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Hierarchical production control for integrated pulp and paper mills: a survey
Copyright
©
Session 19
IFAC PRP 4 Automation, Ghent, Belgium 1980
HIERARCHICAL PRODUCTION CONTROL FOR INTEGRATED PULP AND PAPER MILLS: A SURVEY P. Uronen International Institute for A pplied Systems Analysis, 2361 Laxenburg, A ustr":a
Abstract. In recent years the terms hierarchy and distributed system have become a common practice in discussions concerning the control and automation in the pulp and paper industry. Clearly the development goes in the direction of applying these methods more and more. There can be found many types of hierarchies and hierarchical structures and organizations in the pulp and paper industry; also concerning the control systems in this industry we can find different possibilities in applying hierarchical structures and ideas. In this paper the present situation and trends in the application of hierarchical structure in the production planning and control in the integrated pulp and paper mills will be discussed. Keywords. Production planning, production control, paper industry, computer applications, hierarchical systems, distributed systems.
chies can be found in most of the existing process computer systems in the pulp and paper industry (Al-Shaikh, 1978; Jutila, Kauppinen, Mensonen, Olli1a, 1978)
INTRODUCTION Hierarchical organizations and structures are typical both in the society and in industry and business. Especially after World War 11 there has been a rapid growth of really large organizations in the administration and in the industry. This development has also been an important stimuli to the systems scientists to study these kind of large-scale systems in order to develop methodology for governing and optimizing these systems. The effective management and control of large systems is difficult because a.o. the formulation of comprehensive models and objectives is very cGmplicated and the large size of the system makes the normal techniques of model solving and optimization very slow and impractical.
The multilevel hierarchy includes a coordinator and subordinated local decisionmctking and control units. The function of the coordinator is to affect the local control units in such a way that the overall target will be achieved. These hierarchies are thus based on distribution and coordination of complex systems making the solving of the whole problem more economic and/or possible. This idea can also be applied to on-line process control. Then the following features are important (Findeisen, 1978): the process is subject to disturbances;
Basically for economic and reliability reasons there now exists a general trend towards decentralized decision making, distributed computation and control and hierarchical systemstructures in complex systems (Athans, 1978). In conceptualizing of hierarchical systems several possibilities exist. The commonly used classification is into multilayer (Lefkowitz, 1966) and multilevel (Mesarovic, Macko, Takahara, 1970) hierarchies. In former the control actions of a plant are divided into different functional or temporal layers. Each of the layers is considering a different function and/or time horizon for the optimization and control of the system, the highest layer having the longest horizon. As an example of this kind of functional hierarchy we can mention the following layers of process control: Stabilizing control, optimizing control and adaptive control. These kind of control hierar-
the necessary measurements are available; the constraints must always be fulfilled; and the time reserved for computation of optimal algorithms is limited. The common feature for all hierarchies is that the decision making has been distributed in such ct way, that a hierarchical structure will result. This means that there exist several decision making units (controllers) in the system but only some of them are directly connected to the process variables; the others are at higher levels (or layers) and they coordinate
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the functions at the lower level but they cannot change the decisions made by the lower level. The general benefits and advantages achieved by a hierarchical system are: Easier integration of all the functions and better adaptability to existing (from their nature hierarchical) organizations. Better utilization of resources available; for example the data processing capability of individual subsystems. Flexibility and reliability. Reducing complexity and thus simplification of the solution process. Coping with uncertainties; the decisions at each level are made at different times and thus much data at lower level is quite uncertain at the moment when higher level decision has to be made. In a centralized system all decisions should be done at the same time and thus earlier at the lowest levels when the data available are more uncertain. The limited decision-making capability of an individual is extended by the hierarchical structure. Subsystems may be geographically far apart having limited communication with each other. Connected with the transmission of information there will always be costs, delays and errors. There may already in the existing system be local autonomy of decisions made by the subsystems and/or privacy of information. These features can easily be included in and coped with the hierarchical structure. The technical development of the hardware has done it both technically and economically attractive to build and operate this kind of system. METHODOLOGY The theory of hierarchical systems and methodology suitable for modelling and optimizing them has in recent years been a target for extensive theoretical work. One of the "classical" works in conceptualizing and formalizing of the hierarchical control systems and organizations is the book by Mesorovic, Macko and Takahara (1970). They also developed the mathematical framework for the theory of coordination. Since that, there have been numerous theoretical works in this area. Most of these investigations are theoretical distinguishing the concepts (Himmelblau 1973,
Sandell, Varaiya and Athans, 1975; Sage 1977). For the solution techniques some works applying the management science and decision making theory (Athans 1974, Ho and Chu 1974, Bailey 1976), scheduling theories (Drew 1975, Hax 1976, Hax and Meal 1975, Hax and Golovin 1978) and/or control theory and aspects (Findeisen 1978, Tamura 1975, Singh 1977). Much work has also been done concerning different coordination and decomposition algorithms (Danzig and Wolfe 1960, Benders 1962, Rosen 1964, Geoffrion 1970). There seems to be a lot of theoretical work done in this area but very little has so far been really applied. The applicability of the theoretical methods and algorithms in practical problem solving in large scale systems is so far quite low (Athans 1978) and more emphasis should be put on reliability questions, on sensors available and on stochastic nature of the system. However some applications in different industries for example in steel industry are planned or exist (Letkowi tz and Cheliutskin 1976, Williams 1978, Miyazaki, Sakairi, Okano" Arakawa and Suzuki 1978). The trend in pulp and paper industry is also clearly going into the direction of integrated hierarchical control and information systems but so far only very few and quite limited applications in this industry exist; the general situation being such that separate computer systems at different departments stand alone without any realtime coordination or exchange of information with each others (Eriksson 1978, Uronen and Williams 1978). PRODUCTION PLANNING AND CONTROL IN PULP AND PAPER MILLS When discussing about the hierarchies in the integrated pulp and paper mills we can have several types of hierarchies; organizational, functional, technical etc. Typical example is the hierarchy in the tasks of process control as I mentioned already. However, I will not talk more about it because there will be another paper in this conference covering that topic. Concerning the managerial tasks in pulp and paper industry we will get another hierarchy, a temporal multilayer type as depicted in Fig. 1 (Uronen, 1980). Here the time span of the decisions and actions to be taken will fall in the range from several years (strategic planning) to a few seconds (real-time process control). When we concentrate in the production planning and control tasks we take from the above hierarchy only the lowest levels i.e. corporate and mill level tasks, into account. Fig. 1 also very clearly shows the fact that most management decisions especially in the strategic planning will be strongly affected by several factors which are not dependent on the corporate alone and which must be taken into account; just to mention a few of these: trends in world trade, new demands on end
