US20070158040A1 - Method and apparatus for estimating an optimal dosage of bleaching agent to be used in a process for producing pulp - Google Patents

Method and apparatus for estimating an optimal dosage of bleaching agent to be used in a process for producing pulp Download PDF

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US20070158040A1
US20070158040A1 US10/577,434 US57743404A US2007158040A1 US 20070158040 A1 US20070158040 A1 US 20070158040A1 US 57743404 A US57743404 A US 57743404A US 2007158040 A1 US2007158040 A1 US 2007158040A1
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bleaching agent
pulp
brightness value
wood chips
dosage
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Mokhtar Benaoudia
Pierre Bedard
Luc Laperriere
Celine Leduc
Claude Daneault
Laurier Morissette
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Centre de Recherche Industrielle du Quebec CRIQ
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Centre de Recherche Industrielle du Quebec CRIQ
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Assigned to CENTRE DE RECHERCHE INDUSTRIELLE DU QUEBEC reassignment CENTRE DE RECHERCHE INDUSTRIELLE DU QUEBEC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: BEDARD, PIERRE, BENAOUDIA, MOKHTAR, DANEAULT, CLAUDE, LAPERRIERE, LUC, LEDUC, CELINE, MORISSETTE, LAURIER
Publication of US20070158040A1 publication Critical patent/US20070158040A1/en
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    • D—TEXTILES; PAPER
    • D21—PAPER-MAKING; PRODUCTION OF CELLULOSE
    • D21C—PRODUCTION OF CELLULOSE BY REMOVING NON-CELLULOSE SUBSTANCES FROM CELLULOSE-CONTAINING MATERIALS; REGENERATION OF PULPING LIQUORS; APPARATUS THEREFOR
    • D21C9/00—After-treatment of cellulose pulp, e.g. of wood pulp, or cotton linters ; Treatment of dilute or dewatered pulp or process improvement taking place after obtaining the raw cellulosic material and not provided for elsewhere
    • D21C9/10—Bleaching ; Apparatus therefor
    • D21C9/1026—Other features in bleaching processes
    • D21C9/1052—Controlling the process
    • D—TEXTILES; PAPER
    • D21—PAPER-MAKING; PRODUCTION OF CELLULOSE
    • D21C—PRODUCTION OF CELLULOSE BY REMOVING NON-CELLULOSE SUBSTANCES FROM CELLULOSE-CONTAINING MATERIALS; REGENERATION OF PULPING LIQUORS; APPARATUS THEREFOR
    • D21C9/00—After-treatment of cellulose pulp, e.g. of wood pulp, or cotton linters ; Treatment of dilute or dewatered pulp or process improvement taking place after obtaining the raw cellulosic material and not provided for elsewhere
    • D21C9/10—Bleaching ; Apparatus therefor
    • D21C9/16—Bleaching ; Apparatus therefor with per compounds
    • D21C9/163—Bleaching ; Apparatus therefor with per compounds with peroxides

Definitions

  • the present invention relates to the field of pulp and paper process automation, and more particularity to methods for estimating and controlling optimal dosage of bleaching agent to be used in a process for producing pulp of a required brightness value from wood chips.
  • Thermomechanical pulp properties and quality are influenced by two types of variables: feed material (chips) and process (refiner). Over the years, many researchers have underscored the impact of the stability of the refiner operation for the production of constant pulp quality, as mentioned by Strand, B. C. in “The Effect of Refiner Variation on Pulp Quality”, International Mechanical Pulping Conference, Proceedings, 125-130 (1995). However, variations of the process itself are mainly related to variations in the raw material feeding the system as, mentioned by Wood, J. A. in “Chip Quality Effects in Mechanical Pulping—a Selected Review”, 1996 TAPPI Pulping Conference, Proceedings, 491-497 (1996). In particular, pulp brightness is considered as an important quality requirement, as discussed by Dence, C. W. et al. in “Pulp Bleaching—Principles and Practice”, TAPPI Press, 457-490 (1996).
