AI-Driven Autonomous Control Optimizes Sizing Chemistry and Reduces Masking Occurrences

GoalReduce wet tensile variation and improving wet tensile quality adherence.

<h6>Customer Challenge</h6> <p>A North American recycled packaging producer was interested in optimizing ASA sizing chemistry while reducing occurrences of off quality and lost production due to size masking.</p> <h6>Recommended Solution</h6> <p>Solenis recommended implementation of OPTIX Applied Intelligence (AI), a machine-learning, predictive analytics platform with autonomous control capabilities. OPTIX generates a virtual measure of the Cobb sizing value in real-time. Utilizing AI to make data-driven process adjustments, the ASA sizing chemistry is finely tuned to drive Cobb quality to target.</p> <h6>Results Achieved</h6> <p>Over a six-month period of utilizing OPTIX autonomous control, the mill realized reduced Cobb quality variation and increased target quality adherence.</p> <p><img style="max-width: 50%; width: auto; height: auto;" src="/link/ea31a5a396944e1d810de7ae6742b0bc.aspx" alt="" width="550" height="537" /></p> <p><img style="max-width: 50%; width: auto; height: auto;" src="/link/7fef86f62b21424a9c432b5c82612f83.aspx" alt="" width="550" height="561" /></p> <p style="text-align: center;">Chemical optimization via OPTIX led to a reduction of 175K dry pounds of ASA annually.</p> <p style="text-align: center;"><img style="max-width: 100%; width: auto; height: auto;" src="/link/da25624947c4412e97e9437718e01944.aspx" alt="" width="1100" height="551" /></p> <p style="text-align: center;">&nbsp;</p>