Patent Publication Number: US-2005136547-A1

Title: Polymer reaction and quality optimizer

Description:
FIELD OF THE INVENTION  
      This invention relates to the production of polymers such as polyvinyl chloride (PVC) and more particularly to the optimization of the process for producing polymers and improving the quality of the polymer produced by that process.  
      Description of the Prior Art  
      PVC is one of the oldest polymers and the second largest thermoplastics in terms of volume manufactured in the world. This widespread use arises from PVC&#39;s high degree of chemical resistance and its truly unique ability to be mixed with additives to give a large number of reproducible compounds having a wide range of physical, chemical, and biological properties. This makes PVC a versatile choice over other plastic materials.  
      More than 75% of the world&#39;s PVC resins are produced by the batchwise aqueous suspension precipitation polymerization process. Due to the number of variables involved, such as the amount of monomer charged, monomer impurities, initiator charge and properties, temperature control profile, etc., the process is extremely complex and it is difficult to achieve an optimum operation of the process.  
      The suspension polymerization process uses a reactor which includes an agitator to facilitate improved monomer/water dispersion. Most current reactors are water-jacketed and lined with glass or stainless steel to minimize polymer buildup on the walls. Typically, a reflux condenser is also used within the process to assist with the removal of heat generated from the highly exothermic polymerization reactions. The process flowsheet of a typical batch suspension PVC reactor  1  is shown in  FIG. 1 . Other types of PVC polymerization processes include mass polymerization and emulsion polymerization.  
      A vinyl chloride monomer (VCM) which includes recovered vinyl chloride monomer (RVCM)  2  is used in the process. The VCM and included RVCM  2  are first finely dispersed in process water  13  by vigorous agitation using agitator  3 . A small amount of primary and/or secondary suspension agents or dispersants  4  such as partially saponified polyvinyl alcohol (PVA) or polyvinyl acetates, are added to control coalescence of the growing grains as a protective coating of polymer is eventually formed. Viscosity changes can be managed with conversion and also injection water, ensuring effective heat transfer to the reactor walls; however, this becomes less important for systems with reflux condensers  5  (since this is where 80% of heat removal occurs).  
      Polymerization is induced by the addition of oil- or monomer-soluble initiators  6  used either alone or in combination with each other. Materials such as those coming from the diacyl peroxide, peroxydicarbonate, azo initiator or alkyl peroxyester groups are initiators commonly employed in suspension or mass polymerization of VCM. Initiators may also be added by batch or while not so common today at a controlled rate during the polymerization process. The reaction takes place in the coalesced monomer droplets. The reactor&#39;s contents are heated to the required temperature by either steam or hot water  7 . Once the initiator(s)  6  begin to decompose into free radicals, polymerization commences. The heat of polymerization is transferred from the monomer droplets to the aqueous phase and then to the reactor wall, which is cooled by water  8  flowing through the reactor&#39;s jacket.  
      The reactor design includes a cooling jacket  9  which may or may not provide the means for all heat removal. If the reactor  1  includes a reflux condenser  5 , it is typically provided as an upper extension to the reactor for condensing monomer vapor generated in the reactor and refluxing the condensed monomer back into the reactor. The reflux condenser  5  will remove most of the heat. If only a jacket  9  is used, chilled water  8  will normally be used in the jacket  9  unless the cooling jacket  9  is very efficient.  
      When the free liquid monomer has been consumed, the pressure in the reactor  1  begins to fall as a result of free monomer being consumed in the liquid phase and increased monomer mass transfer from the vapor phase to the polymer phase due to a sub-saturation condition. In industrial PVC production, the reaction is usually stopped when the pressure drops a certain amount. Since PVC is mostly insoluble in its own monomer, once the polymer chains are first generated, they precipitate immediately to form two separate phases in the polymerization droplet (the polymer and an entrapped monomer phase). Reactions continue in both the free liquid monomer phase and the entrapped monomer phase dispersed about the formed polymer. When polymerization is complete, the polymer is in the form of a colloid consisting of spherical particles dispersed in water. If the polymerization conditions are properly chosen through the course of the batch, a polymer having extremely narrow particle-size distributions can be obtained.  
