Real deployments. Measurable outcomes.

Quantified improvements from live mill optimizations across four continents.

United States

System: ABB QCS + DCS - 272 loops evaluated - 86 tuned

Challenge: A paper machine was experiencing frequent sheet breaks and high process variability affecting quality consistency.

Solution: Systematic evaluation and tuning of 272 control loops, targeted optimization of 86 critical loops, QCS Level 2 improvements.

Results: 22% reduction in sheet breaks, up to 70% reduction in process variability, improved QCS Level 2 control performance.

India

System: ABB DCS + Honeywell QCS - Cyclic 12-min oscillation resolved

Challenge: Paper machine exhibited 12-minute cyclic oscillation in basis weight control affecting moisture and ash profiles.

Solution: Re-optimization methodology applied across multi-vendor systems to identify and eliminate oscillation source.

Results: ~68% basis weight variability reduction, >50% moisture and ash reduction, 4.8% quality reject reduction.

Pakistan

System: AccuRay QCS + DCS - PM - 284 loops analyzed

Challenge: Significant basis weight and moisture variability on PM with slow machine response affecting grade changes.

Solution: Comprehensive loop analysis and targeted tuning to improve response and stabilize wet-end operations.

Results: ~50% variability reduction, 80%+ machine response improvement, stabilized wet-end and fiber distribution.

South Africa

System: Full PM optimization - 228 loops - 113 tuned

Challenge: Paper Machine required optimization for stock stability across multiple plies and weight control responsiveness.

Solution: Full machine optimization engagement with systematic loop tuning across all operational dimensions.

Results: 50-60% stock stability improvement, 46% basis weight variability reduction, 40% faster weight response.

South Africa Digester APC

System: Continuous Digester (NSSC) - 71 loops tuned - AI predictive control

Challenge: NSSC continuous digester experiencing chip level variation affecting pulp quality and suboptimal throughput.

Solution: AI predictive control implementation with focus on chip handling optimization and predictive modeling.

Results: +3.6% production increase, 72% chip variation reduction, $1.2�1.6M estimated annual benefit.

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