Hierarchical Production Control products, environmental and other regulations, competition on raw material, pricing of energy, scarcity of labor etc. These and related important long-term effects on pulp and paper industry are global, universal or national and thus they cannot be studied inside one corporate or mill; these question must be studied internationally and in this connection I can mention that the International Institute for Applied Systems Analysis (IIASA) at Laxenburg, Austria, has started an international project investigating some of these global and universal long-term production planning problems of the pulp and paper industry. Coming now back to the mill level today's situation in the pulp and paper industry as for the utilization of computerized control and planning systems Fig. 2 illustrates this. Clearly there are dedicated computer control systems developed and commercially available for almost all technical subprocess in the pulp and paper mill and also several "management type" or administrative applications; but in general these systems work alone without any coordination or real-time exchange of information. This cannot be the optimal way of control when the whole mill is considered. So there is a need for coordinated operation and planning and these functions can be realized with an hierarchical system. The hierarchical production planning and control tasks in an integrated pulp and paper mill can be described with different types of hierarchy i.e. multilayer temporal and multilevel functional hierarchies. Fig. 3 shows a typical arrangement of the different steps in production planning and control in an integrated white paper mill producing several types of products (Uronen and Williams 1978). The upper part in this system is typically temporal multilayer hierarchy with the spans as marked ranging from one year until a few hours. Below this there will be the production control, efficiency and quality supervision and process control and this part of the total system can be hand~ed as a multilevel coordination and optimization problem. The tasks in this hierarchy can be grouped and organized in several different ways. Figures 4 and 5 give one possible solution (Uronen and Williams, 1978). Typically a paper mill can producE several grades and the inventory at the mill can include tens (or even hundreds) of items (grades and sizes). The production planning procedures start as depicted in Fig. 3 with a basic plan (budget) based on order history, market situation and forecasts and existing and planned production capacity at the mill (or inside the corporate). Then the planning will continue as follows: The corporation sales division takes care of all sales activities and direct contacts with customers. The customer orders will be sent from the sales department to the target mill, (if the corporate has several mills
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producing same qualities) according to the mill production specifications and budgeted production capacity, etc. So the order stream coming to the mill will already be prescheduled by the corporate sales organization. Of course feedback from the mill situation (inventory, capacity restrictions, shut-downs, etc.) will be continuously sent to the sales department. Under present practices the normal starting point for a detailed production schedule in the mill is the production cycle with a period of several (5-7) days. The cycle means that each paper machine will produce for certain periods of time (dictated by the budget plan or order backlog) certain qualities and grades of papers during the cycle (for example first heavy weight papers, then light weight papers, then special qualities, etc.). All orders for the same quality (and items in a composite order) will be collected together to form a batch run which is as big as possible within the basic cycle. Thus, the grade changes and trimming losses,etc., will be kept to a minimum. The minimum batch amount of each quality depends on the capacity and qualities produced. The total inventory capacity represents typically about I month's production. If there are not enough orders, production will be run for inventory. If a sudden unpredictable shutdown occurs the whole cycle will be delayed. No rescheduling inside the cycle will be done. The order handling, shipping documentation, billing, etc., is computerized. The detailed production scheduling of the cycling and trimning operat~ons is today still in most cases manual but off-line operations for file searches and updating of data-banks and different types of techno-economical calculations (lot sizes, trimming for paper machines etc.) have also been computerized. The methods used for scheduling and production planning based on budget and oraer flow are typically (King 1975) branch and bound algorithms, Johnson's rule algorithm or different sorting and ranking methods or heuristics. These same methods can also be applied to direct job scheduling in finishing department and for example in trimming and cutting of paper rolls. (Gilmore and Gomory 1961, 1963) because these are more or less typical job-shop type scheduling problems. Let us consider now in a little more details the hierarchy depicted in Fig. 5. Production control, coordination and scheduling functions are different in different parts of the integrated pulp and paper mill. Therefore level III-B (Fig. 5) can be decomposed horizontally as presented. This level has been called Area Control. Now three areas are considered: the paper mill, the pulp mill and the power plant (incl. chemicals recovery and environmental monitoring and control) .
P. Uronen
578 The tasks common to each area are:
1.
2.
3.
The determination of the short term production schedules for the pulp mill and paper mill processes (Fig. S). The production rates of power plant processes are determined based on these. This determination of pulp and paper production rates is based on the long term paper production schedule which is to be realized by minimizing the costs of raw materials, energy and chemicals. Sometimes also the maximization of the paper production (or the pulp production) can be considered. The collection, updating and presentation of different reports for both operators and supervisors and to other systems like marketing, maintenance etc. Maintenance of history data files (operations, usage of raw materials, of chemicals and of energy, inventories, quality, production etc.).
4.
Maintenance of real-time data files (production, disturbances).
S.
Maintenance scheduling.
6.
R&D functions.
7.
Follow-up of the realization of the short term production schedule for each process. Determination of necessary actions in abnormal situations.
Uronen 1980) : 1.
The planned pulp production schedule must be followed.
2.
The production rate changes should be avoided and minimized.
3.
Planned shut-downs (for maintenance etc.) must be taken into account in advance.
4.
Random disturbances (machine failures etc.) should also be accounted for.
5.
The production rate of the "bottleneck" department should be maximized if the market are not restricted.
6.
Storage tanks may not become empty or overflow.
7.
Storage capacity of in-process inventories should be effectively used.
8.
There exist suitable target levels i.e. expectation values for each buffer storage at the ertd of the planning period (2 ... 3 days). That should be reached. This will help in scheduling for the next period.
9.
Liquor and chemicals should be in balance.
10.
The dynamics (retention times) of the processes must be taken into account in the schedule.
11.
The usage of cheapest fuel (i.e. the bark at the auxiliary boiler for example) must be maximized.
12.
Recovery boiler cannot be used for compensating of the short term variations in the energy balance.
13.
The steam can be indirectly stored in black liquor or in pulp.
In paper mill also following tasks will be included: 1.
Realization of rate and grade changes.
2.
Coordination and utilization of the results from an automatic paper laboratory or from in-process quality measurements (i.e. quality supervision) .
3.
In some cases also order handling can be included in the production control system at this level.
Based on the production schedule of the paper mill the needs (per quality and amount) of different pulps (and additives) are calculated and after this the operations of the pulp mill must be coordinated and optimized. This part of problem has lately been studied by several authors. (Pettersson 1969, 1970, Golemanov 1972, Tinnis 1974, Alsholm and Haglund 1977, Edlund and Rigerl 1978, Leivisk~ and Uronen 1979a, 1979b). Different types of targets, criteria and solution algorithms or methods have been suggested and demonstrated. The goals of the production coordination and control in the pulp mill can be listed as follows (LeiviskM and
Most of these requirements are selfexplanatory and for example the requirement to avoid excess production rate changes, start-ups and shut-downs is important therefore that in connection with such changes always many kind of undesirable side-effects (production losses, quality losses, decrease of yield, energy losses, extra environmental load, extra job, risks etc.) will occur. The coordination of the power plant requires following special tasks: 1.
The production schedules of different types of energy.
2.
In some cases also the optimization of purchased electricity and peak load monitoring can be included in the production control system. Very often it would be better, however,
Hierarchical Production Control to use a specific system for the optimization of purchased electricity, for instance on corporate level. The optimization of the pulp line processes and the chemical recovery cycle together with the optimal allocation of boilers and turbines takes place on the process control and optimization level, (Levels II and IlIA, Fig. 5) even though they deal with the optimization of larger process complexes. More detailed specifications for this kind of hierarchy at all levels with input and output connections and also with some hardware considerations can be found in Uronen and Williams (1978). For the coordination problem of the pulp mill production different mathematical formulations and solution algorithms have been studied, for example network algorithms (Edlund and Rigerl 1978), maximum principle (Chalaye and Foulard 1976), linear programming (Pettersson 1970), simulation (Golemanov 1972) heuristics (Leiviska, Komokallio, Aurasmaa and Uronen 1980) and different hierarchical optimization algorithms (Leiviska and Uronen 1979a,b) have been applied. Closely connected with the above discussed scheduling and coordination tasks is the necessary data collection and information part of the production planning and control system. This could also be the first step in developing the whole system. This information system is, in fact, distributed on different levels of hierarchy and in different hardware which is used in constructing the whole system. In the design of this kind of information system, following aspects must be taken into account (Leiviska Jutila, Uronen and Heikkil:i 1980): 1.
2.
3.
