Control of polymerization processes

Copyright

© IFAC

PRP 4 Automation, Ghent, Belgium 1980

Session 7

CONTROL OF POLYMERIZATION PROCESSES K. Hoogendoorn* and R. Shaw** *Department of Mathematics and Process Control, DSM, Geleen, The Netherlands **Plastics Division, ICI, Welwyn Garden City, UK

Abstract. This paper presents a survey of the control of commercial continuous and batch polymerization plants, by conventional means as well as with the help of processcomputers, PLC's and microcomputers. Kel!0rds. Application, chemical industry, computercontrol, composition control plastic~~industr~, optimal control, regulatory control, safety, temperature control.

INTRODUCTION Automation of polymer plants did not receive attention for rather a long time. This situation changed in 1970, when reports came out of a number of spectacular sequence control applications in PVC-plants. At the third PRP Congress, Amrehn (1977) reported on the situation as regards large-scale process computer applications. Now that both large and small-scale automation has become possible, it is to be expected that all types of application will be succesful. At the same time, the borderline between computer controlled automation and conventional processcontrol will fade away. This survey reviews a number of application areas that have now become important.

CONrROL OF BATCH :'PERATIONS In many polymer plants, batchwise operation is applied for some process units. Examples in point are: - catalyst preparation units - reactor or reactor-trains - homogenization and mixing units - loading bunker3. Often, units operated batchwise alterate with continuously-operated ones. In the past decade, the large-scale automation of batch-reactors has been receiving much attention. Also the control of processes applied to products available as powder or granules has proved important.

MOTIVES FOR AUTOMATION A reactor section operated batchwise may be automated for a variety of reasons, of which we may mention: 1. Saving of manpower. 2. Improving product consistency through uniform operation or better control, leading to fewer batches differing unallowably from the standard specification. 3. The possibility of shortening batch cycle times through elimination of improductive time, and hence increase of production. 4. Improved safety through better interlocking and process monitoring. 5. Logging for process development and trouble shooting. 6. The possibility of so scheduling the operation of parallel reactors that optimum use can be made of common equipment. 7. Saving of feedstocks, utilities or auxiliaries. 8. The flexibility enabling other, more complex, control strategies to be applied, possibly induced by different mode of operation as a result of d9bottlenecking. 9. The possibility to adapt feedrates to experience gained in previous batch runs. 10. Saving on cost of instrumentation or instrument maintainance. 11. Accelerated start-up of a newly constructed plant or process. 12. Saving on staff capacity. 13. Possibility to vary the batch output volume in a simple way. Table 1 indicates to what extend the above motives are mentioned by some authors on this subject.

624

K. Hoogendoorn and R. Shaw

iAuthor

Ref.

Allen Tsai Gran Winkier, Alllrehn Uhlig Moll, Doclo Luethy Law, Moloney Nakagawa Nisenfeld Hoogendoorn, Nap

1977 1976 1976 1970 1977 1976 1976 1971 1970 1975 1976

Motive: 1

2

5~

X

3

4

5

15-20%

X

5-1~

X

7

6

8

9

10

11

12

13 X

X 3~

X

X X

8.5% 2a:t X

X X

X

X

X ----

X

-

X

X X

X

X

1a:t

X

X X X

X

5-1a:t

6a:t

10%

6.5%

X

-- ----

X X

L- _ _ _

Most of the above mentioned motives apply also to batch homogenization, blending and transportation systems. Only in this case the accent is more on the avoidence of mistakes leading to off-spec production, less on safety aspects.

CONVENTIONAL BJ\TClIREi\CTOR CONTROLS The firs t mode of automa ti.on appl ied in ba tch production plants in the late 1950's was remote control. Local operation by means of hand wheels and local reading of process data was ousted by centralized control from one controlstation. The operator runs the plant by means of push-button system~, lamps in graphic panels indicating situations in the plant and audiovisual signals indicating that a limit value is exceeded and action is required. The switch-over from completely local to central control is essential to further automation; it is a very heavy cost factor. It should be added that co~plete automation is not always possible because certain actions cannot be automated in a simple way (e.g,. cleaning a reactor after a batch production run). The second step in automation might then be to relieve the operators of the routine jobs in the control room, by introducing sequencers with relays, counters and timers, or by applying solid-state sequencing logic (early 1960's) Recipe-dependence is introduced by means of cards or punched tapes. When applicable, setpoint profiles are fixed by means of cam-set controllers'. In the past this procedure -which we wiJI not deal with in too much detail- has actually been applied. lIowever, such systems have little flexibility and are difficult to maintain, and it is precisely these aspects which weigh hea~ vily in polymer production processes. Therefore, modern batch production plants nowadays use digital processors (microcomputers PLC's or minicomputers) for sequence control.

CONTROL BY MICROCOMPUTERS, PLC'S AND PC'S The microcomputer may he viewed as a small version of the minicomputer, which will be discussed in the next chapter. In general, a microcomputer will be assigned only one program taSk, whereas a minicomputer can handle several. Reprogramming will be needod less in the case of a microcomnuter system than for

30-50% X

-

--

minicomputers. Therefore, the micru primarily fills the gap between the simple instrument and the mini and is used to replace equipment items conventionally employed. In batch production plants these might be PID-controllers, metering devices, weighers, equipment for processing analysis results, set-point programmers, etc. Some of these pieces of equipment complete with microcomputers can be bought on the market, as is the case with weighers, comprising automatic taring and the sequence logic needed in portioning. It is to be expected that makers of measuring and control instuments for this area of ope~ ration will come forward with numerous new developments programmed ready for use. At this moment there is still a shortage of communication means capable of operating between fully microbased systems on the oue hand and minicomputers on the other. Possibly, the recently proposed process data highway (PROWAY) for distributed process control systems will fill this gap (IEC,1979) For many sequence control problems the programmable logic controller (PLC) provides a good intermediate solution. PLC's can be made with up to 256 digital inputs and outputs. They are very suitable notably for bunker control and control of final processing operations, but then lack the capability of supplying the operator with reliable data on process situations. An advantage is that most types can easily be programmed by means of ladder diagrams. However, they cannot be used for regulatory control. ~he last remark does not apply to a development of the PLC, namely the programmable controller (PC), which also contains analog inputs and outputs. The system may have up to 512 di~ital inputs and outputs and 32 analog ones. Also, the PC can communicate with a computer. In that case a minicomputer can be used as a means of communication between several pc's linked up to it, and as the central channel for communication to the operator. It is possible then to provide a number of reactor trains, or even individual reactor~ with PC's and to entrust the coordination to a minicomputer (Nisenfeld,1976). The same layout may be used where control is effected individually for each unit by means of small minicomputers (or big microcomputers) (Moloney,1976). Care should be taken to ensure compatibility between different system items.