      Suspension polymerization can be carried to 84% to 88% conversion, under proper pressure and temperature by using oil-soluble initiators. The final conversion determines the finished polymer properties. The reaction temperature is used for molecular weight control. Sometimes, a chain transfer agent may be added to control molecular weight in the free radical polymerization. Polymerization inhibitors may also be used in this system for control of polymerization reactions, kill agents if needed in highly unusual circumstances to immediately stop the reaction and end stop agents at the end of the batch to bring the polymerization reactions to a controlled stop. Typical polymerization times can vary between 3.5 to 6 hours, depending on the molecular weight of the polymer resin being prepared, as well as the heat-removal capacity of the reactor system. After completion of the batch, the mixture (polymer slurry)  11  is transferred to a blow-down vessel (not shown) where unreacted vinyl chloride is recovered. The PVC slurry  11  is then stripped, dried, and stored.  
      The prior art has dealt mostly with the real-time control of certain parameters within the PVC polymerization process. For example, U.S. Pat. No. 6,106,785 and U.S. Pat. No. 6,440,374 each describe a batch polymerization process controller that uses inferential sensing to determine the integral reaction heat. The integral reaction heat is used to estimate the degree of polymerization which has occurred in the batch reactor. The integral reaction heat can be used in either a feedback mode where it is the direct controlled variable or a feedforward mode where another variable such as reaction temperature is the direct controlled variable. In whatever mode used, the reaction heat tends to be a poor measurement of the degree of polymerization since heats of reaction vary depending upon chain length, the degree of cross-linking and the amount of heat holdup within the reaction vessel which is also affected by heat transfer resistances to the jacket and reflux condenser. Therefore the prior art suffers since it does not provide an ability to backward correlate the degree of polymerization to these other parameters.  
      Furthermore, the prior art is focused upon maintaining or regulating a particular “desired” value assigned “a priori” to either the integral reaction heat or reaction temperature without focusing upon a better determination of an improved control target of these values based upon a multiple number of other factors. Such factors that can affect the “desired” values include the amount and impurities of monomer charged to the reactor; the amount, time and activity of initiator(s) charged to the reactor; the amount and impurities of water charged to the reactor; the heat exchange coefficients for the jacket and reflux condenser; the remaining time to batch completion; etc. In fact, all parameters will affect the desired temperature target not only for instantaneous control of the reactor but how to best control the reactor over the remaining time of the batch.  
      In contrast to the polymerization process controller described in the prior art it is desirable to optimally determine all factors affecting the finished polymer prior to initiating the batch, using these optimized parameters in setting up and starting the batch, in an on-line procedure for correcting assumptions made in the optimal determination based upon measurement responses from batch startup, and in an on-line procedure that periodically executes to determine and adapt reactor temperature control profiles across the remaining life of the batch (also estimated by the procedure) to achieve the desired polymer properties and optimal polymer yield. The present invention meets these requirements.  
     SUMMARY OF THE INVENTION  
      In a polymer plant a method that comprises: 
          creating an initial model of a polymer batch process run in the plant;     characterizing the initial model based on past operation of the batch process; and     using the characterized model to perform dynamic optimization of a batch to be run in the polymer batch process.        

      In a polymer plant a method that comprises: 
          collecting data from a batch run in a polymer batch process in the plant; and     performing after the data is collected a dynamic reconciliation and parameter estimation for providing both reconciled data and a tuned model for the process.        

      In a polymer plant a method that comprises: 
          collecting data from a batch run in a polymer batch process in the plant for one or more predetermined periods of time;     initializing from the data and a tuned model for the process the state variables of the batch; and     performing on-line optimization of process variables of the batch run in the process.        

      A polymer plant that comprises: 
          a computing device for optimizing a batch run in a polymer batch process in the plant, the computing device either:     for determining optimal performance of the polymer batch process by executing one or more optimizations selected from:     a dynamic optimization of a batch to be run in the polymer batch process;     on-line optimization of process variables of a batch run in the process; and     an optimization to determine if any of the equipment used within the process should be cleaned; or for performing after data is collected from a batch run in the process a dynamic reconciliation and parameter estimation for providing both reconciled data and a tuned model for the process.       

    
    
     DESCRIPTION OF THE DRAWING  
       FIG. 1  shows a process flowsheet for a typical batch suspension PVC reactor.  
       FIG. 2  shows a block diagram of how the present invention of the performs its PVC reactor optimization and quality control functions.  
       FIG. 3  shows a flowchart for the pre-batch off-line optimization phase of the present invention.  
