On the techno-economic evaluation of automated control and management systems for continuous technological processes
Abstract Generated abstract
This paper proposes a methodology for the technical and economic evaluation of automated control and management systems for enterprises with continuous technological processes, particularly in chemical and oil-refining industries. It argues that justification should proceed through assessment of potential economic effect, selection of economically efficient design variants, and later determination of actual efficiency, using payback period or an efficiency coefficient as the principal criterion. The authors outline a technical-economic graph model linking sources of savings, process disturbances, system functions, technical device complexes, and costs, with emphasis on reducing the technological component of production cost. The paper concludes with a staged procedure for predesign analysis, system design, and post-implementation evaluation, while noting that quantitative relationships and implementation experience remain insufficiently developed.
Full Text
ON THE TECHNICAL AND ECONOMIC EVALUATION OF AUTOMATED CONTROL AND MANAGEMENT SYSTEMS FOR CONTINUOUS TECHNOLOGICAL PROCESSES
Yu. M. Ageev, V. I. Konovalov
(Presented by the scientific seminar of the Department of Automation and Telemechanics)
At present, automated management systems are being developed intensively for enterprises, shops, and individual sections of the chemical, oil-refining, and other branches of industry. An exceptionally important issue in this connection is the technical and economic justification of such systems. The present work is devoted to consideration of a methodology for the technical and economic analysis of designed control and management systems for enterprises with continuous technological processes.
The technical and economic justification of designed automated control and management systems for operating technological processes presupposes the solution of three main tasks:
— assessment of the potential economic effect;
— assessment of the economic efficiency of the system being designed and the selection of optimal technical solutions;
— determination of the actual economic efficiency.
To solve these tasks, a technical and economic model of the technological process with a control and management system is needed, one that would establish a quantitative relationship between the system optimality criterion, the sources by which savings are formed, the technical means of control and management, and their cost.
The sequence of work for constructing the technical and economic model and solving the formulated tasks may be represented in the form of the graph shown in Fig. 1, where the numbers denote:
Fig. 1
1 — formulation of the indicator of economic efficiency;
2 — analysis of the technological process for the purpose of identifying and classifying the causes affecting the efficiency indicator and the degree of their influence;
3 — analysis of ways to eliminate the causes or reduce their influence on the efficiency indicator;
4 — selection of technical means that make it possible to implement methods for eliminating the causes, and determination of their cost;
5 — evaluation of the effectiveness of the control and management system being designed.
At present, the payback period of the system or the efficiency coefficient [1] is used as the indicator of economic effectiveness by which a decision is made on the need to develop one or another variant of a control and management system. For most modern continuous chemical-technological processes, savings from the introduction of the system can be achieved mainly by reducing the technological component of cost, since the cost of raw materials, intermediate products, and energy of all kinds is the main item in calculating the cost of the products manufactured.
The technical-economic model of the objects mentioned, reflecting the principal qualitative interrelationships, can be represented by a graph diagram, the adjacency matrix of which is illustrated by Table 1. The lower part of Table 1 indicates the main groups of causes whose elimination or reduction by the system being developed will make it possible to obtain savings from introduction of the system. Tables 2–4 show, through the performance of which functions and with the aid of which technical devices a particular group of causes can be eliminated. By estimating the cost of the necessary technical means, as well as the planned savings, it is possible to estimate the payback period of the system.
At the stage of predesign studies, the potential economic effect should be estimated and a decision made on the advisability of developing a control and management system. The potential economic effect is calculated on the condition that all the causes indicated in Table 1 are eliminated. To do this, it is necessary to analyze the technological process of the existing control and management system and to establish the quantitative interrelationships among the events of the graph diagram. At this stage one may restrict oneself to the links marked in the adjacency matrix (Table 1) with a “plus” sign. If the annual potential economic effect amounts to 300–500 thousand rubles or more, a decision may be made on the need to develop, for the process under consideration, an automated control and management system with a developed computing device. Naturally, the limiting value of the potential economic effect given here is approximate. Its exact value should be determined on the basis of experience in designing and implementing analogous systems at related enterprises; unfortunately, at present this cannot be done mainly for two reasons. First, little such experience has been accumulated in our country, and, second, during implementation the economic effect actually obtained is not properly evaluated.
When designing the system, the functions must be determined and the tasks that this system is to solve must be listed; the technical means required for this must be selected; and at each design stage the most optimal variant in the sense indicated above must be chosen. For this purpose it is necessary to know the quantitative relationships among the individual elements of Tables 2–4.
Similar qualitative relationships have been presented in works [2, 3], but quantitative relationships have not yet been established. Much work remains to be done in this direction to generalize the experience of introducing automated control and management systems at various enterprises.