  • a main object of the methods, apparatus and system according to the invention is to estimate the optimal dosage of bleaching agent for the purpose of control thereof in a pulp production process, by modeling the relationship between the quality of the chips feeding the process with an important pulp and paper resulting property, namely pulp brightness.
  • the model is used to evaluate the minimum charge of peroxide required to reach certain level of pulp brightness according to possible chips properties fluctuations, in order to minimize the cost and environmental impact of the bleaching operation.
  • a method for estimating an optimal dosage of bleaching agent to be used in a process for producing pulp of a required brightness value from wood chips comprises the step of: i) estimating a set of wood chip properties characterizing said wood chips to generate corresponding wood chip properties data, said set including reflectance-related properties; said method being characterized by further comprising the steps of: ii) providing an initial dosage value of said bleaching agent; and iii) feeding said wood chip properties data and said bleaching agent dosage value at corresponding inputs of a predictive model for generating predicted brightness value of pulp to produce from said wood chips, to estimate the optimal bleaching agent dosage for which said predicted brightness value substantially reaches said required brightness value.
  • a method of controlling the bleaching of pulp in a pulp production process on the basis of the optimal bleaching agent dosage estimated according to the above mentioned estimation method said pulp production process including, between said steps i) and iii), at least one processing step including a step of refining said wood chips to produce refined wood chips.
  • the control method comprises the step of: a) adding bleaching agent to said refined wood chips according to said optimal bleaching agent dosage to produce said pulp.
  • a method of controlling the bleaching of pulp in a pulp production process on the basis of the optimal bleaching agent dosage estimated according to the above mentioned estimation method said pulp production process including, between said steps i) and iii), at least one processing steps including a step of refining said wood chips to produce refined wood chips.
  • the control method comprising the step of: a) estimating a resulting brightness value of the pulp according to a time delay following said predicted brightness value generation; b) comparing said predicted brightness value with said resulting brightness value to generate further error data; c) further optimizing said bleaching agent dosage value to minimize said further error data; and d) adding bleaching agent to said refined wood chips according to said further optimized bleaching agent dosage to produce said pulp.
  • an apparatus for estimating an optimal dosage of bleaching agent to be used in a process for producing pulp of a required brightness value from wood chips comprises means for estimating a set of wood chip properties characterizing said wood chips to generate corresponding wood chip properties data, said set including reflectance-related properties.
  • the apparatus is characterized by further comprising: data processor means implementing a predictive model receiving at corresponding inputs thereof said wood chip properties data and an initial bleaching agent dosage value for generating predicted brightness value of pulp to produce from said wood chips, to estimate the optimal bleaching agent dosage for which said predicted brightness value substantially reaches said required brightness value.
  • a system of controlling the bleaching of pulp in a pulp production process on the basis of the optimal bleaching agent dosage estimated by the above mentioned apparatus said pulp production process including at least one processing steps including a step of refining said wood chips to produce refined wood chips.
  • the control system comprises means for adding bleaching agent to said refined wood chips according to said optimal bleaching agent dosage to produce said pulp.
  • a system for controlling the bleaching of pulp in a pulp production process on the basis of the optimal bleaching agent dosage estimated by the above mentioned apparatus said pulp production process including at least one processing steps including a step of refining said wood chips to produce refined wood chips.
  • the control system comprises means for estimating a resulting brightness value of the pulp according to a time delay following said predicted brightness value generation by said predictive model; means for time delaying said predicted brightness value according to said time delay; means for comparing said delayed predicted brightness value with said resulting brightness value to generate further error data; said predictive model further optimizing said bleaching agent dosage value to minimize said further error data; and means for adding bleaching agent to said refined wood chips according to said further optimized bleaching agent dosage to produce said pulp.
  • FIG. 1 is a graph showing relative importance index of independent variables according to PLS analysis
  • FIG. 2 is a graph showing coefficient of correlation for dependent variables by PLS analysis
  • FIG. 3 is a graph representing observed and predicted values for ISO brightness
  • FIG. 4 is a block diagram of a bleaching agent control system according to a first embodiment of the invention, which includes an estimation apparatus based on a neural network-based predictive model;
  • FIG. 5 is a block diagram of a bleaching agent control system according to another embodiment of the invention, which is particularly adapted for controlling a bleaching operation as part of a continuous pulp production process.