       FIG. 4  shows the elements of the pre-batch optimization in the flowchart of  FIG. 3 .  
       FIG. 5  shows a flowchart for the batch characterization part of the on-line phase of the present invention.  
       FIG. 6  shows the elements associated with the batch characterization in the flowchart of  FIG. 5 .  
       FIGS. 7   a  and  7   b  show a flowchart for the on-line optimization of the on-line phase of the present invention.  
       FIG. 8  shows the elements associated with the on-line optimization in the flowchart of  FIG. 7   a.    
       FIG. 9  shows a flowchart for the reactor cleaning optimization of the post batch phase of the present invention.  
       FIG. 10  shows the elements of the reactor cleaning optimization in the flowchart of  FIG. 9 . 
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENT(S)  
      Referring now to  FIG. 2 , there is shown a block diagram of how the technique  10  of the present invention performs its PVC reactor optimization and quality control functions. The technique of the present invention can be performed in a computing device such as a supervisory computer platform or a distributed control system (not shown) and is divided into three phases, namely pre-batch off-line phase  12 , on-line phase  14  and post-batch off-line phase  16  as is shown in  FIG. 2 .  
      In pre-batch off-line phase  12  the off-line reaction optimizer is executed to determine how to load the reactor  18  shown symbolically in  FIG. 2 . Phase  12  starts with an initial model  12   a  of the PVC reaction process. The initial model  12   a  is created using one of a number of commercially available process modeling packages. In estimation  12   b  raw data from the reactor  18  and if available properties from a laboratory analysis from one or more prior PVC batches may be used to characterize the initial model  12   a , that is establish the model parameters, to arrive at pre-batch model  12   c . Off-line optimization  12   d  which has many uses is then used to establish the recipe to be used. The existing batch recipe is used if the pre-batch off-line phase  12  is performed weeks before the start of the on-line phase  14 . A new or updated recipe for the batch is used if the pre-batch off-line phase  12  is performed just before the start of the on-line phase  14 . Off-line optimization may also be used to perform dynamic optimization of more than one batch to be run in the polymer process.  
      The reactor  18  is loaded using the recommendations of the off-line phase  12 . The reactor  18  is started after it is loaded and controlled at the temperature profile provided by the off-line phase  12 .  
      The technique then enters the on-line phase  14  where on-line dynamic reconciliation and parameter estimation  14   a  is performed. Up to this point in the technique assumptions on model parameters, efficiencies of initiator(s), VCM and water impurities, etc. have been made in the recipe. On-line dynamic reconciliation and parameter estimation  14   a  is used to correct for errors in these assumptions. Since the present invention is concerned with dynamic reconciliation and parameter estimation the corrections are performed by  14   a  only after the process has run for some time collecting measurements from its start, for example, fifteen minutes or one half hour. The technique of the present invention can perform this dynamic correction either only once or on scheduled cycles. Measurements of the PVC reaction process in operation are taken and are used in the on-line dynamic reconciliation and parameter estimation  14   a.    
      The end results of the dynamic reconciliation and parameter estimation is reconciled plant data  14   b  and a tuned on-line model  14   c . That model is used in an on-line optimization  14   d  of the process as for example to check for and control run away temperatures in reactor  18  and determine the end time of the batch. The on-line optimization may be performed one time or may be periodically scheduled over the course of the batch.  
      Once the batch is complete the technique  10  enters the post-batch off-line phase  16  where the reactor cleaning optimizer  16   a  is executed to determine if any of the equipment used with the batch such as reactor  18  should or should not be cleaned. If optimizer  16   a  determines that the reactor  18  should not be cleaned then the tuned on-line model  14   c  is transferred to the pre-batch model  12   c  to become that model for the next batch to be made in reactor  18  and the heat exchange coefficient for reactor  18  calculated during on-line phase  14  is used for the next batch. If optimizer  16   a  determines that the reactor  18  should be cleaned then the tuned on-line model  14   c  is transferred to the pre-batch model  12   c  to become that model for the next batch to be made in reactor  18  and the clean heat exchange coefficient for reactor  18  is used for the next batch. Thus the technique  10  will use the tuned on-line model  14   c  for the prior batch as the pre-batch model  12   c  for the next batch as long as that model is available.  