System specification must follow the existing organizational and operational structures. There ought to be at least one person for each sub-system who is responsible for its operation, who is using it and whose needs the system must fulfil. There are two distinct phases in the design: the specification phase based on the requirements of the system users and the implementation phase.
4.
Data transfer linking the systems together must be standardized.
5.
The impetus for the control system must come from the user.
6.
Large production control systems must be of modular type. They concentrate on collection, reduction and presentation of information. Reliability is one keyword. Human decisionmakers have the responsibility of final decisions.
7.
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The system forms inherently a hierarchy. This hierarchy is to be adapted to the existing organization, rather than vice versa.
Generally speaking, the information system deals with, at least, the following data: production rates, inventories, material flows, costs of different flows and specific consumptions of raw materials and energy. This information is collected as direct measurements or manual inputs or it is calculated from the collected process data. It must be pointed out that the development of this kind of hierarchy, Fig. 5 is designed mostly on functional basis. The hierarchy of the hardware of a possible implementation does not necessarily follow the identical structure. Today's technology gives possibilities for very versatile and flexible solutions at reasonable prices. One difficulty in building such hierarchies so far is the lack of international standardization in interfaces, communications and programming of the systems; so the compatibility of subsystems delivered by different vendors may be a serious problem. The computerization in the full scale on the process control level is not necessarily a precondition for the production control system, but the functions of the existing process control systems must be taken into account, because there is then no need to duplicate these functions. The flexibility, the modularity, the adaptability and easy-to-use features must be kept in mind during the specification of the production control tasks. As a summary for specifying and planning of this kind of system following questions should be answered and solved:
1.
General structure, how many levels etc.
2.
Tasks at different levels.
3.
User and user needs at each level.
4.
Input and output connections at each level.
5.
Manual entries and other Operator communications at each level.
6.
Degree of distribution.
7.
Data transfer techniques and methods.
8.
Hardware questions.
9.
Adaptaticn to the existing organization.
10.
Reliability and redundancy.
11.
Location of data banks.
12.
Use of databanks, unlimited for all users or restricted use.
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580 13.
Implementation; building above the process control blocks and using them or separate information system with bypassing the process control systems and by using direct measurements.
14.
Handling of disturbance and shutdown situations.
15.
Maintenance and updating.
16.
Benefits vs. costs.
17.
Models needed at each level.
18.
Algorithms used at each level.
19.
Method of coordination.
20.
"Optimal" level of distribution and computerization.
efficiency of utilization of capital equipment in the paper industry today. A 1.0% increase in this efficiency would mean about 650,000 tons per year of for the U.S. paper industry for the same capital investment (Hannigan, 1978).
Many of these questions still need a lot of research work but none of them can be solved by the researchers or vendors alone; the viewpoints and needs of the users are essence.
b.
There is a potential productivity gain of about 5% through the better coordination of interacting departments and their related buffer storage (Edlund, Rigerl, 1978) .
c.
with modern recovery boilers showing efficiencies of the order of 65% and older systems running as low as 40-45%, there is a very great potential for energy savings in this area through better control and coordination.
d.
Labor productivity can be improved with a complete measurement and reporting system coordinated with engineering performance standards in a hierarchical system. According to Geisel (Geisel 1978) one container corporation has cut labor costs per ton by 19% during the past eight years with a productivity measurement system, and a 2.5% decrease in material waste on a case line has also been reached.
BENEFITS OF HIERARCHICAL PRODUCTION PLANNING AND CONTROL SYSTEMS It is a well-documented fact that the individual computer control systems in pulp and paper industry have been successful giving remarkable gains in terms of increased throughputs, higher yields, lower raw material and energy usage and higher quality. The general advantages of hierarchy were already discussed. In addition to these there is a long list of other, often intangible, gains which are available, particularly from the coordination capabilities of a hierarchical planning and control system, which need to be mentioned. Some of these are as follows: (Uronen and Williams 1978)
1.
2.
3.
4.
Faster availability and more frequent updating of information flow from the plant to management thus aiding decision making at all such levels. Plant production and operational aata (both current and historic) will be much more precise and time coordinated than is possible with manual methods. This is a major aid to long term planning, Plant data system can detect trends in plant operations. These and other plant data available from the system will readily permit the testing of various plant operating strategies prior to actual implementation. Some examples of gains are obtained from these kinds of systems: a.
There is about a 90% average
5.
Full plant optimization studies are possible only with the full availability of plant operating data supplied by a hierarchical system.
6.
Fast and effective monitoring of effluents and emissions can often prevent major leaks and the resulting damage or loss.
7.
Savings in operational personnel and other staffing (Thompson, 1978).
Some specific benefits of the distributed hierarchical system architecture are as follows: 1.
Flexible system configuration - distributed subsystems may be modified, replaced, or deleted without upsetting the rest of the system.
2.
Graceful degradation - failure in one or more components or subsystems will not cause the entire system to fail.
3.
High systems reliability due to: a.
Easy to add parallel redundant units and subsystems which can be incorporated to back up and duplicate the functions of the main components and subsystems.
Hierarchical Production Contrul b.
Transmission of partially processed plant information allowing: i)
ii)
4.
Decreased data rates since processors are distributed to functional areas and only processed information need be sent between any two subsystems rather than raw data as formerly. Use of error detection codes which allow any fault or casualty condition in the system to be detected and identified by the processor in its area of responsibility.
But clearly there are also a tendency and justified needs for coordination between these systems and combining them into a hierarchical total mill information and planning system. Fig. 6 demonstrates the three "generations" of process control systems in pulp and paper industry. It is very understandable that the development and implementation of the whole hierarchy is a project of several years demanding remarkable investments and resources; so some kind of piece-wise or modular system approach seems economically most promising. If the compatibility problems and other standardizing questions can be solved satisfactorily the building by starting from existing process control packages is feasible.
Lower cost due to: a.
Simplified hardware configuration packaging. Since processors need not be large due to the reduced processing requirements of each processor.
b.
Simplified software because functions are carried out by several small, locally responsible processors, not by a large machine that must perform all of the control functions and calculations within the entire control system.
c.
Large scale integration technology.
d.
Multiple use of standard components. Many different subsystems can use identical hardware to perform varied functions.
e.
Ease of incrementally increasing capability since units may be added to the system without drastically interfering with the functions of the rest of the system.
f.
Simplified installation since common data channels can be used for processor-to-processor communication. This eliminates the need for individual multiplewire cables between any two units.
CONCLUSIONS As already mentioned earlier the "normal" situation in an integrated pulp ana paper mill today is the increasing use of separate dedicated process computer system.
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other possibility is to first build a suitable information system and computerized planning tool for the production planner separately from process control systems (Edlund and Rigerl 1978). I believe that both of these approaches can and will be used;~o which extent and how rapidly depends very much on the further development work and general economic situation in the pulp and paper industry. There exist already some hierarchical systems in operation in several mills in Finland and in Sweden (Eriksson 1978, Petersson and RUckert 1978) and both of the above mentioned approaches have been used. However these systems vary very much in their tasks, in hardware and software used and in their sophistication of hierarchy. Today we are in a situation where 80% of the paper will be produced during other than normal day-shift when all the management and other key-persons for making decisions are on site. This necessitates the development of tools and techniques for the assistance of the operators and according to my opinion the hierarchical production planning and control systems are one very useful and effective tool for this purpose. In theory almost everything in a pulp and paper mill could be automated today. The question remains how do we use most effectively the techniques available and how do we combine the human resources and automation in a modern mill i.e. what is the optimum level of automation?