  • the methods for estimating an optimal dosage of bleaching agent of the present invention being based on the estimation of properties of wood chips that must have significant effect on the bleaching characteristics of the pulp made therefrom, an experimental protocol used to qualify wood chip properties to be preferably used in modeling will be presented first.
  • two sets of experiments corresponding to two different blocks were performed.
  • the last two species were chosen because they represent a potential source of new resources.
  • the trees have been selected, cut, barked and chipped in order to obtain standard chips with known and controlled age. In fall, outdoor stacks of each species of chips were prepared.
  • the six samples allow to evaluate the evolution of the quality, i.e. degradation, of the chips in time. This degradation is highly dependent on storage temperature.
  • the first four samples were evaluated at an interval of three weeks. After that, there has been a longer waiting time. It was noticed that the winter degradation of each stack was extremely slow.
  • the second block of experiments was used to investigate the effects of other important variables regarding pulp quality.
  • This second block of experiments has been conducted with four variables: species (black spruce, balsam fir), density (high, low), initial dryness of the chips (fresh, dry), and thickness of the chips (0-4 mm, 4-8 mm).
  • Table 2 describes the experiments for chips aging that were conducted in this second block. TABLE 2 Large chips Small chips (4-8 mm) 0-4 mm INITIAL CHIPS Spruce at low density Test no. 1 Test no. 2 Balsam fir at low density Test no. 3 Test no. 4 Spruce at high density Tests no. 5 and 6 Test no. 7 Balsam fir at high density Test no. 8 Tests no.
  • Test no. 20 For the purpose of the experiment, the estimation and control method according to the invention was applied to a batch pulp production process. Refining was conducted on a pilot unit Metso CD-300. Each sample was washed and refined in two stages. The first one was conducted at a temperature of 128° C. and the second one at atmospheric pressure. For each experiment, pulps with a freeness ranging from 200 to 150 mL were selected for further peroxide bleaching, which fundamental principles are briefly described next.
  • Hydrogen peroxide readily decomposes under bleaching conditions according to the following equation: 2H 2 O 2 ⁇ O 2 +H 2 O (2)
  • Sodium silicate and magnesium silicate are normally added to the bleach liquor to stabilize peroxide. Transition metals ions like iron, manganese and copper catalyze peroxide decomposition.
  • the pulp was pretreated with 0.2% of DTPA. The pretreatment of the pulp was done at 60° C., 15 minutes and 3% of consistency.
  • the bleaching liquor was composed of 3.00% of sodium silicate, 0.05% of magnesium sulfate, hydrogen peroxide and sodium hydroxide. After the bleaching step, the pulp was diluted at 1% of consistency and neutralized with sodium metabisulfite at pH 5.5. A volume of the bleaching liquor was kept to measure the residual peroxide by an iodometric dosage. Optical properties such as ISO brightness and color coordinates (L*, a*, b*) have been measured according to Paptac standard.
  • Chips of the eighty four (84) runs in block 1 and twenty (20) runs in block 2 were systematically analyzed using a wood chip optical inspection apparatus known as CMS-100 chip management system commercially available from the present assignee, Centre de mecanic Industrielle du Quebec (Ste-foy, Canada), for measuring a number of optical properties as well as moisture content.
  • a wood chip optical inspection apparatus known as CMS-100 chip management system commercially available from the present assignee, Centre de mecanic Industrielle du Quebec (Ste-foy, Canada
  • Such wood chip inspection apparatus is described in U.S. Pat. No. 6,175,092 B1 issued on Jan. 16, 2001 to the present assignee.
  • Such multi-sensor system includes main and optional auxiliary sensors able to characterize wood chips online.
  • the main sensors include artificial vision sensor (an RGB color camera) and near infrared sensor to measure chip brightness and moisture content.
