Buckman Laboratories International, Inc.

John Carter

Feiran Li

Daniel E Glover

Mark L Reed

Narasimha M Rao

Arun Kumar Raju Ganesan

Mark Christopher

Remi Charron

Bryan Glover

Mark Reed

Systems and methods as disclosed herein automatically provide real-time dosing corrections for an industrial process wherein enzyme blends are applied to natural fibers for pulp/paper production. An initial enzyme blend (e.g., enzymes and supporting formulation components, as relevant) and respective dose rates are selected to be applied based on expected fiber surface substrate characterization, expected fiber quality characterization, the physical conditions of the system being treated, respective characteristics of the initially selected enzyme blend components, etc. Upon application of the initial enzyme blend, online sensors provide real-time feedback data corresponding to measured actual values for the fiber surface substrate characterization and fiber quality characterization. A replacement enzyme blend (enzymes and supporting formulation components) and respective dose rates thereof is dynamically selected based on the feedback data. The enzyme dosing stage can be optimized responsive to product changes and/or variations in fiber sources/blend and/or physical conditions, substantially in real time.

System and method of dynamic corrective enzyme selection and formulation for pulp and paper production

A system and method is provided for proactive process intervention in manufacturing creped products via a chemical feed stage and a Yankee dryer stage. The method includes generating signals from a plurality of online sensors, corresponding to directly measured variables for respective process components such as, e.g., pH, conductivity, and Yankee blade vibration. Models are developed including retrievable information relating combinations of certain directly measured variables to respective quality characteristics of the creped product. The method further includes indirectly determining quality characteristics (e.g., softness, bulk) for the creped product, substantially in real time, based on, e.g., signals corresponding to directly measured variables, and optionally a predicted natural coating potential. An output feedback signal is automatically generated corresponding to a detected intervention event based on the indirectly determined one or more quality characteristics and respective predetermined targets. The feedback signal may automatically regulate chemistry feed characteristics, substantially in real time.

Predictive control of Yankee dryer chemistry and creped product quality

Systems and methods are disclosed herein for contextual data analysis and proactive intervention in industrial plant processes. Each of multiple data streams in an industrial plant are mapped to a common hierarchical data structure, wherein the data streams correspond to respective values or states associated with unit operations, assets, and process streams in the plant. The mapped data streams define hierarchical process relationships between subsets of the unit operations, assets, and process streams. Real-time data is collected to populate at least one level of the hierarchical data structure for certain data streams, wherein future outcomes are predicted for downstream operations based on the collected real-time data for at least one data stream, and at least one other data stream having a defined hierarchical process relationship therewith. Upon ascertaining that predicted future outcomes correspond to issues requiring intervention, output signals are generated based thereon for operator alerts and/or automated control.

Contextual data modeling and dynamic process intervention for industrial plants

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Mobile, AL, United States of America

John Carter