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Hierarchical Production Control Lefkowitz, I., and A. Cheliustkin Editors (1976). Integrated systems Control in tne Steel Industry, State-of-theart review and proceedings of the conference, June 30 - July 2, 1975, International Institute for Applied Systems Analysis, Laxenburg, Austria. LeiVisks", K., and P. Uronen. (1979a) . Dynamic Optimization of a sulphate mill pulp line. IFAC/IFORS Symposium "Comparison of Automatic Control and Operational Research Techniques Applied to Large Systems Analysis and Control", Toulouse. Leivisks', K., and P. Uronen. (1979b). Dynamic Optimization of a sulphate pulp mill, IFAC Symposium Optimization Methods, Applied Aspects, Varna. Leiviska, K., and P. Uronen. (1980) . Different approaches for the production control of a pulp mill, IFAC Conference PRP 4, Ghent. Leivisk!, K., H. Komokallio, H. Aurasmaa and P. Uronen. (1980). Heuristic Algorithm for production control of an integrated pulp and paper mill. To be presented in the 2nd IFAC Symposium Large Scale Systems; Theory and Applications, June 16-19, Toulouse. Leiviska, K., E. Jutila, P. Uronen and S. Heikkila (1980). Production control of complex integrated mills, Computers in Industry, Vol. 2 (in print). NorthHolland Publishing Company, Amsterdam. Mesarovic, M.D., D. Macko and Y. Takakora. (1970). Theory of Hierarchical, Multilevel Systems, New York, Academic Press. Miyazaki, Y., Y. Sakairi, T. Okano, J. Arakawa and K. Suzuki. (1978). Integrated Computer System at Oita Steel Works. Proceedings of the 7th IFAC World Congress, Helsinki. Peterson, E., and H. Rllckert. (1978). Total Computerized production control, PPI, April 1978, pp. 77-82. Petterson, B. (1969). Production Control of a complex integrated pulp and paper mill, Tappi, 52, 11.
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Pettersson, B. (1970). Mathematical methods of a pulp and paper mill scheduling problem, Report 7001, Division of Automatic Control, Lund Institute of Technology, Lund. Rosen, J.E. (1964). Primal Partition Programming for block diagonal matrices. Numerische Mathematik, 6, 250-260. Sage, A.P. (1977). On the application of systems methodology to economic and organizational management of integrated industrial complexes, Proceedings of the IFAC Workshop Control and Management of Integrated Industrial Complexes, Toulouse, France, 6-8 September. Sandell, N.R., P.P. Varaiya and M. Athans. (1975). A Survey of Decentralized control methods for large scale systems. Proceedings Engineering Foundation Conference on Systems Engineering for Power Systems, Henniker, New Hamshire. Singh, M.G. (1977). Dynamic Hierarchical Control, North Holland Publishing Company. Tamura, H. (1975). Decentralized optimization for distributed time-lag models of discrete systems, Automatica, 11, 6, 593-602. Thompson, L. J. (19'78). Executive Decision: What's the bottom line, PlMA, July, pp. 21-25. Tinnis v. (1974). An Optimum Production Control System. Pulp and Paper Magazine of Canada, 75, 7. Uronen, P., and T.J. Williams. (1978). Hierarchical control in the pulp and paper industry. Report No. III Purdue Laboratory for Applied Industrial Control, West Lafayette. Uronen, P. (1980). Management Systems in the Forest Industry; An overview, Working Paper. International Institute for Applied Systems Analysis, Laxenburg, Austria. Williams, T. J. (1978). Hierarchical Control for Large Scale Systems - A survey, Proceedings of the 7th IFAC World Congress, Helsinki.
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DEDICATED COMPUTER SYSTEl1S FOR: Stock preparation TMP. refiners On-machine CO.1ter Coating paste Roll handling Laboratory etc,
Computer Systems in the Pul~ and Paper Mill Today.
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585
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©
Session 19
IFAC PRP 4 Automation, Ghent, Belgium 1980
HIERARCHICAL PRODUCTION CONTROL FOR INTEGRATED PULP AND PAPER MILLS: A SURVEY P. Uronen International Institute for A pplied Systems Analysis, 2361 Laxenburg, A ustr":a
Abstract. In recent years the terms hierarchy and distributed system have become a common practice in discussions concerning the control and automation in the pulp and paper industry. Clearly the development goes in the direction of applying these methods more and more. There can be found many types of hierarchies and hierarchical structures and organizations in the pulp and paper industry; also concerning the control systems in this industry we can find different possibilities in applying hierarchical structures and ideas. In this paper the present situation and trends in the application of hierarchical structure in the production planning and control in the integrated pulp and paper mills will be discussed. Keywords. Production planning, production control, paper industry, computer applications, hierarchical systems, distributed systems.
chies can be found in most of the existing process computer systems in the pulp and paper industry (Al-Shaikh, 1978; Jutila, Kauppinen, Mensonen, Olli1a, 1978)
INTRODUCTION Hierarchical organizations and structures are typical both in the society and in industry and business. Especially after World War 11 there has been a rapid growth of really large organizations in the administration and in the industry. This development has also been an important stimuli to the systems scientists to study these kind of large-scale systems in order to develop methodology for governing and optimizing these systems. The effective management and control of large systems is difficult because a.o. the formulation of comprehensive models and objectives is very cGmplicated and the large size of the system makes the normal techniques of model solving and optimization very slow and impractical.
The multilevel hierarchy includes a coordinator and subordinated local decisionmctking and control units. The function of the coordinator is to affect the local control units in such a way that the overall target will be achieved. These hierarchies are thus based on distribution and coordination of complex systems making the solving of the whole problem more economic and/or possible. This idea can also be applied to on-line process control. Then the following features are important (Findeisen, 1978): the process is subject to disturbances;
Basically for economic and reliability reasons there now exists a general trend towards decentralized decision making, distributed computation and control and hierarchical systemstructures in complex systems (Athans, 1978). In conceptualizing of hierarchical systems several possibilities exist. The commonly used classification is into multilayer (Lefkowitz, 1966) and multilevel (Mesarovic, Macko, Takahara, 1970) hierarchies. In former the control actions of a plant are divided into different functional or temporal layers. Each of the layers is considering a different function and/or time horizon for the optimization and control of the system, the highest layer having the longest horizon. As an example of this kind of functional hierarchy we can mention the following layers of process control: Stabilizing control, optimizing control and adaptive control. These kind of control hierar-
the necessary measurements are available; the constraints must always be fulfilled; and the time reserved for computation of optimal algorithms is limited. The common feature for all hierarchies is that the decision making has been distributed in such ct way, that a hierarchical structure will result. This means that there exist several decision making units (controllers) in the system but only some of them are directly connected to the process variables; the others are at higher levels (or layers) and they coordinate
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the functions at the lower level but they cannot change the decisions made by the lower level. The general benefits and advantages achieved by a hierarchical system are: Easier integration of all the functions and better adaptability to existing (from their nature hierarchical) organizations. Better utilization of resources available; for example the data processing capability of individual subsystems. Flexibility and reliability. Reducing complexity and thus simplification of the solution process. Coping with uncertainties; the decisions at each level are made at different times and thus much data at lower level is quite uncertain at the moment when higher level decision has to be made. In a centralized system all decisions should be done at the same time and thus earlier at the lowest levels when the data available are more uncertain. The limited decision-making capability of an individual is extended by the hierarchical structure. Subsystems may be geographically far apart having limited communication with each other. Connected with the transmission of information there will always be costs, delays and errors. There may already in the existing system be local autonomy of decisions made by the subsystems and/or privacy of information. These features can easily be included in and coped with the hierarchical structure. The technical development of the hardware has done it both technically and economically attractive to build and operate this kind of system. METHODOLOGY The theory of hierarchical systems and methodology suitable for modelling and optimizing them has in recent years been a target for extensive theoretical work. One of the "classical" works in conceptualizing and formalizing of the hierarchical control systems and organizations is the book by Mesorovic, Macko and Takahara (1970). They also developed the mathematical framework for the theory of coordination. Since that, there have been numerous theoretical works in this area. Most of these investigations are theoretical distinguishing the concepts (Himmelblau 1973,