  • Auxiliary sensors such as a distance sensor and an air conditions sensor to measure air temperature and relative humidity may be advantageously used. They provide information that extends measurements of the main sensor to stabilize the system (for example, variations of the camera measuring distance will influence the chip brightness measurement).
  • the system will work on frozen and non-frozen wood chips, and it used for predicting bleach charges or dosage based on chip quality for use as a bleach control method or system. The correlation between some chip properties and its possible application in bleach control is discussed by Ding, F. et al. in “Economizing the Bleaching Agent Consumption by Controlling Wood Chip Brightness”, Control System 2002 , Proceedings , June 3-5, Sweden, 205-209 (2002). The most relevant wood chips properties measurements for the purpose of the present invention are described next.
  • a first measurement relates to chip luminance, wherein the brightness of black is defined as zero and the brightness of white as 150 .
  • the RGB colour camera of the system is calibrated by a color checker made of black and white paperboard.
  • the wood chip color is between white and black, so its brightness is between 0 and 150.
  • a second measurement relates to chip average moisture content.
  • the system includes a near infrared sensor such as model NDC 55 supplied by Korins Co. Ltd. (Korea), that is used to measure surface moisture content of wood chips, without any non-contact therewith.
  • a method for estimating surface moisture of wood chips that can be used for the purpose of the estimation method of the present invention is disclosed by Ding, F. et al.
  • a number of four (4) other measurements are considered, namely the image “H”, “S” and “L” parameters, as well as a chip average size estimation, which may be obtained using an imaging-based, chip size classifier such as the ScanChipTM system supplied by Iggesund Tools Inc. (Oldsmar, Fla., USA).
  • a sampling-based size estimation method according to a known standard such as William size classifying protocol may be used to provide chip size data.
  • Other color imaging standard measurements such as “R G B” or “LAB” may be also used to characterize reflectance-related characteristics of wood chips.
  • the techniques that are preferably used to screen the columns of data to a reasonable amount of most relevant variables and to use the lines for neural network training will be explained. Both techniques are done with the objective of obtaining a good enough pulp brightness model that could be used in a brightness control strategy.
  • FIG. 1 presents the independent variables that have been chosen according their relative importance index.
  • the parameters, which have most impact and are correlated to dependent variables are the concentration of sodium hydroxide (NaOH) and the concentration of hydrogen peroxide (PEROA).
  • the variables CO_moy (chip size), MDH (average of H), MMLC (average of luminance), MDS (average of S), MDL (average of L) and MSURFM (average of the surface moisture) also contribute to a lesser extent to the bleached pulp properties response.
  • the correlation coefficients for each dependent variable are presented in FIG. 2 .
  • the value R 2 shows the correlation for the dependent variables. It is an indication of how well the model can fit the experimental data.
  • the value Q 2 shows the correlation of the interpolated responses, i.e. predictions not part of the experimental data.
  • the graph shows that the model is adequate to predict ISO brightness [ISOB] (coefficient of correlation of 0.88), color coordinates L*[LB] (coefficient of correlation of 0.92) and a*[AB] (coefficient of correlation of 0.90), and residual peroxide [PEROR] (coefficient of correlation of 0.83).
  • the coefficient of correlation is only 0.60.
  • chemical properties such as MEXT (extractives) and AGR (fatty and resinic acids) are difficult to correlate (coefficients of correlation of 0.33 and 0.26 are respectively obtained).
  • FIG. 3 presents observed and predicted values for the ISO brightness. These results show that the model is able to predict adequate values for this optical property. Brightness ranging from 43.79% to 80.2% was measured on the bleached pulps.
  • a neural network-based predictive model that can be used to carry out the method according to the invention will now be described in reference to FIG. 4 .
  • any appropriate modeling technique such as neural network, PLS, Model Predictive Controller (MPC), regression, state space matrix, FRI, fuzzy logic, genetic algorithm, or a combination thereof can be used to obtain a predictive model for the purpose of the present invention.