      Referring now to  FIG. 3  there is shown a complete flowchart for the pre-batch off-line optimization phase  12  of technique  10 . Phase  12  starts in  20  with the collection of the starting batch information such as initiator type and quantity available, fresh and recovered VCM properties and availability. The phase in  22  then initializes the batch by identifying the state variables.  
      The phase then proceeds in  24  to identify the: 
          a. the raw material values and availablity;     b. the value of the finished polymer;     c. final polymer product properties; and     d. other constraints such as cooling water availability and temperature.        

      Phase  12  then proceeds to  26  where it executes the optimization of the pre-batch model. The optimization results are then in  28  sent to the operator for inspection. If in  30  the optimization results are rejected the existing recipe is used in  32 . If in  30  the optimization results are accepted an updated recipe is used in  34 . The operator may accept the optimization results if based on experience the results seem reasonable or the results may be automatically rejected in the event of a failure code from the optimizer such as an over-constrained problem.  
      After the recipe is selected the batch is started in  36  and the technique enters the on-line phase  14 .  
      Referring now to  FIG. 4 , there are shown the elements of the pre-batch optimization  26  in the flowchart of  FIG. 3 . As is shown in  FIG. 4 , pre-batch optimization includes the determination in  26   a  of the decision variables by maximizing or minimizing one of the objective functions of  26   c  as constrained by the variables identified in  26   b . The decision variables include for example the amount of PVC reaction initiator charge and the charge time, the ratio between vinyl chloride monomer (VCM) and water in the reactor  18 , and predetermined process conditions such as the reactor fill amount and the temperature profile or any other material charged to the batch such as primary and secondary suspension agents, inhibitors, time and amount of end stop, etc. The constraint variables include the availability of cooling water, the path polymer properties which are the properties of the polymer as it is being developed during the batch and final polymer properties, the capacity of reactor  18  and the process constraints such as pressure, temperature and level. The objective function is the economic objective to be met by the plant for this batch or the polymer produced by the plant. That objective may be either to minimize the cost of the process or maximize the profit from the batch or the polymer.  
      Referring now to  FIG. 5 , there is shown a flowchart for the batch characterization part of the on-line phase  14  of technique  10 . As was described above, since the present invention is concerned with dynamic reconciliation and parameter estimation the corrections are performed by  14   a  of  FIG. 2  only after the process has run for some time as measured from its start, for example, fifteen minutes or one half hour.  FIG. 5  shows a loop  40  comprising batch processing  40   a  and time to execute decision  40   b  the purpose of which is to allow the process to run from start for a predetermined time before dynamic reconciliation and parameter estimation corrections are performed. If  40   b  determines that the time to execute has not yet expired loop  40  continues. Data from the batch processing is stored in data historian  42 . When decision  40   b  determines that the predetermined running time has expired the batch is characterized in  44  using the data stored in historian  42 .  
      After the batch is characterized in  44  the technique proceeds to decision  46  where it determines if the operator has the option to either validate the results of the characterization or input different results. If the operator does not have the option the technique proceeds to  48  and then to  50  where the model parameters are updated.  
      If decision  46  determines that the operator has the option to validate the results or input different results the technique proceeds to  52  where the optimization results are sent to the operator for inspection and then to  54  for operator entry and then to decision  56  to determine if the operator does or does not accept the results. As described above if the operator accepts the optimization results then the model parameters are updated at  50 . If the operator does not accept the optimization results then the model parameters are not updated. In either case the technique for the on-line phase proceeds to the on-line optimization  14   d.    
      Referring now to  FIG. 6  there are shown the elements associated with batch characterization  44  in the flowchart of  FIG. 5 . As is shown in  FIG. 6 , batch characterization  44  uses the raw plant data from historian  42  to characterize in  44   c  the estimated variables in consideration of the measurement variables  44   a  and the controlled variables  44   b . The measurement variables, which are the process response data, include for example the temperature and pressure of reactor  18 , and the temperature(s) and flowrate(s) of the cooling water for reactor  18 . The controlled variables, which are the changes invoked on the process, include for example the temperature target for reactor  18  and other controller targets. The estimated variables include for example measurement errors, heat transfer coefficients, initiator activity(ies) and other estimated variables.  