Sandell, Varaiya and Athans, 1975; Sage 1977). For the solution techniques some works applying the management science and decision making theory (Athans 1974, Ho and Chu 1974, Bailey 1976), scheduling theories (Drew 1975, Hax 1976, Hax and Meal 1975, Hax and Golovin 1978) and/or control theory and aspects (Findeisen 1978, Tamura 1975, Singh 1977). Much work has also been done concerning different coordination and decomposition algorithms (Danzig and Wolfe 1960, Benders 1962, Rosen 1964, Geoffrion 1970). There seems to be a lot of theoretical work done in this area but very little has so far been really applied. The applicability of the theoretical methods and algorithms in practical problem solving in large scale systems is so far quite low (Athans 1978) and more emphasis should be put on reliability questions, on sensors available and on stochastic nature of the system. However some applications in different industries for example in steel industry are planned or exist (Letkowi tz and Cheliutskin 1976, Williams 1978, Miyazaki, Sakairi, Okano" Arakawa and Suzuki 1978). The trend in pulp and paper industry is also clearly going into the direction of integrated hierarchical control and information systems but so far only very few and quite limited applications in this industry exist; the general situation being such that separate computer systems at different departments stand alone without any realtime coordination or exchange of information with each others (Eriksson 1978, Uronen and Williams 1978). PRODUCTION PLANNING AND CONTROL IN PULP AND PAPER MILLS When discussing about the hierarchies in the integrated pulp and paper mills we can have several types of hierarchies; organizational, functional, technical etc. Typical example is the hierarchy in the tasks of process control as I mentioned already. However, I will not talk more about it because there will be another paper in this conference covering that topic. Concerning the managerial tasks in pulp and paper industry we will get another hierarchy, a temporal multilayer type as depicted in Fig. 1 (Uronen, 1980). Here the time span of the decisions and actions to be taken will fall in the range from several years (strategic planning) to a few seconds (real-time process control). When we concentrate in the production planning and control tasks we take from the above hierarchy only the lowest levels i.e. corporate and mill level tasks, into account. Fig. 1 also very clearly shows the fact that most management decisions especially in the strategic planning will be strongly affected by several factors which are not dependent on the corporate alone and which must be taken into account; just to mention a few of these: trends in world trade, new demands on end
Hierarchical Production Control products, environmental and other regulations, competition on raw material, pricing of energy, scarcity of labor etc. These and related important long-term effects on pulp and paper industry are global, universal or national and thus they cannot be studied inside one corporate or mill; these question must be studied internationally and in this connection I can mention that the International Institute for Applied Systems Analysis (IIASA) at Laxenburg, Austria, has started an international project investigating some of these global and universal long-term production planning problems of the pulp and paper industry. Coming now back to the mill level today's situation in the pulp and paper industry as for the utilization of computerized control and planning systems Fig. 2 illustrates this. Clearly there are dedicated computer control systems developed and commercially available for almost all technical subprocess in the pulp and paper mill and also several "management type" or administrative applications; but in general these systems work alone without any coordination or real-time exchange of information. This cannot be the optimal way of control when the whole mill is considered. So there is a need for coordinated operation and planning and these functions can be realized with an hierarchical system. The hierarchical production planning and control tasks in an integrated pulp and paper mill can be described with different types of hierarchy i.e. multilayer temporal and multilevel functional hierarchies. Fig. 3 shows a typical arrangement of the different steps in production planning and control in an integrated white paper mill producing several types of products (Uronen and Williams 1978). The upper part in this system is typically temporal multilayer hierarchy with the spans as marked ranging from one year until a few hours. Below this there will be the production control, efficiency and quality supervision and process control and this part of the total system can be hand~ed as a multilevel coordination and optimization problem. The tasks in this hierarchy can be grouped and organized in several different ways. Figures 4 and 5 give one possible solution (Uronen and Williams, 1978). Typically a paper mill can producE several grades and the inventory at the mill can include tens (or even hundreds) of items (grades and sizes). The production planning procedures start as depicted in Fig. 3 with a basic plan (budget) based on order history, market situation and forecasts and existing and planned production capacity at the mill (or inside the corporate). Then the planning will continue as follows: The corporation sales division takes care of all sales activities and direct contacts with customers. The customer orders will be sent from the sales department to the target mill, (if the corporate has several mills
577
producing same qualities) according to the mill production specifications and budgeted production capacity, etc. So the order stream coming to the mill will already be prescheduled by the corporate sales organization. Of course feedback from the mill situation (inventory, capacity restrictions, shut-downs, etc.) will be continuously sent to the sales department. Under present practices the normal starting point for a detailed production schedule in the mill is the production cycle with a period of several (5-7) days. The cycle means that each paper machine will produce for certain periods of time (dictated by the budget plan or order backlog) certain qualities and grades of papers during the cycle (for example first heavy weight papers, then light weight papers, then special qualities, etc.). All orders for the same quality (and items in a composite order) will be collected together to form a batch run which is as big as possible within the basic cycle. Thus, the grade changes and trimming losses,etc., will be kept to a minimum. The minimum batch amount of each quality depends on the capacity and qualities produced. The total inventory capacity represents typically about I month's production. If there are not enough orders, production will be run for inventory. If a sudden unpredictable shutdown occurs the whole cycle will be delayed. No rescheduling inside the cycle will be done. The order handling, shipping documentation, billing, etc., is computerized. The detailed production scheduling of the cycling and trimning operat~ons is today still in most cases manual but off-line operations for file searches and updating of data-banks and different types of techno-economical calculations (lot sizes, trimming for paper machines etc.) have also been computerized. The methods used for scheduling and production planning based on budget and oraer flow are typically (King 1975) branch and bound algorithms, Johnson's rule algorithm or different sorting and ranking methods or heuristics. These same methods can also be applied to direct job scheduling in finishing department and for example in trimming and cutting of paper rolls. (Gilmore and Gomory 1961, 1963) because these are more or less typical job-shop type scheduling problems. Let us consider now in a little more details the hierarchy depicted in Fig. 5. Production control, coordination and scheduling functions are different in different parts of the integrated pulp and paper mill. Therefore level III-B (Fig. 5) can be decomposed horizontally as presented. This level has been called Area Control. Now three areas are considered: the paper mill, the pulp mill and the power plant (incl. chemicals recovery and environmental monitoring and control) .
P. Uronen
578 The tasks common to each area are:
1.
2.
3.
The determination of the short term production schedules for the pulp mill and paper mill processes (Fig. S). The production rates of power plant processes are determined based on these. This determination of pulp and paper production rates is based on the long term paper production schedule which is to be realized by minimizing the costs of raw materials, energy and chemicals. Sometimes also the maximization of the paper production (or the pulp production) can be considered. The collection, updating and presentation of different reports for both operators and supervisors and to other systems like marketing, maintenance etc. Maintenance of history data files (operations, usage of raw materials, of chemicals and of energy, inventories, quality, production etc.).
4.
Maintenance of real-time data files (production, disturbances).
S.
Maintenance scheduling.
6.
R&D functions.
7.
Follow-up of the realization of the short term production schedule for each process. Determination of necessary actions in abnormal situations.
Uronen 1980) : 1.
The planned pulp production schedule must be followed.
