Buckman Laboratories International, Inc.

Richard Lusk

Daniel E Glover

Philip M Hoekstra

David Buist

Vincent Roy

Colin Ruemmele

Sergio Arreola, Jr

Paul Quinn

Nate Brandeburg

Mark D Schroen

Robert Brian White

Vince Roy

Phil Hoekstra

A system and method are provided for predictive control of brown stock treatment at a pulp mill. Various online sensors generate output signals representative of actual values for respective process characteristics, each of which are directly or indirectly affected by adjustments to corresponding process variables. A controller uses the output signals or associated measurement data to dynamically set target values for the process characteristics based on a predicted impact of control responses for corresponding process variables. The controller further generates control signals to actuators associated with the respective process variables based on detected variations between the respective actual values and target values. Exemplary brown stock washing control systems may optimize various types of brown stock washing configurations, including for example vacuum drum washers, compaction baffle washers, chemiwashers, direct displacement washers and wash presses. Cloud-based analytics and machine learning may also be implemented to improve the control algorithms over time.

Predictive control system and method for brown washing treatment in pulp mills

Various embodiments of the present disclosure relate to proactive dosing optimization chemical feed units producing an output solution (such as an oxidizing biocide) therefrom. Online sensors generate signals corresponding to directly measured variables for respective process components. Information is selectively retrieved from models relating combinations of input variables to respective industrial process states, wherein various current process states may be indirectly determined based on directly measured variables for respective system components. An output feedback signal is automatically generated corresponding to a detected intervention event based on the indirectly determined process state. A controller may receive the signal and implement, e.g., regulation of oxidizing biocide feed for optimization of end products and/or performance metrics.

Predictive systems and methods for proactive intervention in chemical processes

A method is provided for decision support in regulating an adhesive coating applied to Yankee dryers. Online sensors are configured to continuously measure stock characteristics, and additional sensors provide actual stock flow rate and machine speed. A controller predicts potential natural coating application from a fibrous sheet generated from the stock to the Yankee dryer surface, substantially in real time, based on the measured characteristics and sensed actual machine values. An output signal may be provided to a display unit, wherein an optimal adhesive coating feed rate may be determined and displayed for operator decision support. The controller may in an automatic mode be configured to regulate the adhesive coating feed rate based on a comparison of one or more determined optimal values associated with respective actual values. The method may include identifying fiber source changes in real time, and predicting a natural coating potential based partly on predetermined correlations.

Real time regulation of Yankee dryer coating based on predicted natural coating transfer

Real time regulation of yankee dryer coating based on predicted natural coating transfer

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Memphis, TN, United States of America

Richard Lusk