Control of Polymerization Processes

CONTROL BY (MINI)PROCESS COMPUTERS This subject has been widely dealt with in literature (Tsai,1976; Winkler,1970; MOll,1976 Amrehn,1977; Hoogendoorn,1976). The technique developed through the late 1960's has now become a proven one. The main factor is the development and support of the appli~ cation software in the form of sequence descriptions. Tsai (1976) makes mention of a serious underestimation of the time needed to analyze a process to the necessary extend to ensure minimum batch runtime and maximum safety. The time devoted to process analysis is distinctly longer than the time consumed by programming for a known process or for correcting a program. Further simplification of the programming is required along the lines of present table-driven sequence programming methods. Also the back-up problems require much attention. A hierarchic build-up of the system, as outlined above, will solve many of the problems involved, perhaps with duplication of control at critical points. A point of great importance remains the presentation to the operator. The use of "full-graphic" colour screens is now common; however, there is still no concensus about the contents of the information to be presented. The ergonomics of display have also received attention ('Rijnsdorp and Ronse, 1977; Kortlandt and Kragt, 1978). CONTROL OF BATCH POLYMERIZATION REACTORS The control of the reaction conditions (temperature, sometimes pressure) can in many cases be subdivided into three phases: a) Determination of the optimum profile of the control variables throughout the batch runtime. Often this results in one (or more) stationary phases which have to be reached as quick as possible; see Fig. 1. b) minimization of the duration of the transition nhase without 0vershoot to the stationary phase. c) the closest possible adherence to the desirable profile in the stationary phase. Often, different controllers are used for the two phases (the "dual-mode control" concept). Optimizing control The control variables can, in principle, be so altered during a batchrun that the runtime is minimized. Of course, this can be done only within certain limits. Hicks, Mohan and Ray (1969) have posed and solved this problem for various types of polymerization reactions, assuming ideal temperature control. Marroquin and Luyben (1973) have derived optimum temperature profiles, assuming realistic kinetic behaviour, using reactor models. In the case of irreversible reactions little time can he gained with time-optimum operation, because the maximum allowable temperature has to be

625

used throughout. Clough and others (1978) determined the optimum profiles of temperature and catalyst feed for the solution polymerization of styrene. The off-line calculations gave profiles that were in good agreement with those commonly practiced. Gran (1974,1976) based his considerations on the supposition that not only should a maximum temperature be adhered to, but the reaction temperature averaged over the whole of the polymerization phase should have a given value. This results in an interesting profile. In his latest publication this author obeys three constraints, viz. a mean reaction temperature a profile for the maximum reaction tempe- ' rature, and a profile for the desirable reserve cooling capacity. In the final part of the batchrun the reactor temperature is not subject to any constraint. The profiles were determined empirically. They are dictated i.a. by safety considerations and by the objective of shortening batchrun times. The corresponding behaviour is illustrated in Fig. 2. Although there is only one practical application at present, it is to be expected that the present pragmatic determination of profiles will continu to be used.

During the heating phase the controller sees to it that the temperature is raised to the desired value as rapidly as possible, while preventing temperature overshoot, which means that the rate of temperature rise becomes zero as soon as the target temperature has been reached. If these requirements are satisfied, the steady-state control mechanism is not unduly loaded at the moment the equipment is started. Therefore, it can be given optimum controller settings for the stationary phase. The systems for control of the heating phase are non-linear in character; often, use is made of bang-bang control. (Fig. 3) In all of the cases shown, heating to maximum temperature is the first step. Thereafter the stationary-phase control can be switched on as soon as the temperature has approached the set point closely enough (first switching point, Ta). It is wiser, however to wait somewhat longer, as is illustrated by Nakagawa's delay time forcast circuit (Fig. 3b). The stationary phase is reached even more quickly if after the heating phase cooling is applied for a given time (Fig. 3c). Amrehn further improved the transition to the steady-state situation, calculating the setpoint of the cooling water temperature from a heat balance (Fig. 3d). All this procedures were established empirically, Slangen (1978) applied Pontryagin's maximum principle to the problem, starting from a 4 th-order process model. His result is a bang-bang control system with two switching points (Fig. 3e and 4). The time between the first and second switch was very short (7 sec.) He also derived a sub-optimum controller with

626

K. Hoogendoorn and R. Shaw

one switching point, which strongly resembles Amrehn's. The optimum control offers less than ! % gain in time as compared with the control used in practice. However, it does result in a lower degree of conversion at the end of the startup phase, which might be important in view of product properties.

Stabilizing control An exothermic batch reactor is, in general, open-Ioop-unstable , but can be stabilised, in some cases even by means of a proportional controller (Luyben,1975); however, in most cases derivative action is required also. If well set, such a controller will perform excellently. For very big reactors with parameters varying strongly within a batch run it may be desirable to apply not only feed-back but also feed-forward control. Nakagawa (1970) makes corrections for the known variations of the heat of reaction and for the heat-transfer coefficient on the basis of a heat-balance calculation. In this way he corrects for the strong increase of the reaction heat towards the end of the batch run (Tromsdorff-effect). Other authors (Adams and Schooley,1969; Kennedy, 1976) use for this control a model in which one or more parameters are updated. Such feed-forward controls have not been widely adapted in practice, however. Table 2 gives a review of literature on the control of batch (polymerization) reactors, arranged by subject. TABLE 2 Literature on batch (polymerization) control. Author

StabiliOptimum Control FeedRef. Model forward za tion develop- control of hea ting control control ment ohase

lAmrehn Winkler Marroquin, Luyben !Ham, Liemberg t-topkins ,Alford

1977 1970 1973 1975 1973 1970 1974 1976 1977 1975 1976 1965 1974 1969 1969

~kagawa

ran ~ran

~llen

uyben Kennedy Shinskey "eyes, Kennedy "'lcks. Mohan, Ray ~dams, Schooley

X

X X X

X X X

X X X X

X X X

X

X X

X

X

X X X X

X X X

X

HOMOGENIZIMJ ,BLENDINJ ,COLOURIMJ AND arHER FINAL PROCESSINJ UNITS These units comprise storage, analysis,homogenization and blending bunkers, a possibly pneumatic transport system, extruders for supplying additives and pigments, bagging machines and loading equipment. Controlling the transport from one bunker system to another is generally done from a central control station, which, for ease of reference, may be equipped with graphic panels. The various processing treatments of the polymers are as a rule controlled locally, however.