2.
The production rate changes should be avoided and minimized.
3.
Planned shut-downs (for maintenance etc.) must be taken into account in advance.
4.
Random disturbances (machine failures etc.) should also be accounted for.
5.
The production rate of the "bottleneck" department should be maximized if the market are not restricted.
6.
Storage tanks may not become empty or overflow.
7.
Storage capacity of in-process inventories should be effectively used.
8.
There exist suitable target levels i.e. expectation values for each buffer storage at the ertd of the planning period (2 ... 3 days). That should be reached. This will help in scheduling for the next period.
9.
Liquor and chemicals should be in balance.
10.
The dynamics (retention times) of the processes must be taken into account in the schedule.
11.
The usage of cheapest fuel (i.e. the bark at the auxiliary boiler for example) must be maximized.
12.
Recovery boiler cannot be used for compensating of the short term variations in the energy balance.
13.
The steam can be indirectly stored in black liquor or in pulp.
In paper mill also following tasks will be included: 1.
Realization of rate and grade changes.
2.
Coordination and utilization of the results from an automatic paper laboratory or from in-process quality measurements (i.e. quality supervision) .
3.
In some cases also order handling can be included in the production control system at this level.
Based on the production schedule of the paper mill the needs (per quality and amount) of different pulps (and additives) are calculated and after this the operations of the pulp mill must be coordinated and optimized. This part of problem has lately been studied by several authors. (Pettersson 1969, 1970, Golemanov 1972, Tinnis 1974, Alsholm and Haglund 1977, Edlund and Rigerl 1978, Leivisk~ and Uronen 1979a, 1979b). Different types of targets, criteria and solution algorithms or methods have been suggested and demonstrated. The goals of the production coordination and control in the pulp mill can be listed as follows (LeiviskM and
Most of these requirements are selfexplanatory and for example the requirement to avoid excess production rate changes, start-ups and shut-downs is important therefore that in connection with such changes always many kind of undesirable side-effects (production losses, quality losses, decrease of yield, energy losses, extra environmental load, extra job, risks etc.) will occur. The coordination of the power plant requires following special tasks: 1.
The production schedules of different types of energy.
2.
In some cases also the optimization of purchased electricity and peak load monitoring can be included in the production control system. Very often it would be better, however,
Hierarchical Production Control to use a specific system for the optimization of purchased electricity, for instance on corporate level. The optimization of the pulp line processes and the chemical recovery cycle together with the optimal allocation of boilers and turbines takes place on the process control and optimization level, (Levels II and IlIA, Fig. 5) even though they deal with the optimization of larger process complexes. More detailed specifications for this kind of hierarchy at all levels with input and output connections and also with some hardware considerations can be found in Uronen and Williams (1978). For the coordination problem of the pulp mill production different mathematical formulations and solution algorithms have been studied, for example network algorithms (Edlund and Rigerl 1978), maximum principle (Chalaye and Foulard 1976), linear programming (Pettersson 1970), simulation (Golemanov 1972) heuristics (Leiviska, Komokallio, Aurasmaa and Uronen 1980) and different hierarchical optimization algorithms (Leiviska and Uronen 1979a,b) have been applied. Closely connected with the above discussed scheduling and coordination tasks is the necessary data collection and information part of the production planning and control system. This could also be the first step in developing the whole system. This information system is, in fact, distributed on different levels of hierarchy and in different hardware which is used in constructing the whole system. In the design of this kind of information system, following aspects must be taken into account (Leiviska Jutila, Uronen and Heikkil:i 1980): 1.
2.
3.
System specification must follow the existing organizational and operational structures. There ought to be at least one person for each sub-system who is responsible for its operation, who is using it and whose needs the system must fulfil. There are two distinct phases in the design: the specification phase based on the requirements of the system users and the implementation phase.
4.
Data transfer linking the systems together must be standardized.
5.
The impetus for the control system must come from the user.
6.
Large production control systems must be of modular type. They concentrate on collection, reduction and presentation of information. Reliability is one keyword. Human decisionmakers have the responsibility of final decisions.
7.
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The system forms inherently a hierarchy. This hierarchy is to be adapted to the existing organization, rather than vice versa.
Generally speaking, the information system deals with, at least, the following data: production rates, inventories, material flows, costs of different flows and specific consumptions of raw materials and energy. This information is collected as direct measurements or manual inputs or it is calculated from the collected process data. It must be pointed out that the development of this kind of hierarchy, Fig. 5 is designed mostly on functional basis. The hierarchy of the hardware of a possible implementation does not necessarily follow the identical structure. Today's technology gives possibilities for very versatile and flexible solutions at reasonable prices. One difficulty in building such hierarchies so far is the lack of international standardization in interfaces, communications and programming of the systems; so the compatibility of subsystems delivered by different vendors may be a serious problem. The computerization in the full scale on the process control level is not necessarily a precondition for the production control system, but the functions of the existing process control systems must be taken into account, because there is then no need to duplicate these functions. The flexibility, the modularity, the adaptability and easy-to-use features must be kept in mind during the specification of the production control tasks. As a summary for specifying and planning of this kind of system following questions should be answered and solved:
1.
General structure, how many levels etc.
2.
Tasks at different levels.
3.
User and user needs at each level.
4.
Input and output connections at each level.
5.
Manual entries and other Operator communications at each level.
6.
Degree of distribution.
7.
Data transfer techniques and methods.
8.
Hardware questions.
9.
Adaptaticn to the existing organization.
10.
Reliability and redundancy.
11.
Location of data banks.
12.
Use of databanks, unlimited for all users or restricted use.
P. Uronen
580 13.
Implementation; building above the process control blocks and using them or separate information system with bypassing the process control systems and by using direct measurements.
14.
Handling of disturbance and shutdown situations.
15.
Maintenance and updating.
16.
Benefits vs. costs.
17.
Models needed at each level.
18.
Algorithms used at each level.
19.
Method of coordination.
20.
"Optimal" level of distribution and computerization.
efficiency of utilization of capital equipment in the paper industry today. A 1.0% increase in this efficiency would mean about 650,000 tons per year of for the U.S. paper industry for the same capital investment (Hannigan, 1978).
Many of these questions still need a lot of research work but none of them can be solved by the researchers or vendors alone; the viewpoints and needs of the users are essence.
b.
There is a potential productivity gain of about 5% through the better coordination of interacting departments and their related buffer storage (Edlund, Rigerl, 1978) .
c.
with modern recovery boilers showing efficiencies of the order of 65% and older systems running as low as 40-45%, there is a very great potential for energy savings in this area through better control and coordination.
d.
Labor productivity can be improved with a complete measurement and reporting system coordinated with engineering performance standards in a hierarchical system. According to Geisel (Geisel 1978) one container corporation has cut labor costs per ton by 19% during the past eight years with a productivity measurement system, and a 2.5% decrease in material waste on a case line has also been reached.
BENEFITS OF HIERARCHICAL PRODUCTION PLANNING AND CONTROL SYSTEMS It is a well-documented fact that the individual computer control systems in pulp and paper industry have been successful giving remarkable gains in terms of increased throughputs, higher yields, lower raw material and energy usage and higher quality. The general advantages of hierarchy were already discussed. In addition to these there is a long list of other, often intangible, gains which are available, particularly from the coordination capabilities of a hierarchical planning and control system, which need to be mentioned. Some of these are as follows: (Uronen and Williams 1978)
1.
2.
3.
4.
