Celulose, , through Trinity Business Group, operates large-scale industrial production lines in the tissue and paper segment.

  
  

• Operating under high variability in raw material quality, the company required greater predictability in production performance and maintenance strategy.
  

The Challenge

Variability in cellulose raw material quality directly impacted production stability, machine performance, and output efficiency. Traditional monitoring frameworks failed to connect predictive maintenance requirements and pptimal machine setup configurations:

• Suboptimal OEE performance

• Reactive maintenance cycles

• Inconsistent production throughput

• Inefficient parameter adjustments on the production line
  

Operations required real-time intelligence to translate raw material variability into optimal machine decisions.

Grand Thera Deployment

Grand Thera implemented a decision-grade AI built on:

TheraOS Structured consolidation of production data, quality metrics, and machine telemetry into unified operational intelligence.

• Integrate raw material quality data with machine telemetry and production metrics

• Standardize and contextualize fragmented industrial datasets

• Translate cellulose variability into real-time performance signals

• Provide unified visibility across production, maintenance, and quality teams

• Establish a deterministic decision layer over variable industrial inputs
  

Specialized AITs – Predictive and optimzation models designed to:

• Identify production potential based on cellulose quality inputs

• Anticipate maintenance requirements before performance degradation

• Recommend ideal machine setup configurations

• Optimize operational stability across shifts
  

Production monitoring evolved from reactive supervision to predictive performance orchestration.

Results

• +10 basis points increase in OEE on the deployed production line

• Reduction in unplanned downtime through predictive maintenance logic

• Improved stability in throughput and quality consistency

• Data-driven setup optimization replacing manual trial-and-error adjustments

  
  

The initiative transformed raw material variability from a constraint into a controllable operational variable.

Client Testimonial

“The integration between raw material intelligence and machine setup fundamentally changed how we operate. Performance became predictable, and maintenance became strategic rather than reactive.” - Matthew Couri, Performance Consultant

Discover how Grand Thera AI transforms complex data into clarity, control, and confidence for critical decision-making. Schedule a demonstration .