Use is made of all kind of control systems, working with relay logic, solid-state logic and PLC's, and normally supplied by the makers of the machines (packaged units). The principal task of an overall automation system here is monitoring, interlocking, and coordination, as transportation and processing errors may lead to one product type contaminating another, so that the value of the output may be affected considerably. The first step in automation is feeding to a computer data on the state of switches and valves, and of the volumes and types of product contained in bunkers. When an action is to be undertaken, the operator communicates to the computer what he intends to do (e.g. X tons is to go from bunker A to bunker B; X tons from bunker A and Y tons from bunker B are to be blended and stored in bunker C; etc.). The computer now finns out what is the best route, taking into account current actions and deciding whether or not the order can be carried out immediately, and advises the operator. The operator considers the advice, makes quantity settings, opens and closes valves as required, and starts the transport process. The computer can then monitor the transport. A second step would be to have the computer itself carry out (or initiate) the control, for instance after the operator has approved the choice made by the computer. In a third step, only the intended result of an action is communicated to the computer. For instance, the operator communicates to the computer that he needs X tons of product i, treated according recipe j. The computer now chooses the source bunkers and destination bUnkers, computes the amounts to be supplied, and sets the appropriate routes again after having invited the operator's approval. Several commands may be given simultaneously; the computer will determine the best sequence of dealing with them. In many cases the computer needs to be informed on product properties. These are determined from samples drawn from a bunker after the polymerization unit. The results are fed into the computer from the laboratory. If on-line quality measuring equipment has been installed, the computer can continuously det~rmine polymer quality, so that no analysis bunkers need to be used. If the on-line data should indicate that a batch to be produced is suiIiciently homogeneous, the energy normally required for homogenization can be saved, and the batch sent direct to storage. Often, computers of this type also serve for "management information" The computer has a fairly accurate knowledge of the product property of every lot made, and of the treatments the product has undergone. This information is every day printed out for use by the sales planning department and for later customer queries. In a simular way, information on product stocks may be supplied by the computer.

Control of Polymerization Processes

627

This test project was set up with the object of obtaining experience in making failure SAFETY ASPECTS OF THE AUTOMATION analysis for batch processes and discovering OF BATCH PLANTS weaknesses possibly contained in this rather old and drastically altered design. Also in the reactor section of batch polymerThe study comprised the following steps: ization plants safety is an important consia- Re-consideration of the design philosophy appl ierl, notably as regard the computer deration, as the reactions here are exothermic, 0ontrol system. often large quantities of combustible or toxic materials are contained in the equipment, and b- A step-by-step examination of the sequence a multiplicity of actions have to be performed description, to discover all potentially dangerous situations and take necessary during a batchrun. Equipment failures and operating errors may lead to wrong connections and action; this was done by the ICI method. hence to highly undesirable situations. c- Checking on all failures that m-6ht occur in the computer-process interface, and on In the past, batch polymerization reactors, all passible cOllsequences next, finding out like all other processequipment items, have been provided with mechanical safety devices, ways for automatic detection of such failures· this, too ~~s done by the ICI method. ' such as spring-loaded protection devices, d- Checking on all failures which might occur blow-off systems, and rupture discs, as an in the computer and lead to no-detection of ultimate protection against calamities. Still a wrong situation or erroneous functioning; in many cases these provisions are inadequate. To supplement them, use has come to be made of finding ways for automatic detection of such failures. protection instrumentation, for the final Some conclusions that can be drawn from this detection of irregularities and, if necessary, study are: termination of the process. Such devices will; 1) Not all of the changes made in the control for instance, supply a "stopper" when temperature or pressure in a reactor threaten to system as a consequence of the many improvements on the original process were in become too high. In addition, it is possible accordance with the original control phito interlock valves to prevent wrong actions losophy. by an operator. 2) Automatic operation is safer than manual Such a safety logic system should, however, operation, because the many interlocks by take due account of the phase which a process the computer are not backed-up by convenmay have reached. tional logic; it should even be asked whether If, therefore for any of the reasons mentioned manual operation is to be allowed at all. above, a change-over to automatic control is 3) Permanent monitoring of the status of critimade,care must be taken to study the separate cal valves, a feature included in later requirements of control automation and satety systems, is essential (meanwhile this prooperations if these use the same equipment. vision has been introduced). Even so, there will remain a small, residual, 4) The system's disc memory, containing all chance of control errors, e.g. if a relay in recipes and unit addresses, is a very crithe systemdoes not work properly. tical part; therefore, the data in unit and This residual chance of malfunctioning may be recipe records have been assigned a checkfurther minimized by careful design of the sum. After a record has been read in, the control system, using fail-safe characteristics checksum is computed again, and if it is wherever possible. If, to enhance flexibility found to be different from the one stored or because of a wish to sophisticated monitorin the disc memory, the system is stopped. ing (e.g. on the basis of calculated parameters), control by digital computer is opted for, it 5) The same provision has been made in respect of core-resident files, containing the bits will be necessary also to minimize the residual of digital inputs and outputs. chance of operating failures. The last mentioned provisions have now made The electronics of a digital computer being this computer control system as safe as it can rather complex, what is called for is a sound be. analysis of all possible errors and failures designers (Quietzsch,1979). The result of such an analysis We feel that, like PLC designers, can then be used in making suitable provisions. of process computers and process interface Often, one of these provisions takes the form of equipment ought to pay due attention to these a back-up computer. The improved availability of safety techniques, and have all hardware and software errors in computer and interface the system is believed to result in improved safety. In a sense, this is true. The non-avail- detected in the computer. ability of a computer entails the cut-out of In commercially available systems this aspect part of the process control, which makes the receives too little attention. Any designer of process less safe. However, it should be borne a system for the control of batch polyrnerizations in mind that with or without a back-up computer really ought to perform an analysis as described detection of computer mal-functioning is vital. above. Analysis of potential failures is best performed as a hazard-and-operability study of the entire system, including processinstrumentation and CONTROL OF CONrINEOUS POLYMERIZATION control. One form such a study might take is PROCESSES described in a ICI publication (Knowlton,1976). DSM has made a study of this type for an Contineous polymerization processes differ from automated batch polymerization process. other chemical processes in the following

628

K. Hoogendoorn and R. Shaw

respects: a- on-line quali~y inspection and control is difficult. b- there are periodical changes in productgrade -a different grade sometimes requires different control; some processes also requiI..'e frequent starts and shut-downs. c- polymer flows are viscous, which tends to make measurement and control difficult Most control problems are centred around the reactors. They can be described as follows: 1. What adjustment has to be used to get the desired product quality (the static control problem)? 2. What controls have to be made in order to maintain as best possible the adjustment meant under 1. above (the regulatory control problem)? 3. How is a change in product-grade or a startup to be carried out so that only a minimum of unsaleable product is made (the transition problem)? A more detailed example is described in the section about computer control of polypro~ylene plants.