Faster availability and more frequent updating of information flow from the plant to management thus aiding decision making at all such levels. Plant production and operational aata (both current and historic) will be much more precise and time coordinated than is possible with manual methods. This is a major aid to long term planning, Plant data system can detect trends in plant operations. These and other plant data available from the system will readily permit the testing of various plant operating strategies prior to actual implementation. Some examples of gains are obtained from these kinds of systems: a.
There is about a 90% average
5.
Full plant optimization studies are possible only with the full availability of plant operating data supplied by a hierarchical system.
6.
Fast and effective monitoring of effluents and emissions can often prevent major leaks and the resulting damage or loss.
7.
Savings in operational personnel and other staffing (Thompson, 1978).
Some specific benefits of the distributed hierarchical system architecture are as follows: 1.
Flexible system configuration - distributed subsystems may be modified, replaced, or deleted without upsetting the rest of the system.
2.
Graceful degradation - failure in one or more components or subsystems will not cause the entire system to fail.
3.
High systems reliability due to: a.
Easy to add parallel redundant units and subsystems which can be incorporated to back up and duplicate the functions of the main components and subsystems.
Hierarchical Production Contrul b.
Transmission of partially processed plant information allowing: i)
ii)
4.
Decreased data rates since processors are distributed to functional areas and only processed information need be sent between any two subsystems rather than raw data as formerly. Use of error detection codes which allow any fault or casualty condition in the system to be detected and identified by the processor in its area of responsibility.
But clearly there are also a tendency and justified needs for coordination between these systems and combining them into a hierarchical total mill information and planning system. Fig. 6 demonstrates the three "generations" of process control systems in pulp and paper industry. It is very understandable that the development and implementation of the whole hierarchy is a project of several years demanding remarkable investments and resources; so some kind of piece-wise or modular system approach seems economically most promising. If the compatibility problems and other standardizing questions can be solved satisfactorily the building by starting from existing process control packages is feasible.
Lower cost due to: a.
Simplified hardware configuration packaging. Since processors need not be large due to the reduced processing requirements of each processor.
b.
Simplified software because functions are carried out by several small, locally responsible processors, not by a large machine that must perform all of the control functions and calculations within the entire control system.
c.
Large scale integration technology.
d.
Multiple use of standard components. Many different subsystems can use identical hardware to perform varied functions.
e.
Ease of incrementally increasing capability since units may be added to the system without drastically interfering with the functions of the rest of the system.
f.
Simplified installation since common data channels can be used for processor-to-processor communication. This eliminates the need for individual multiplewire cables between any two units.
CONCLUSIONS As already mentioned earlier the "normal" situation in an integrated pulp ana paper mill today is the increasing use of separate dedicated process computer system.
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oc
other possibility is to first build a suitable information system and computerized planning tool for the production planner separately from process control systems (Edlund and Rigerl 1978). I believe that both of these approaches can and will be used;~o which extent and how rapidly depends very much on the further development work and general economic situation in the pulp and paper industry. There exist already some hierarchical systems in operation in several mills in Finland and in Sweden (Eriksson 1978, Petersson and RUckert 1978) and both of the above mentioned approaches have been used. However these systems vary very much in their tasks, in hardware and software used and in their sophistication of hierarchy. Today we are in a situation where 80% of the paper will be produced during other than normal day-shift when all the management and other key-persons for making decisions are on site. This necessitates the development of tools and techniques for the assistance of the operators and according to my opinion the hierarchical production planning and control systems are one very useful and effective tool for this purpose. In theory almost everything in a pulp and paper mill could be automated today. The question remains how do we use most effectively the techniques available and how do we combine the human resources and automation in a modern mill i.e. what is the optimum level of automation?
P. Uronen
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REFERENCE Ahlsholm, 0., and L. Haglund. (1977). Computer network for process control and production coordination of a big integrated pulp and paper mill. Preprints 1977 International Symposium on Process Control in the Pulp and Paper Industry, May 1-4, Vancouver.
for Applied Systems Analysis, Laxenburg, Austria. Geisel, C.E. (1978). Productivity measurement, A prelude to improvement, Tappi, 61, No. 8. Geoffrion, A.M. (1970). Elements of largescale mathematical programming. Management Sci. Theory, 16, 652-691.
Al-Shaikh, A. (1978). New Paper Machine Control Strategies including field and economic results, International Measurex Symposium on Process Control, Monterey Ca., September 24-27.
Gilmore, P.C., and R.E. Gomory. (1961). linear programming approach to the cutting-stock problem - Part I. Operations Research, Vol. 9, No. 6.
Athans, M. (1974). Survey of decentralized control methods. 3rd NBER/FRB WorkShop on Stochastic Control, Washington D.C.
Gilmore, P.C., and R.E. Gomory. (1963). A linear programming approach to the cutting-stock problem - Part II. Operations Research, Vol. 11, No. 6.
Athans, M. (1978). Advances and open problems on the control of large scale systems, Plenary Paper; IFAC 1978, Helsinki, Vol. 4, 2371-2382.
Golemanov, L. A. (1972). Systems Theoretical Approach in the projecting and control of Industrial production Systems. Ekono Publication No. 133, Helsinki.
Bailey, F.N. (1976). Decision processes in organizations In Large-Scale dynamical systems (ed. R. Sacks). Point Lobos Press, California.
Hannigan, J. (1978). Productivity as I see it, Tappi, 61, No. 8.
Benders, J.F. (1962). Partitioning procedures for solving mixed-variables programming problems. Numerische Mathematik,-!, 238-252. Chalaye, G., and C. Foulard. (1976). Hierarchical control of a pulp mill. Proceedings of 3rd International Conference on Instrumentation and Automation in the Paper, Rubber and Plastics Industries, Brussels. Danzig, G.B., and P. Wolfe. (1960). Decomposition principle for linear programs. Operations Research, ~, 101-111. Drew, S.A.W. (1975). A study in the application of large scale control methods to a practical industrial problem. Proceedings of the 6th IFAC World Congress, Boston. Edlund, S.G., and K. H. Rigerl. (1978). A Computer-based production control system for the coordination of operations in a pulp and paper mill. Proceedings of the 7th IFAC World Congress, Helsinki. Eriksson, L. (1978). Survey of multilevel computer control systems in the pulp and paper industry. Proceedings of the 7th IFAC World Congress, Helsinki. Findeisen, W. (1978). Hierarchical control systems - an introduction; Professional Paper PP-78-l, International Institute
A
Hax, A.C. (1976). The design of large scale Logistics Systems: A survey and an approach In Modern Trends in Logistics Research (ed. W. Marlow), M.I.T. Press. Hax, A.C., and J.J. Golovin. (1978) Computer based Operations Management Systems (COMS), In Studies in Operations Management (ed. A.C. Hax ) North Holland - American Elsevier. Hax, A.C., and H.C. Meal. (1975). Hierichical Integration of Production Planning and Scheduling. In Studies in Management _S_c_i_e_n_c_e_s--,-,_V_o_l_._I_L_o_g....l_·s_t_i_c_s. (ed. M. A. Geisler). North Holland - American Elsevier. Hirnmelblau, D.M. (Ed) (1973). Decomposition of Large Scale Problems, North Holland Publishing Co., Amsterdam. Ho, Y.C., and K.C. Chu. (1974). Information Structure in dynamic multi-person control problems, Automatica, 10, 341-351. Jutila, E.A.A., S. Kauppinen, K. Mensonen and A. Ollila. (1978). Special features of Computer Control of a continuous digester and diffuser washer. Paperi ja Puu, 60, 10, 573-588. King, J.R. (1975). Production Planning and Control, an Introduction to Quantitative methods, Pergamon Press, Oxford. Lefkowitz, I. (1966). Multilevel Approach applied to control system design, Trans. ASME, Vol. 88, No. 2.