  • Training was stopped after an average absolute mean error of 5% was reached between the neural network prediction and the training output brightness value for each of the 506 lines.
  • the value of 5% was chosen by taking two factors into consideration: 1) reliability of the output measurements: the experimental error related to the brightness value is about 3%, i.e. ⁇ 0.5 brightness points in the experimental span of 43.79 to 80.2 measured brightness; and 2) reliability of the input measurements: calibration errors may encourage an increase of the training error.
  • the training results of the final network, in terms of the connection weights between each of its constituting neurons, were imported into the neural network 12 of model 10 , in the form of a computer program that can be implemented in a microcomputer by any person skilled in the art using well-known programming tools.
  • Such program is able to simulate brightness prediction based on the seven (7) chosen inputs, namely reflectance-related properties of wood chips that are Luminance, M, H, S, L and chip size from measurement system 14 as part of the bleaching agent dosage estimating apparatus, and bleaching agent dosage (peroxide charge) value used by the bleaching unit 16 as part of the bleaching control system, to add a corresponding volume of bleaching agent solution into the pulp made of refined wood chips to produce bleached pulp.
  • unmodeled disturbances may also be applied to the neural network at input 17
  • corresponding wood chip properties data are fed at respective inputs 18 of neural network 12 , as well as an initial dosage value of the bleaching agent (peroxide) at further input 20 .
  • input 20 is preferably used to receive bleaching agent dosage as actually fed to pulp as typically calculated from a flow meter measurement at bleaching unit outlet, knowing agent concentration and pulp weight, the initial dosage may be set to a predetermined value for the purpose of initializing the prediction model.
  • the neural network 12 generates at output 22 thereof, a predicted brightness value for pulp to produce from the inspected wood chips. Then, the brightness predicted value is compared with the required brightness value to generate error data, as indicated at node 24 .
  • the error data is used by an optimization module 26 , which optimizes the bleaching agent dosage value to minimize the error data.
  • the above prediction, comparison and optimization steps are repeated with the optimized bleaching agent dosage value as fed back to the network 12 at input 25 thereof, until the brightness predicted value substantially reaches the required brightness value, to estimate the optimal bleaching agent dosage.
  • the peroxide charge is tuned to minimize the error, while maintaining constant chip properties, and an optimization loops is performed in model 10 for several iterations before it reaches the peroxide charge that meets the required brightness value or set point according to the neural network model prediction.
  • a bleaching agent control system which is particularly adapted for controlling a bleaching operation as part of a continuous pulp production process will now be described with reference to FIG. 5 .
  • Such continuous pulp production process includes, between raw wood chips supplying step, where the wood chips properties are measured, and bleaching step at least one step consisting of refining chips, and generally a plurality of other processing or handling steps each being characterized by a specific processing time, involving equipment such as chests and towers for performing process functions such as storage, mixing and transfer on various pulp matter such as accepted pulp, unrefined reject, refined reject, screened reject, etc.
  • the estimated wood chips properties may be used by the predictive model according to the invention only if the time delay between wood properties estimation and bleaching steps as induced by the intermediate processing steps is considered by the bleaching agent estimation method.
  • a time delay module 30 receiving all wood chip properties data, namely luminance, moisture content”, H, S, L and size data, to apply thereto a time delay value, which can be either a fixed value in the case of a simple process involving few intermediate processing steps, or a calculated value in the case of a more complex process, using input/output process parameters including pulp consistency, pulp weight/mass flow rate, chest/tower volume and filling levels, etc.
  • a time delay module 30 receiving all wood chip properties data, namely luminance, moisture content”, H, S, L and size data, to apply thereto a time delay value, which can be either a fixed value in the case of a simple process involving few intermediate processing steps, or a calculated value in the case of a more complex process, using input/output process parameters including pulp consistency, pulp weight/mass flow rate, chest/tower volume and filling levels, etc.