!he sta !.ic _~ontrol problem For the operation many variables need to be set, e.g.: - monomer feed, - comonomer feed, - supply of diluent, - cooling water flow (or reactor temperature), - modifier supply, - catalyst supply, etc. The setpoints for these variables must result in production of the required amount of product having the composition necessery for satisfying demands in respect of mechanical, optical and processing properties. It is not always possible to translate these requirements into setpoints for variables that are actually controlled, as effects may be unclear or unknown. It has been found, however, that a certain product-grade will result if a number of the variables are set to specific values and others are adjusted to control production volume or product properties. Sometimes the requirements are translated into setpoints for key variables, e.g. monomer concentration in the reactor, conversion, monomer-to-comonomer ratio, etc. It is clear that the recipe determines the greater number of the degrees of freedom of the process. This is the principal reason why optimizing process computers, have rarely been applied in polymer plants. Still, it is useful to control the key variables to the desired values. Often, setpoints can be calculated directly from measured values of process parameters and from the setpoints of key variables and other setpoints In such calculations, account can be taken also of limiting quantities, e.g.a polymer concentration, in the case that plugging occurs if its value becomes too high. It is then possible to apply override control or constraint control so as to prevent constraints being exceeded. Calculation of key variables need not always

be combined with control. A system warning the operator if a variable deviates too far from the setpoint may in many cases have the same effect, if used for instance in combination with a system for data or alarm logging.

The regulatory control problem In general, less then 10 % of all controls of primarily measured quantities present dynamic control problems. One third of them call for a special approach (Ellingsen,1976). Moreover, process designers, assisted by control engineers, can sometimes find a way to avoid dynamic control problems by making process alterations, in spite of the circumstance that "there is much more information available about how to improve the controls than on how to change the process to improve controllability' (Trevathan,1976). Nevertheless, there remain some difficult problems of dynamic control with polymerization reactors. The problem that is easiest to solve is that of reactor temperature control. A process carried out in an autothermic CSTR may have open-loop instability (Hoftijzer and Zwietering,1961), as may a process carried out in a jacked-cooled CSTR. Addition of derivative action to the control will solve this problem, but the tuning of a PIn controller to be used for this purpose is not always a simple matter. Also cascade control may be used in this case (Hopkins,1973). Another problem is bound up with the control of concentrations in the. reactor, e.g. the modifier concentration. However, the control problem that is the most difficult to solve is that presented by the polymer properties, if these are determined only at the end of the process, on samples drawn from an analysis bunker. In making adjustments, the operator will have to exercise caution, in order not to disturb the process too severely. In practice, use is often made of control charts or nomograms (Butchart,1969). Even then, it is frequently impossible to ensure sufficient product homogeneity. Process design engineers normally introduce a bunker arranged after the analysis lJunker, in which a blend is made of a large quantity of product made over a period of many hours. Variations are thus averaged out. For this application there is another control-chart method,viz. the use of the histonomogram. Each time the analysis result for a sample from an analysis bunker is received, an estimate is made of the average value of the product property, and of the corresponding standard deviation resulting from adding the contents of the analysis bunker to the product lot in the blending bunker. If either of the estimates falls outside the specifications set, the contents of the analysis bunker are not added to the product lot. If the average value of the product properties deviates too far from the target value, the operator will take action, so that after some time the target value will be reached again.

Control of Polymerization Processes

COMPUTER CONTROL Process computers are increasingly used in polymerization processes, although they are not yet part of the standard equipment of a plant as is the case in the petrochemical and the paper industry. A European survey (excluding Great Britain) carried out in 1976 with respect to computer application reports 36 systems operational in polymer plants. Most of those were in batch plants. The survey did not cover all applications in operation around 1976 and since then many have been added. Table 3 shows an extract, specified as to the principal applications. TABLE 3

Proc~~~_<2.0mp~ters i~_Polymer

Production Polymer

PVC Polyolefines Polystyrene Polyester Rubber Synth.fibres Miscellaneous Total

Number of computers in operation 11 7 1 4 2 6 5

36

A summary of the experience gained in the various fields, is presented in the following.

Most publications on batch polymerization sequence control are concerned with PVC. The area covered comprises the bulk PVC process (Winkler and Amrehn,1970), the suspension process (Nakagawa,1970; Winkler and Amrehn, 1970; Tsai and Lane,1976; and Gran,1976) as well as the emulsion process (Gran,1976). Amrehn (1977) presents a very good survey of the applications in the field of PVC. Keyes and Kennedy (1974) give a very good description of the control problem in a PVC plant. Tsai (1976) outlines the latest developments for very large reactors. It appears that the dual computer system has persisted, that very much emphasis is put on safety aspects, ~nd that the degree of redundancy in the instrumentation has assumed unprecedentedly high proportions. Very much attention is paid to the quality of the temperature control in these very large reactors. There will be very few new PVC plants by now without computer control.

Polyester In 1971 the first reports appeared about attempts at computer control of both the unsaturated polyester resin process and the satured polyester process. In the following

629

years AlIen (1977) published further details about the first a~~lication. Luethy (1976) points out that computer is also profitable in the case of a small polyester plant, and he emphasizes the flexibility of a batch plant in terms of grade switching as well as of production volume. Here, too, the facility of alteration of control schemes permitted by the computer appeared to be an essential factor. Moloney and Flower (1976) and Moll and Doclo (1976) concluded that computers had become an essential feature of polyester fiber batch production.

Othe~~EElications

in batch production

Other applications of computer control in batch polymer production are in the polyurethane process (Nisenfeld,1975), and in processes for phenol and epoxy resins (Uhlig, 1977). In the latter case, three process computers were installed in a period of 4 years.

Weber (1977) gives a clear description of how the polymer product is passed through a homogenization stage to final processing, and how the homogenization step in itself is controlled. In addition to these control functions, this system yields the maximum quantity of a desired product to a bunker, while the aim is to empty as many bunkers as possible and to minimize the number of transport operations in order to save energy and time. Quietzsch and Hoffman (1976) describe the automation of transport in a number of bunker systems with a mixing station a~d a s~~t~c~ for dissolving of the polymer. Law and Moloney (1974) designed a system for blending of polyester chips from a batch production plant. The properties of each batch are determined in a laboratory and fed to the computer. The computer performs blending calculations and determines to which storage bunker the product can best be discharged. All movements are controlled by an automatic solids transfer manifold system; the number of transport options is so large that only a computer is capable of keeping track. Sequence control and interlocking are not direct computer functions; but are integra ted in a solid sta te logic S:TS tern; the action signals are generated by the computer.