Hierarchical Production Control Lefkowitz, I., and A. Cheliustkin Editors (1976). Integrated systems Control in tne Steel Industry, State-of-theart review and proceedings of the conference, June 30 - July 2, 1975, International Institute for Applied Systems Analysis, Laxenburg, Austria. LeiVisks", K., and P. Uronen. (1979a) . Dynamic Optimization of a sulphate mill pulp line. IFAC/IFORS Symposium "Comparison of Automatic Control and Operational Research Techniques Applied to Large Systems Analysis and Control", Toulouse. Leivisks', K., and P. Uronen. (1979b). Dynamic Optimization of a sulphate pulp mill, IFAC Symposium Optimization Methods, Applied Aspects, Varna. Leiviska, K., and P. Uronen. (1980) . Different approaches for the production control of a pulp mill, IFAC Conference PRP 4, Ghent. Leivisk!, K., H. Komokallio, H. Aurasmaa and P. Uronen. (1980). Heuristic Algorithm for production control of an integrated pulp and paper mill. To be presented in the 2nd IFAC Symposium Large Scale Systems; Theory and Applications, June 16-19, Toulouse. Leiviska, K., E. Jutila, P. Uronen and S. Heikkila (1980). Production control of complex integrated mills, Computers in Industry, Vol. 2 (in print). NorthHolland Publishing Company, Amsterdam. Mesarovic, M.D., D. Macko and Y. Takakora. (1970). Theory of Hierarchical, Multilevel Systems, New York, Academic Press. Miyazaki, Y., Y. Sakairi, T. Okano, J. Arakawa and K. Suzuki. (1978). Integrated Computer System at Oita Steel Works. Proceedings of the 7th IFAC World Congress, Helsinki. Peterson, E., and H. Rllckert. (1978). Total Computerized production control, PPI, April 1978, pp. 77-82. Petterson, B. (1969). Production Control of a complex integrated pulp and paper mill, Tappi, 52, 11.
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Pettersson, B. (1970). Mathematical methods of a pulp and paper mill scheduling problem, Report 7001, Division of Automatic Control, Lund Institute of Technology, Lund. Rosen, J.E. (1964). Primal Partition Programming for block diagonal matrices. Numerische Mathematik, 6, 250-260. Sage, A.P. (1977). On the application of systems methodology to economic and organizational management of integrated industrial complexes, Proceedings of the IFAC Workshop Control and Management of Integrated Industrial Complexes, Toulouse, France, 6-8 September. Sandell, N.R., P.P. Varaiya and M. Athans. (1975). A Survey of Decentralized control methods for large scale systems. Proceedings Engineering Foundation Conference on Systems Engineering for Power Systems, Henniker, New Hamshire. Singh, M.G. (1977). Dynamic Hierarchical Control, North Holland Publishing Company. Tamura, H. (1975). Decentralized optimization for distributed time-lag models of discrete systems, Automatica, 11, 6, 593-602. Thompson, L. J. (19'78). Executive Decision: What's the bottom line, PlMA, July, pp. 21-25. Tinnis v. (1974). An Optimum Production Control System. Pulp and Paper Magazine of Canada, 75, 7. Uronen, P., and T.J. Williams. (1978). Hierarchical control in the pulp and paper industry. Report No. III Purdue Laboratory for Applied Industrial Control, West Lafayette. Uronen, P. (1980). Management Systems in the Forest Industry; An overview, Working Paper. International Institute for Applied Systems Analysis, Laxenburg, Austria. Williams, T. J. (1978). Hierarchical Control for Large Scale Systems - A survey, Proceedings of the 7th IFAC World Congress, Helsinki.
584
P. Uronen
~RAJ
~or
Id '!'c.ldc 'l·c·chnologic.ll Ch.lllgl"
Enl>rqy
1
NATIONAL AND
REGIONAL
Requlations Poiicies, Ra~ MaterIal Inflation, rinanclng Labor Force
r CORPORATE
Corporate Plannina Forest Manaqcmer.t Resource Aliocat10n Management Systems
l' Management Systems Production Planning and Coordination Process Control and Optimization
MILL
Fig. 1.
Range of Plannino'Problems in Forest Industry.
El
MANAGEME:'lT AN 0 ADtiINISTRATtON
PAPER MILL
PULP MILL
l{J
l!!J [;J
~
El
Gll DEDICATED COMPUTER SYSTEMS FOR: Batch digesters (SA.SI) Kamyr digesters (SA. SI. NSSC) Bleach plant Recovery boilers Washing & screening Evapora tors Lime kiln & causticization Energy management etc. Fig. 2.
DEDICATED COMPUTER SYSTEl1S FOR: Stock preparation TMP. refiners On-machine CO.1ter Coating paste Roll handling Laboratory etc,
Computer Systems in the Pul~ and Paper Mill Today.
@
[UJ "BUSINESS" COMPUTERS FOR:
Payroll Sales. Inventory Bookkeeping Techno-economical Calculations etc.
Hierarchical Production Control
585
(Management)
Pr ices of 1 ..... 1iateri.l8 , Chemicals, Energy, ete.
~
Orders
Pulp 1'11.11
I
~
Energy Chemic.ls Paper Mill
Fig.
3.
Production Planninq in a White Paoer Mill.
" , G MJ\NAGE"'.E~T
DATA PRCSI::NTATION
(LEVEL Cl)
Other
Areas
(LEVEL 3B)
SUPERVISOR'S CONSOLES
Other
Supervisory Computers of the Same Area
(LEVEL 3A)
(LEVEL 2)
(W:VEL 1)
PROCESS
Fig. 4.
Hierarchical Control Levels.
P. Uronen
586
!:!!!U! IVI
KIS
KAHACEKINT
llO'OlHATION PRODUCTION PUNNINC
PRODUCTION SCHEDULING
I
1
~ ~
OODYARD'
KAMYR.
WASHING COENING
2
5
L!ACHING'
BLEACH CHEMICAL REPARATION
Fig.
5~
~
LEVIL 1111
IECOVER.Y
EHEJ.GY
1
OWER IOILER.
TUUlNE • GENiIlATOR WATER TUATKENT PURCHASED POWER.
3
EMVIROKKENT
PAPER KILL
III
~VAPORATORS. RlCOVERY IOILlR AUSTICIZAnON AND LIKE ~ILN
~ASTE WATER TREATHENTS
10
t
(AUA C0In1l0L) DETAILED SCUD-
ULIHC. COOlDlRATION. QUALln CONTROL AND OPTIMIZATION
~ADDITIV!S.
6 Stoa pupSPECIAL KEASUI.EAl.ATIONS KENTS 7 ON-HACBllf! MONITORING AND 8 lOLL BANDLtNG ALAIMING AIID rlN1SBUIC 9 LAlOIlATOIY
LEVELS I, 11 AND 1111. PROCESS
CONTiOL
Hierarchical Control Applied to the Pulp and Paper Mill.
1970-1980
1960-1970
I
I I
PROCESS CONTHOL SYSTEMS
TOT AL 1·11 LL CO~~TROL
I I
~
PROCESS CONTROL SYSTEMS
r I
1980
A;'~D
}tAt~';GEr-a:::T
MhNP.GE;·\Ei;T SYSTeMS
SYSTeM
___ - - - - J
centralized
hard~are
t-'.ANAGEH£!~T SYSTE~S
mini-and midicomputers
distrib~tec harc~~r~
big cor..puters
separate departments
hicrarchic.:11 stru..:turc
in-house systems
"packaged" systems
taylormade systerr.s
Develo~ment
of Control and Manaqement Systems.
Fig. 6.