  • basic dynamic calculation or a more advanced modeling technique such as neural networks, fuzzy logic, genetic algorithms, or a combination thereof along with active mass balance data
  • the processing chest/towers used in the process between chip properties estimation and bleaching operation induce an attenuation of the actual wood chip properties, and therefore, the estimated wood chip properties data must be filtered accordingly, preferably using an attenuation filter 32 receiving the delayed chip properties data from time delay 30 , and feeding the resulting chip property data to inputs 18 of the predictive model 10 .
  • an attenuation filter 32 receiving the delayed chip properties data from time delay 30 , and feeding the resulting chip property data to inputs 18 of the predictive model 10 .
  • basic dynamic calculation or a more advanced modeling technique may be used by any person skilled in the computer programming for the purpose of implementing the desired attenuation filtering.
  • the model 10 in addition to receiving the required brightness (set point) at input 34 thereof in a same manner as explained above with reference to the embodiment shown in FIG. 4 , receives further error data at input 40 , in order to further improve bleaching dosage estimation, as will now be explained in detail. Since the optimal dosage estimation is based on a prediction by the model 10 of the resulting, final brightness of the bleached pulp, an estimation of the resulting, actual pulp brightness as obtained either with an online measurement sensor (not shown) or following an off-line analyzing procedure on a pulp sample (Paptac standard), is made according to a time delay following the predicted brightness value generation by the predictive model 10 .
  • such measurement may be made at the outlet of bleaching chest/tower, or be made at the scanning station of the paper machine by implanting an appropriate model considering active mass balance data and respective chip properties data associated with the various pulp matters used to produce the paper.
  • a time delay 36 is provided for delaying the predicted brightness value according to the time delay, which may be either a fixed value or a calculated value obtained through dynamic calculation or advanced modeling in a similar manner as explained above.
  • a comparator 38 is provided for comparing the delayed predicted brightness value with the resulting brightness value to generate further error data that is fed back to input 40 of predictive model 10 , which can further optimize the bleaching agent dosage value to minimize further error data.
  • the bleaching unit 28 Upon receiving further optimized bleaching dosage data generated by the model 10 , the bleaching unit 28 is caused to discharge a corresponding amount of bleaching agent solution, and the applied dosage measurement is fed back to the input 20 of model 10 in a same manner as explained before with respect to the embodiment shown in FIG. 4 .
  • the bleaching agent addition control function may be conveniently performed through a model implemented in the data processing device, generating one or more mass flow set points for the bleaching agent so as to better regulate the process.
  • the same brightness set point can be achieved at lower bleaching agent charges when the chip quality increases.
  • the method may be useful to assist chip management in the mill, or in the context of internal model control (IMC) or model predictive control (MPC) strategies. It is to be understood that dosage of other bleaching agents such as hydrosulfites may also be performed with the method of the invention.

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CA2,447,098 2003-10-28
CA002447098A CA2447098A1 (fr) 2003-10-28 2003-10-28 Methode d'estimation du dosage optimal d'agent de blanchiment a melanger a des copeaux de bois
PCT/CA2004/001888 WO2005042832A1 (fr) 2003-10-28 2004-10-28 Procede et dispositif permettant l'estimation du dosage optimal d'agent de blanchiment pour un procede de production de pate a papier

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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070027565A1 (en) * 2003-12-05 2007-02-01 Saurer Gmbh & Co. Kg Method and apparatus for order control in a production process for a fiber product