Rubber plants The classic example of computer utilization in rubber plants is the control of the early SBR and BR process reactors (R.C.Smith, 1971; Amrehn, 1976). Ahlberg and Cheyne (1976) describe an interesting application of the extended Kalman filter for identification of a synthetic butyl rubber process. Due to the fouling of the reactor, the heat transfer coefficient changes rather quickly

630

K. Hoogendoorn and R. Shaw

and unpredictably. Moreover, the reactors are cleaned regularly, which means that there is a kind of cyclic opera tion - an addi tional source of fluctuation of the process parameters. Finally, the feed and catalyst flows contain unknown impurities, which may have a long-term influence on productivity and quality, if they accumulate in the reactor system through recycling. A dynamic model was constructed with which the rubber quality and the productivity can be predicted. However, the parameters in this model may vary up to 50 % from the nominal value. With the Kalman filter, these parameters are updated on the basis of process measurements of temperatures, pressures and compositions of the reactor gas. With application of the model thus updated, the process is then adjusted. In this manner it was possible to reduce the standard deviation of the Mooney viscosity by 25 %, to effectuate grade switching 3 times faster, and to raise the production. The Kalman filter is only rarely used in the process industry, because parameter variations as large as described above are exceptional. The paper states that only 5 % of the total research time was spent on the development of the filter, 95 % on the solving of problems with the implementation of all programs within the real-time system. A process computer can also be used in the final processing of a rubber process. In such an application at DSM the computer tracks the bales of rubber down to an automatic box loader. Thus, it is known what specific product is contained in each of the boxes, and the entire transport system is monitored. Part of this function will shortly be taken over by a PLC.

Computers are also increasingly used in the operation of hdpe and pp plants. Amrehn (1977) and Weber (1976) both present a system of melt index control based on a statistical model, which is updated by means of off-line analysis results. Because it is not possible to measure the procuct quality immediately after the reactor, it is desirable to stabilize as many of the relevant variables as possible. Weber (1977) mentions the monomer mass flow control. Of even greater importance is stabilization of the concentrations in the reactor, for instance by controlling the modifier concentration in the reactor (D.E.Smith,1974). This can be done by means of on-line chroIDRtographic analysis of the reactor gas released from the downstream flash tank, with a direct link to the modifier flow itself. For known disturbances in the recycle flows, feed forward corrections can be made. By means of a deterministic process model, which calculates the degree of conversion, and the monomer and comonomer concentrations from primary measurement data, the reactor processes can be additonally stabilized (Buss and coworkers,1976). This example includes an optimizing control scheme which maximizes the polymer production. In the first

place, the production is stabilized by influencing the quantity of monomer, which is determined by the heat balance across the reactor. In addition, it is tried to keep the monomer concentration in the reactor constant by controlling the diluent feed (situation shown in Fig. 5). If the polymer production falls short of the target, or if the monomer or the polymer concentration in the reactor increase beyond the maximum, another control scheme becomes operational. This enables the polymer production to be maximized, while a- excessive monomer concentrations are prevented b- plugging of the reactor is prevented. Such a scheme cannot be used in any hdpe process. Specific process design, identification of the constraints, determination of the optimum control stategy, allowing for the process dynamics will all have to precede the development of that type of control scheme. Kawamura and Mitsugamo (1977) applied the maximum principle of Pontryagin to the gradechange operation in a polypropylene plant. The calculated optimum control stategy for grade shifting was implemented in a process computer. The modifier setpoint is controlled so that the averagp molecular weight of the product which is obtained in the mixing bunker is exactly equal to that of the new grade (see Fig. 6). In this manner it appeared to be possible to fully prevent off-spec product being made in grade shifting.

Low-density

polyet~lene

Low-density polyethylene plant processes are complicated, with hundreds of temperature measurements, the necessity of imposed process perturbations to prevent plugging, and occasional occurence of product decomposition or reactor tripping (Volter,1966). Nevertheless, very little has been published on computer applicattons in this field, although according to the survey at the Florence conference (1976) some lpde plants are equipped with computers. Takahashi (1979) reports feedforward control of temperature and pressure, as well as control of product quality and enlargement of production by means of a process computer, but he does not give any details. Most systems are primarily designed for data logging, not only of measured but also of calculated data, such as conversion and heat transfer coefficient. These data are used in recipe evaluation. When initial sympto~s of decomposition are observed, it may be possible to ascertain the cause from the data stored in the computer memory. In many cases there are frequent product shifts, or the plant is stopped and re-started frequently With this type of plant,t~erefore, it often pays to opt for an automatic start-function, because this may prevent formation of off-spec product and reduces the start-up time. Quality control can be t~sed on computer processing of the data from an on-line melt index meter, a gel counter :Dane,1980), and the like (Butchard,1969).

Control of Polymerization Processes

It is not customary yet, however, to close the quality control loop. Dead time in measurement is certainly an important factor here, but also the complexity of the measurement system, with an availability of about 95 %, plays a role. It is customary, though, to carry out the routing of the product to the various bunkers on the basis of product qUality data, either automatically or via the operator.

Hidden costs In spite of the good results of computer control, cited above, it is necessary to mention the "hidden costs" that show up in the development stage of a project and also within the further life-cycle of a system. -In the design stage: Here a) staff for studies b) staff for complex operability studies, c) training of design project staff and production staff in new technology or maker's computer systems is necessary. These costs are often neglected in feasibili~y studies. -In the investment: Required back-up equipment adds to the normal instrumentation costs as well as extra testing and programm development facilities and spare parts. -In commissioning: Here extra time is necessary for complex commissioning -Support: During the life-cycle of the system, a back-up staff is necessary for ongoing support, besides support staff. This staff is not readily available. Knowledgeable people find more satisfaction in the design and programming of new systems. Another need for extra staff is caused by the flexibility of the computer which may give uncontrolled development of the process.

Some examples of computer con~urations that are installed these da~n polymer plants -Classical dual computer system (Fi~. 7) This configuration has been in use for the past ten years and is still practised. Many alterations have been made also to this scheme. The basic idea is that the hot spare computer takes over control when the control computer fails. This is done by manual intervention and there is a time gap. If the hot spare also fails standby instrumentation ensures a safe shut-down of the plant. -Identical twin system for reaction control (Fig. 8). In this configuration computer A hands over control to identical twin computer B upon detection of any malfunction. This is specially used for the control of exothermic reactions and ensures almost failsafe operation. Computer C controls non-critical parts of the process.

631

-Distributed system (Fig. 9) This configuration may be used in multitrain or multi-reactor plants. Redundancy might be included, but is not indicated. For sequence control tasks a PLC or PC might replace the plant micro. The management computer can load the plant micros down-line. The management and scheduling tasks can be separated again and involve two computers.

