A method and apparatus for controlling a cellulosic pulp process for producing a pulp product having a desired pulp property is disclosed. The method involves illuminating an in-process portion of pulp using a first wavelength of light, and receiving a scattered light spectrum from the illuminated portion of pulp, the scattered light spectrum including spectral components that have been shifted in wavelength through interaction with a constituent of the illuminated portion of pulp. The method also involves filtering the scattered light spectrum to separate the spectral components, and identifying spectral features in the filtered scattered light spectrum that correspond to the pulp property. The method further involves generating a control signal for controlling the pulp process based on variations in the identified spectral features to cause the pulp property to fall within a desired range.

A method for obtaining information on quality of combustion of a liquor in a chemical recovery boiler. The method comprises entering a value of a first input parameter to a computational model configured to determine, based on the value of the first input parameter, a value of the quality of combustion of the liquor in the chemical recovery boiler, and at a first time, running the computational model to obtain a first modelling result. The method comprises measuring, from the chemical recovery boiler a value indicative of carryover to obtain a measurement result; comparing the first modelling result with [a] the measurement result or [b] a result derived from the measurement result, to obtain a primary comparison result; and adjusting the value of the first input parameter based on the primary comparison result to obtain an adjusted value of the first input parameter. The method comprises entering the adjusted value of the first input parameter to the computational model, and at a second time, running the computational model to obtain the information on quality of combustion of the liquor in the chemical recovery boiler.

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.

A method and apparatus for controlling a cellulosic pulp process for producing a pulp product having a desired pulp property is disclosed. The method involves illuminating an in-process portion of pulp using a first wavelength of light, and receiving a scattered light spectrum from the illuminated portion of pulp, the scattered light spectrum including spectral components that have been shifted in wavelength through interaction with a constituent of the illuminated portion of pulp. The method also involves filtering the scattered light spectrum to separate the spectral components, and identifying spectral features in the filtered scattered light spectrum that correspond to the pulp property. The method further involves generating a control signal for controlling the pulp process based on variations in the identified spectral features to cause the pulp property to fall within a desired range.

The presently disclosed subject matter relates to a method and system of providing customized bioprocessing conditions for a variety of feedstock materials. Particularly, it has been surprisingly found that there is a correlation between the weight percent of lignin, cellulose, and/or hemicellulose and various reaction conditions. The weight percent lignin, cellulose, and hemicellulose are used to calculate indexes used to create a process index for sorting the feedstock into categories. A process adjustment factor can also be calculated and used to adjust the reaction conditions for each feedstock material.

A method for obtaining information on quality of combustion of a liquor in a chemical recovery boiler. The method comprises entering a value of a first input parameter to a computational model configured to determine, based on the value of the first input parameter, a value of the quality of combustion of the liquor in the chemical recovery boiler, and at a first time, running the computational model to obtain a first modelling result. The method comprises measuring, from the chemical recovery boiler a value indicative of carryover to obtain a measurement result; comparing the first modelling result with [a] the measurement result or [b] a result derived from the measurement result, to obtain a primary comparison result; and adjusting the value of the first input parameter based on the primary comparison result to obtain an adjusted value of the first input parameter. The method comprises entering the adjusted value of the first input parameter to the computational model, and at a second time, running the computational model to obtain the information on quality of combustion of the liquor in the chemical recovery boiler.

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.

A method for chemical pulp production in a multi-stage process, comprising a first process stage, comprising a woodyard comprising steps such as debarking, chipping, pile storage and/or reclaim; a second process stage, comprising a fiberline comprising steps such as cooking and/or bleaching; and at least a third process stage; wherein a first set of data is gathered at least at the first and at the second process stage, wherein the first set of data for each process stage comprises measurement results and/or parameters calculated based on measurement results, wherein the measurements and/or parameters are related to raw material, equipment, process measurements and/or product properties; the first set of data is sent to the subsequent process stage, wherein the process steps of the subsequent process stage are adjusted based on the first set of data received; a second set of data is gathered at least at the second and at the third process stage, wherein the second set of data for each process stage comprises information related to availability of processing capacity, predicted availability of processing capacity and/or required material flow or quality; the second set of data is sent to the preceding process stage, wherein the process steps of the preceding process stage are adjusted based on the second set of data received.

The present disclosure pertains to bio-composites comprising plant biomass, a bio-binder, and a carbon nanomaterial, and a process for their preparation. The bio-composite materials of the present disclosure offer superior mechanical and thermal properties while being environmentally sustainable.

A method, apparatus, and computer program control a process in making pulp, paper, or board automatically controlling by a rules engine a dosing of a chemical agent in the process into a fibrous suspension. The rules engine receives a plurality of measurements relating to the process and maintains a plurality of rules sets, including an active rules set. Each rules set defines how the dosing depends on the measurements. The rules engine controls the dosing of the chemical agent based on the measurements and the active rules set, logs at least some of the measurements and actualised dosing of the chemical agent, and receives at least one rules set candidate. The dosing of the chemical agent is simulated with the received at least one rules set candidate based on the earlier measurements; and simulation results are output for optimising performance of the chemical agent in the process.