US20100121473A1 (en) * 2007-05-04 2010-05-13 CENTRE DE RECHERCHE INDUSTRIELLE DU QUéBEC System and method for optimizing lignocellulosic granular matter refining
US8540845B2 (en) 2010-04-27 2013-09-24 Centre De Recherche Industrielle Du Quebec Method and system for stabilizing dry-based density of wood chips to be fed to a chip refining process
US8626791B1 (en) * 2011-06-14 2014-01-07 Google Inc. Predictive model caching
JP2015074835A (ja) * 2013-10-04 2015-04-20 王子ホールディングス株式会社 パルプ白色度の推定装置およびその推定方法
JP2020024541A (ja) * 2018-08-07 2020-02-13 株式会社キーエンス データ分析装置及びデータ分析方法
JP2020024542A (ja) * 2018-08-07 2020-02-13 株式会社キーエンス データ分析装置及びデータ分析方法
WO2020168160A1 (fr) 2019-02-15 2020-08-20 Event Capture Systems, Inc. Procédé en ligne permettant la détermination de normes de qualité de copeaux de bois entrants dans un broyeur à papier

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030149493A1 (en) * 2002-02-07 2003-08-07 Blevins Terrence L. Adaptation of advanced process control blocks in response to variable process delay
US6879971B1 (en) * 1995-12-22 2005-04-12 Pavilion Technologies, Inc. Automated method for building a model

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4013506A (en) * 1974-07-22 1977-03-22 Canadian International Paper Company Method and apparatus for automatically and simultaneously controlling solution viscosity and brightness of a pulp during multi-stage bleaching
US6153300A (en) * 1994-04-18 2000-11-28 Ahlstrom Machinery, Inc. Bleaching cellulose pulp having cleanliness which varies significantly over time using at least two different bleaching stages and bleaching chemicals
CA2228023A1 (fr) * 1998-01-23 1999-07-23 Centre De Recherche Industrielle Du Quebec Methode et appareil pour le classement de lots de copeaux de bois ou articles connexes .
US6273994B1 (en) * 1998-01-30 2001-08-14 Iogen Corporation Method and device for measuring bleach requirement, bleachability, and effectivenss of hemicellulase enzyme treatment of pulp
US6153050A (en) * 1998-03-24 2000-11-28 Noranda Forest Inc. Method and system for controlling the addition of bleaching reagents to obtain a substantially constant percentage of pulp delignification across the first bleaching/delignifying stage

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6879971B1 (en) * 1995-12-22 2005-04-12 Pavilion Technologies, Inc. Automated method for building a model
US20030149493A1 (en) * 2002-02-07 2003-08-07 Blevins Terrence L. Adaptation of advanced process control blocks in response to variable process delay

Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070027565A1 (en) * 2003-12-05 2007-02-01 Saurer Gmbh & Co. Kg Method and apparatus for order control in a production process for a fiber product
US7496421B2 (en) * 2003-12-05 2009-02-24 Saurer Gmbh & Co. Kg Method and apparatus for order control in a production process for a fiber product
US20100121473A1 (en) * 2007-05-04 2010-05-13 CENTRE DE RECHERCHE INDUSTRIELLE DU QUéBEC System and method for optimizing lignocellulosic granular matter refining
US8679293B2 (en) 2007-05-04 2014-03-25 Centre De Recherche Industrielle Du Quebec System and method for optimizing lignocellulosic granular matter refining
US8540845B2 (en) 2010-04-27 2013-09-24 Centre De Recherche Industrielle Du Quebec Method and system for stabilizing dry-based density of wood chips to be fed to a chip refining process
US8626791B1 (en) * 2011-06-14 2014-01-07 Google Inc. Predictive model caching
JP2015074835A (ja) * 2013-10-04 2015-04-20 王子ホールディングス株式会社 パルプ白色度の推定装置およびその推定方法
JP2020024541A (ja) * 2018-08-07 2020-02-13 株式会社キーエンス データ分析装置及びデータ分析方法
JP2020024542A (ja) * 2018-08-07 2020-02-13 株式会社キーエンス データ分析装置及びデータ分析方法
JP7049210B2 (ja) 2018-08-07 2022-04-06 株式会社キーエンス データ分析装置及びデータ分析方法
JP7049211B2 (ja) 2018-08-07 2022-04-06 株式会社キーエンス データ分析装置及びデータ分析方法
WO2020168160A1 (fr) 2019-02-15 2020-08-20 Event Capture Systems, Inc. Procédé en ligne permettant la détermination de normes de qualité de copeaux de bois entrants dans un broyeur à papier
EP3924732A4 (fr) * 2019-02-15 2022-10-05 Event Capture Systems, Inc. Procédé en ligne permettant la détermination de normes de qualité de copeaux de bois entrants dans un broyeur à papier

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