MODELS A good control system can only be designed with a thorough knowledge of the process itself. This applies in particular to polymer processes. Basic insight into the process can be strengthened considerably by drawing up met.hematical models. In the case of polymerization reactors, this requires a description of the complex reaction kinetics and often also of the mixing behaviour in the reactors. Given the variables that are to be controlled - including catalyst feed, monomer feed, supply of chain-transfer agent, and, for batch reactors, the heating and cooling pattern - such a model can be used for instance for calculation of the degree of conversion arrived at and of the average mOlee"llar weight. With batch reactors, this is of necessity a dynamic model; for control studies, the dynamic aspect will also be included in the case of continuous reactors. Such models are useful for: a) Designing or debottlenecking of a plant, for instance upscaling of reactors (batch and continuous). b) Study of various control schemes to find out which parameters can best be used for the manipulation of variables to achieve maximum plant stability (the multivariable problem), or to find optimum controller settings, starting from a given control scheme. It is also possi ble to determine the s(~ns i ti vi ty of a control loop to changes in the process and control parameters. c) Training of operators before the plant is put on stream, in order to make them familiar with the consequences of the most important process delays. d) Identifying the consequences of lailures, for instance to find out how much time the operator needs to react when the initiator is too high. If the time is to great, it may be necessary to automate. Most of these dynamic simulation models are used off-line. Parts of such models can also be used on-line, as control model, with utilization of measurement data from the plant. It is important then to take into careful consideration how sensitive the model is to inaccuracies in the measurement data in order to arrive at a realistic assessment of the usefulness of a proposed on-line model. In the sixties there was an exaggerated interest in on-line models, followed by disappointment, and a shift of attention to forms of computerization in the seventies. It may be

K. Hoogendoorn and R. Shaw

632

expected that the eighties will see a balanced and selective use of on-line models. As an illustration of the model applications meant under b), Fig. 10 shows the effect of the pre-lo?d temperature on the control behaviour; the applications under d) are illustrated with a simulation of the effect of various initiator feed values as a percentage of the nominal value on the control behaviour of a batch reactor (Fig. 11).

I NSTRUl\ffiNI'AT ION In instrumentation there is a clear trend toward electronics. Fig. 12 gives our estimation of newly built polymer plants that are controlled pneumatically.

MEASUREMENT PROBLEMS Measuring instruments in a polymer plant are often the weakest links in a control circuit. This is bound up with the viscous nature of the principal process flows or with the occasionally extreme conditions. In the following, a closer look is taken at some of these measurement problems: In the case of batch reactors, the feed accuracy is of great importance since control is actually feedforward. The accuracy requirements are sometimes in the order of 1 per thousand With positive displacement meters, this accuracy requirement can be met in the case of clean liquids. But these meters remain vulnerable, liable to wear, and difficult to calibrate. Verification of proper functioning, for instance by checking level drop in a downstream vessel, is therefore desirable. It is also advisable to make allowance for the temperature of the medium in calculating the mass flow rate. Solids are most usually metered into a vessel, mounted on 3 weight cells, because flow measurement is excluded here. As a matter of course this method, although it is expensive, is also suitable for liquids, and is widely used in that field. In continuous addition there is usually no accuracy problem because the supply is feedback-controlled, for instance by reactor temperature. If there is no such control it may sometimes help to use a simple flow control as part of a flow control circuit, with the setpoint adjusted with reference to long-term level drop in a feed-vessel. Greater use could be made also of variable speed pumps for charging. This may offer also savings of energy. In the determination of the quantity of solid product made there are other flow measurement problems. This determination is of importance, for instance, to obtain exact information on the degree of conversion in the reactor and to verify whether the plant material balance is correct, so as to be the use of weighing belts. With granules, good results have been obtained in some cases, but in general the outcome is disappointing, certainly with powdery product. Temperature measurements in reactors are also critical parameters, both in terms of control

and safety. As a result of fouling of the measuring element, the time constant (normally about 1 min.) of the temperature measurement increasees. In particular in the heating-up of a batch reactor, this time constant may be the cause of a considerable overshoot in control. A solution of this problem is to make use of the Antoine relation between the temperature of the liquid and the vapour pressure over it (see Hopkins and Alford,1973). Wansborough and van Maarleveld (1974) make use of an ingenious system for compensation of the measurement delay occuring with a large positive transition: they introduced a heating element into the tube containing the temperature sensor and thus regulated the heat supply proportional to the measured temperature change. After some time, the temperature reading is correct again. In fact, this system is very much analogous to the solution described by Kennedy (1976), where a dynamlc lead element is placed after the temperature sensor. Remarkably, Simon and Alford (1975) also installed a heating element adjacent to the temperature meter. But they use this to measure the heat transfer coefficient of surfaces in a suspension styrene reactor to detect failure of the suspension. Burnham and Whitney (1978), finally, placed the temperature sensor in the glass lining of a reactor baffle, thus reducing the time constant to 5 seconds for an RTD. Level measurements, in some cases important for control of the residence time and for prevention of overloading, are not always simple. A differential pressure measurement device, often adequate in other plants, may block. Capacitative measurements, too, are still unreliable. The best solution is radio-active measurement. This is expensive, and subject to legal requirements, but no contact with the viscous process liquid is involved. That is why such measurements are often applied in modern polymer plants. Radio-active measurement also provides a solution to the problem of determining the density of the liquid containing a polymer, which can hardly be done with reliable results in any other way. ICI has recently been taking a close look at the current status of instrument and control tech~ nology and the needs of the future. This study revealed that: a) Only ~ - 2 % of plant outages are directly attributable to instrumentation and controller malfunctions. b) But 50 % of the total instrument support eff0rt concerns process measurements. c) A significant area of application is analytical equipment which absorbs 20 % of instrument support effort. Over 50 % of the work on this equipment is relatively inconsequential (check, clean, refill, etc.). This emphasises the need for develo~ment of built-in selfchecking and self-diagnostic devices. d) Only 20 % of calls for checking of instruments reveal any aberration in the instrument. This means that the operator should be given built-in means to allow proof testing of equipment. e) Most trouble with instruments is due to the invasive nature of measurements (chokes, coatings, corrosion, damage). Fig. 13 shows that only few instruments are non-invasive.