      Referring now to  FIGS. 7   a  and  7   b  there is shown a flowchart  60  for the on-line optimization  14   d  of on-line phase  14 . As was described above in connection with  FIG. 2 , on-line optimization  14   d  may be performed one time or periodically scheduled over periodically scheduled over the course of the batch and uses the tuned on-line model  14   c . Therefore flowchart  60  which shows a periodic scheduling of the optimization first asks in decision  62  if it is time to execute the on-line optimization  14   d . If the answer is no, the technique continues to execute loop  64  until it is time to execute the on-line optimization  14   d.    
      If the answer to decision  62  is yes, the flowchart  60  proceeds to  68  where the post estimation state variables are identified and then to  70  which represents the function of block  14   d  of  FIG. 2  where the on-line optimization is performed. After the on-line optimization is performed, flowchart  60  proceeds to decision  72  where it determines if the operator has the option to validate the results.  
      If the operator does not have the option, the flowchart  60  proceeds to  76  where the control targets are updated. If the operator has the option, the results of the on-line optimization are at  78  sent to the operator for inspection and at  80  the operator makes an entry to either accept or reject the results.  
      The flowchart then proceeds to decision  74  where it is determined if the operator has or has not accepted the results of the on-line optimization and as described above to  76  where the control targets are updated if the operator has accepted the results of the optimization. If  74  determines that the operator has not accepted the results of the optimization the flowchart  60  proceeds to  82  in  FIG. 7   b  where there is a delay representing the time interval between periodic execution of the on-line optimization procedure. After the end of the delay, flowchart  60  proceeds to decision  66  where it is determined if the batch is or is not ended. If the batch has not ended, the flowchart  60  returns to  FIG. 7   a  to enter another cycle of on-line optimization. If the batch has ended the technique proceeds to post-batch off-line phase  16  where it is determined as is described below if the reactor  18  should or should not be cleaned before the start of the next batch.  
      Referring now to  FIG. 8 , there is shown the elements associated with on-line optimization  70  in flowchart  60  of  FIG. 7   a . As is shown in  FIG. 8 , on-line optimization includes the determination in  70   a  of the decision variables guided by an objective function  70   c  that is structured to prevent reactor temperature excursions and determine the optimal reaction end-time as constrained by the variables identified in  70   b . The decision variables include for example the water injection rate, amount and time of end-stop addition (the addition of an agent to slow the speed at which the batch reacts) and in extreme circumstances the amount of kill reaction addition. The constraint variables include the reactor temperature.  
      As was described above in connection with  FIG. 7   b , after decision  66  has determined that the batch in reactor  18  has ended, the technique proceeds to post-batch off-line phase  16 . Referring now to  FIG. 9 , there is shown a flowchart for the reactor cleaning optimization  16   a  of phase  16 . As is shown at  84  the operator is asked if the reactor cleaning optimization should be run. The operator makes an entry at  86  and decision  88  determines if the operator&#39;s entry is to run or not to run the reactor cleaning optimization, the elements of which are shown in  FIG. 10  to be described below. If the operator&#39;s entry is to the reactor cleaning optimization, the technique proceeds to  90  where that routine is run and a recommendation is made in  92  for cleaning of reactor  18 .  
      Referring now to  FIG. 10 , there is shown the elements of reactor cleaning optimization  90  of  FIG. 10 . As is shown in  FIG. 10 , reactor cleaning optimization includes the determination in  90   a  of the decision variables by maximizing or minimizing one of the objective functions of  90   c  as constrained by the variables identified in  90   b . The decision variables include for example the time to clean the reactor. The constraint variables include for example the heat transfer coefficients and availability of other reactors for producing needed polymer. The objective function is the most favorable economic objective to be met by the plant. That objective may be either to minimize the cost of the plant or maximize the profit from the plant.  
      While the present invention has been described in connection with the suspension batch production of PVC it should be appreciated that it can be used in other types of batch production of PVC as well as batch production of other polymers. While the present invention is described above in the context of a single batch it should be appreciated that the off-line optimization  12   d , the on-line optimization  14   d  and the reactor cleaning optimization  16   a  all of  FIG. 2  may each be performed simultaneously for one or more than one reactor systems.  
      It is to be understood that the description of the preferred embodiment(s) is (are) intended to be only illustrative, rather than exhaustive, of the present invention. Those of ordinary skill will be able to make certain additions, deletions, and/or modifications to the embodiment(s) of the disclosed subject matter without departing from the spirit of the invention or its scope, as defined by the appended claims.