Application of AI-based Approach to Control Papermaking Process, TAPPICon24

This paper explores AI's role in revolutionizing the pulp and paper industry, explicitly predicting Wet Tensile Strength (WT) for specialty-grade papers. Leveraging eLIXA technology, a 90-day study achieved a 15% chemical dosage reduction and an 80% decrease in Wet Tensile standard deviation. The real-time dosage prediction led to optimizing the Wet Strength Resin consumption and improved process reliability. The self-learning models exhibited adaptability to changing variables, ensuring their robustness. Overall, this study highlights AI's transformative impact on efficiency, cost savings, and product quality within the dynamic landscape of papermaking. The approach used for wet-strength optimization has been used to optimize other aspects of pulp and paper production.

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