Control of Polymerization Processes Therefore, research and development should be conc~Dtrated on non-invasive means of measurement. Those instruments should be simple and electrically safe, which leads to the concept of purely optical sensing with direct fibre optic data transmission to the control room. These statements are equally relevant for the polymer industry. Since many polymerization processes involve recycling and thus accumulation of inerts or modifiers may occur, it is of importance that the composition of the recycle flow be known. This composition can be measured by gas chromotograph. Closed-loop controls are derived from the results of these measurements, but in most tho'J.~r lot all cases, use is made of a process computer. In batch polymerization, the progress of the r6::lctio!i is sometimes measured with reference to off-line determinations of viscosity, refractive index or solids content. Especially when this has to be done frequently, many man-hours are involved, and moreover it requires very careful sampling. In some cases an indirect measurement, fo~ instance of stirrer power or radio-active density, correlates well with the polymer properties, so that such measurement can be used for this control. In essence, the conversion can be determined by means of a heat balance calculation across the reactor and the cooling system. The dependability of the calculation is affected by a number of factors ( heat dissipation, stirring power converted into heat), are not known with great accuracy and multiplied inaccuracy occurs in the determination of the differential between temperatures that are close together. The latter problem can be obviated by using differential temperature measurement. However, a conversion calculation can be sufficiently accurate only if very much attention and care is spent on the relevant instrumentation. Winkler and Amrehn (1970) mention an accuracy of ~ 1 % for this calculation. Ultimately, most polymer properties are measured at the end of a ~atch run, because only then they become really stable. Things are different with continuous poly~arl­ zation. Here the polymer properties at the reactor outlet have to be monitored continuously. The major problem in continuous polymerization, now, is actually the fact that feedback control with reference to product quality is difficult to realize since there is no proven on-line property measurement with sufficient accuracy. Since many polymer properties are bound up with the molecular weight distribution (MWD), it would be ideal if this quantity could be measured on-line. There are some reports about on-line gel permeation chromotography equipment for I\WID determina tion, but it is to be doubted whether such equipment is dependable. Instead of direct measurement, attempts are made to measure the average value of ~rnID. With a pure polymer melt, this variable may be derived from the melt index. Equipment for this measurement is commercially available. It has been found t~at the measurement results obtained with this type of equipment is equivalent to laboratory determinations.Unfortunately,

633

this measurement involves a considerable time-lag. In addition to the dead time incurred in sampling by the equipment, there will be an appreciable time interval between the moment the polymer is prepared in the reactor and the time when it leaves the plant. The alternative is to have the measurement performed immediately after the reactor. Often, however, this calls for special provisions, for instance the use of a degasing extruder ahead of the melt index meter. Few successful applications of this method are known. Only with very good mainteIlance procedures and intensive staff supervision can such a measurement system continue to give good results in the long run. In some cases it is possible to place a visco· sity meter in the reactor outlet. As viscosity and melt index are correlated, the operator can use the viscosity of the outflowing product for the control of the reactor. Sometimes the power input for a stirring mechanism in a polymer vessel is used to the same end. With application of van der Grinten's theory of measurability and controlability it is possible in such situations, assuming that the disturbance pattern and the dead times in the plant as well as the inaccuracies of the various measurements are known, to determine which measurement can best be used for control (Duyfj es, 1975) • Kortlandt (1971,1977) has given examples in point. Fig. 14 illustrates the problem. Prior to installation of expensive measuremegt equipment it is worth remembering that the use of a large buffer capacity in the plant also has a favourable effect on the amplitude and the band width of disturbances. Many on-line analy?ers of polymer properties require a substantial amount of sequence control, checks on proper functionning of the equipment and calculations in order to get a useful result. For this purpose microcomputers are added to the measurement system. For sampling operations simple industrial robots or "pick and place arms" might be used in combination with a microcomputersystem. Measurement results can be fed to a plant computer for processing of data or comtrol. Wilson (1980) reported on the application of a robot in combination with a microcomputer for automating the sample handler of a X-ray fluorescence spectrometer. Such applications will open new possibilities for control in the 80's. All in all, the use of on-line quality meters is on the increase in polymer plants. Looking back to the past it is seen that the number of analysis devices doubles every 10 years. One of the principal motives underlying this development is the fact that off-line analysis is becoming ever more expensive due to the rise of labour cos ts.

ENERGY CONSERVATION The control engineer is now challenged to come up with suggestions on energy-conserving control. Few successful applications in polymer plants have been reported. To a certai~ pxtend, this

634

K. Hoogendoorn and R. Shaw

is accounted for by the scale of the processes which still is a full factor lower than the typical scale in the petrochemical i~dustry. Weber (1977) reports ener~y conservation by discontinuolls opera tion of a pne1.L.la tic transport system. Po~ential applications can also be found in reactor cooling systems, in many of which cold and hot flows are mixed. In one particular case, application of a different process lay-out combined with a different control system led to major savings (Fowler and Harvey, 1978). The main energy consumer in many polymer plants is the drying section. Here, control amendments might very well result in significant energy savings and there c~uld be optimization potential. Other units in which savings of energy could be realized are compressors, extruders, distillation columns and coolers.

SUMMARY AIm CONCLUSIONS Polymer production is highly specialized sector of industry, with its own sub-specialisms. Control engineering, too, is a specialism in its own right. These various specialisms are combined in the design of control systems for polymer plants. This has been successfully done in the application of computers for the control of batch processes. Nevertheless, the contacts between the specialist fields has so far only been superficial. The control engineer with a knowledge of computers became fascinated by the challenge to set up a safe and flexible computersystem. The process engineer familiarized himself with the novel possibilities of computer application, some with keenness some with reluctance. The polymer industry could benefit further from combination of specialisms by intensifyiu5 and stimulating the multi-disciplinary integration of knowhow on instrumentation and computers, with application of thorough knowledge of the mechanism of polymer reactions. Jointly, the degrees of freedom of the pr0cesses could then be defined and guidelines could be developed on how to use them. This presupposes: a) more thorough insight into the processes, which lend themselves to development of valid models b) improved knowledge of the relation between process variables and product properties c) improved on-line measurement methods, particularly for quality.

REFERENCES Adams, P.G., A.T.Schooley (1969). Ada-predictive control for a batch-reaction. Instrum. Technolo~ 16,1,57-62. ------Ahlberg, D.T., I.Chey~e (1976). Adaptive control of a polymerization reactor. AIChE Sympos!.~~~, No 159,72,221-22-9--

AlIen, P (1977). Automation of batch reactors. Chemistry and Industry, 16 april 1977, 300-305. Amrehn, H. (1977). Computer control in the polymerization industry. Aut~~~~~, 13, 533-545. Burnham, R.M. and J.B.Whitney (1978). Process monitoring in glass-lined chemical reactors. ISA-Transactions, 17, 2,61-68 Butchard, R.L. (1969). Dynamic modelling of a chemical plant quality control loop. Pr<2£eed!.~~ Conference on !.~ria!. ~~~~~tions of Dynamic Modellin~, 16-18 september 1969, Durham, 105-113 Buss, R.A., R.Cox and J.B.Palmer (1976). Polymerization method and apparatus. !!..:2.:.Patent 3:.99~~~ Clough, D.E., P.M.Masterton and S.R.Payne (1978). Computational problems in the determination of control policies for batch polymerization. Summerconference Simulation 1978, 279-285. ---Dane, D.M;-
Control of Polymerization Processes st . S10n PVC-process. Preprints 1 Conf. on Non-Linear and Adaptive Control, Purdue Uni vers., 89-97 Knowlton, R.E. and D.K.Shipley (1976). An introduction to hazard and operability studies. ICI-Head Office Report, Feb.1976. Kortlandt, D. and R.L.Zwart (1971). Finding optimum timing for sampling product quality Chem. En3., 1 November 1971, 66-72. Kortlandt, D. (1977). Deciding on control strategy with covariance functions. Preprints Chemdata 77, Helsinki 9-10 June, 1977, 211-220. Kortlandt, D. and H.Kragt (1978). Ergonomics in the struggle against alarm inflation in process control systems - Many questions , few answers. Journal A, 19, 3,135-141 Law, W.H. and T.Moloney (1971). Computer control of a mMlti-train batch plant. r Proceedings 3 IFAC/IFIP Conference, Helsinki, IX, 1-8. Luethy, R.M. (1976). Computer control of a batch polyester plant. Proceedings AIChE Workshop on Control of Batch Processes, Washington,May 3 and 4, 1976, 5-11. Luijben, W.L. (1975). Introduction to batch reactors. Instrum. Technology, Aug. 1975, 27-34. Maroquin, G. and W.L.Luijben (1973). Practical control studies of batch reactors using realistic mathematical models. Chem. Eng. Sci., 28, 993-1003 Moll, P. and R.Doclo (1976). Rezeptabh~ngige Steuerung eines Chargenprozesses; ein Vergleich unterschiedlicher L~sungswegen. Preprints European Symposium, Florence 23-24 September 1976, 416-428. Moloney, T. and J.P.Flower (1976). Computer control of a polymer plant- the hierarchical approach. preprint~~urope~~E.~ Florence l 23-24 September 1976, 283-295. Nakagawa, M. (1970). Large PVC manufact1:.lring plant and computer control system. £EER z 1970, 3, 12-16 and CEER, 1970 z 4, 27-32 Nisenfeld, A.E. (1975). Supervisory control of production of polyurethane rubbers. Proceedings PRP 3,335-339. Preprints European Symposium (1976). Use of process computers for the operation of production plants in the fields of chemical petroleum, paper and process industry. 23-24 September 1976, 552-640. Quietzsch, G. and W.Hoffman (1975). Computer control of a powder silo system. Proceedings PRP 3, 253-259. Quietzsch, G. (1979,1980). Vorschlag zur PrUfung von Prozessrechnern fUr Sicherheitsaufgaben. Regelungstech~~~~~~, 349-353 and 22, 11-15. Rijnsdorp, J.E. and W.B.Rouse (1977). Design of man-machine intt~faces in processcontrol, Preprints of the 5 IFAC/IFIP Intern. Conf., The Hag~~~~ 14-17,1977, 705-720 Shinskey, F.G. and J.L.Weinstein (1965). A dual-mode control system for a bftch exothermic reactor. Preprints 20 n ISAConference, nr 6.4-1-65. Simon, R.H.M. and G.H.Alford (1975). Prompt failure detection in suspension polymerization systems. Appl. PolJ~. Symp., 26, 31-37

635

Slangen, H.J.M. (1978). Design of a control system for optimum heating of batch reactors. Master Thesis, Techn. Hogeschool, Eindhoven (in dutch). Smith, D.E. and W.S.Stewart (1974). Controlled polymerization process and apparatus. D.S.Patent 3.817.962. Smith, R.~. (1971). Digital computer control of polymerization process. D.S.Patent 3.614.682. Takahashi, N. and T.Katoh (1979). Low density polyethylene plant. Hitachi Review, 28, 147-152. Trevathan, V.L. (1976). Process controls in tte chemical industry. AIChE Symposium Series No 159, 72, 40-49 Tsai, T.H. and J.W.Lane (1976). Experiences in batch chemical process control. Proceedings AIChE Workshop on Control of Batch Processes Washin~ton Ma~ 3 and 4, 1976, 15-21 Dhlig, R.J. (1977). Steuerung der Kunstharzproduktion mittels Prozessrechner. Regelungstechn. Praxis, 1, 17-25. Volter, B.V., I.E.Salnikov, A.E.Sofiev,F.A. Shatkhau. (1966). Dynamics and optimization of the polymerization processes. Proceedings Third IFAC Congress, Londcn z 48D, 1-6. wansborough, M. and A.Maarleveld (1974). Improved temperature measurement in batch reactors. Meas. & Control l 7, 187-190. Weber, H. (1975). Computer control of a batch homogenization plant. Proceedings PRP3, 245-251. Weber, H. (1977). Prozessrechner Einsatz in einer Kuns ts toffanlage. .Regelungs techn. Praxis, 2, 49-55. Wilton, M.J. (1979). The application of microprocessors and robotics to autoffi8.~ic analysers. Preprints, IMEKO/IFAC Symposium 17-20 November 1980. Winkler, O. and H.Amrehn (1970). Einfach- oder Doppelrechnersystem ? Zwei Fallbeispiele. Regelungstechnik, 1, 3-10 and 2, 53-56.

LIST OF SYMBOLS (Fixed) time delay. Heat of reaction. Cooking margin. First temperature switching point. Second temperature switching point Autocorrelation time of disturbances. Reactor temperature. 8etpoint of reactor temperature. I~llet temperature of wa ~er to jacket of reactor. Setpoint of T T W' Standard devi~tion in controlled variable Ud due to disturbance.

K. Hoogendoorn and R. Shaw

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•

3.0

K. Hoogendoorn and R. Shaw

640

100 PrlllUr. (bourdon) " pneumatic instrumem.tion

Thermocoupl. Pr....r. (d.regm)

50

o .....

...&..

.&..-

1970

1980

_~~

1960

__

~ - - - ~.

time

Fig. 12 Trend towerds electronics

T empemur. (resistance

..

th.,mom~er)

Flow (E - M) Level (radio active)

Flow Cturbine) Lev.1 (ClPllcity)

~

_:1"J-----I

M I

I

_.1 - - - - - _.1.._ - - --_.....:

T Fig. 14 Different quality meters at different places give different

c:onttoUability

=

Non-invasive m• •.,ements

I

Fig. .13 S.nlOrs (re"tive population)