Table 1
| No. | Elements of the graph model | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Payback period | |||||||||||||||||||||||||||||
| 2 | Capital expenditures | 1 | ||||||||||||||||||||||||||||
| 3 | Savings from implementation of the system | 1 | ||||||||||||||||||||||||||||
| 4 | Reduction of cost | +1 | ||||||||||||||||||||||||||||
| 5 | Increase in process reliability | 1 | ||||||||||||||||||||||||||||
| 6 | Increase in the mass of profit | 1 | ||||||||||||||||||||||||||||
| 7 | Savings of capital investments | 1 | ||||||||||||||||||||||||||||
| 8 | Improvement of quality | 1 | ||||||||||||||||||||||||||||
| 9 | Conditionally fixed expenses | 1 | ||||||||||||||||||||||||||||
| 10 | Wages | 1 | ||||||||||||||||||||||||||||
| 11 | Transportation and procurement expenses | 1 | ||||||||||||||||||||||||||||
| 12 | Auxiliary materials | 1 | ||||||||||||||||||||||||||||
| 13 | Technological component of cost | 1 | ||||||||||||||||||||||||||||
| 14 | Change in the price and quality of raw materials, etc. | +1 | +1 | 1 |
Continuation of Table 1
| No. | Elements of the graph model | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 15 | Losses from rejects | 1 | ||||||||||||||||||||||||||||
| 16 | Raw-material costs | +1 | ||||||||||||||||||||||||||||
| 17 | Energy costs | 1 | ||||||||||||||||||||||||||||
| 18 | Productivity of technological equipment | 1 | 1 | 1 | +1 | |||||||||||||||||||||||||
| 19 | Output technological parameters | 1 | 1 | +1 | 1 | |||||||||||||||||||||||||
| 20 | Dosing of components | 1 | ||||||||||||||||||||||||||||
| 21 | Equipment downtime | +1 | ||||||||||||||||||||||||||||
| 22 | Deviations of technological parameters | 1 | ||||||||||||||||||||||||||||
| 23 | Plan | 1 | ||||||||||||||||||||||||||||
| 24 | Rhythmicity of control | 1 | ||||||||||||||||||||||||||||
| 25 | External causes | 1 | 1 | |||||||||||||||||||||||||||
| 26 | Failures of technological equipment | 1 | 1 | 1 | 1 | |||||||||||||||||||||||||
| 27 | Failures of instrumentation and control equipment | 1 | ||||||||||||||||||||||||||||
| 28 | Violations of technological discipline | 1 | ||||||||||||||||||||||||||||
| 29 | Incorrect actions of the operator | 1 | 1 |
Table 2
| System functions | External causes relative to the shop, section | Failures of technological equipment | Violations of technological discipline | Failures of instrumentation and control devices | Incorrect actions of the operator | Arrhythmicity of control |
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 |
| Drawing up production programs ensuring a minimum of losses | 1 | |||||
| Operational planning | 1 | 1 | ||||
| Determining the volume of reserves | 1 | |||||
| Determining the optimal duration of individual production cycles | 1 | |||||
| Current and final accounting of products, raw materials, energy | 1 | 1 | ||||
| Calculating current generalized process indicators | 1 | 1 | ||||
| Refinement and correction of algorithms on the basis of previous activity | 1 | 1 | ||||
| Obtaining current information about the process | 1 | 1 | 1 | 1 | ||
| Detecting deviations of parameters, signaling, recording | 1 | 1 | ||||
| Determining the “bottleneck” of production | 1 | 1 | ||||
| Forecasting generalized indicators | 1 | 1 | ||||
| Forecasting technological parameters | 1 | 1 | ||||
| Forecasting pre-emergency situations | – | 1 | 1 | |||
| Determining the optimal mode of the technological process | 1 | 1 | 1 |
Continuation of Table 2
| 1 | 2 | 3 | 4 | 5 | 6 | 7 |
|---|---|---|---|---|---|---|
| Detection of the causes of disruptions in the technological process | 1 | 1 | 1 | |||
| Maintaining the optimal mode | 1 | 1 | 1 | |||
| Self-checking | 1 | |||||
| Process control in emergency situations | 1 | 1 | 1 |
Table 3
| No. | Complexes of devices, mathematical support | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Operational control system | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ||||||||||
| 2 | Dispatching system | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ||||||||
| 3 | Information-computing machine | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |||||||||||
| 4 | Machine in advisor mode | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ||||||||
| 5 | Centralized control machine | 1 | 1 | 1 | 1 | ||||||||||||||
| 6 | Control computer | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | ||||||||
| 7 | Protection system | 1 | 1 | 1 | 1 | 1 | |||||||||||||
| 8 | Optimizers | 1 | |||||||||||||||||
| 9 | Technological-process model | 1 | 1 | 1 | 1 | ||||||||||||||
| 10 | Separate dependencies between parameters, indicators | 1 | 1 | 1 | 1 | 1 | |||||||||||||
| 11 | Economic model of production | 1 | 1 | ||||||||||||||||
| 12 | Technical-economic model of production | 1 |
Table 4
| No. | Technical devices | Device complexes (according to Table 3): 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Information-collection devices | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
| 2 | Information sensors | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| 3 | Information-forming devices | 1 | 1 | 1 | 1 | 1 | |||
| 4 | Information-reproduction devices | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
| 5 | Information-transmission devices | 1 | 1 | ||||||
| 6 | Computing devices | 1 | 1 | 1 | 1 | 1 | |||
| 7 | Controllers and actuating devices | 1 | 1 | 1 | 1 |
Thus, the methodology for the technical-economic evaluation of automated control and management systems designed for existing facilities is as follows:
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At the pre-design stage, an indicator of economic efficiency is formulated, a technical-economic model of the process with the existing control system is developed, the potential economic effect is determined, and a decision is made on the need to develop the system.
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At the design stages, the functions of the control and management systems are determined, the specific tasks that the system must solve are enumerated, technical means are selected, the cost of designing, manufacturing, and operating the system is assessed, and the most optimal variant is chosen.
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In the course of operating the system, the actual economic effect from introducing the system as a whole and from performing its individual tasks is assessed. The experience accumulated in this way will be used for designing similar systems in the future.
REFERENCES
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Standard methodology for determining economic efficiency. Gosplan of the USSR, Gosstroy of the USSR, Academy of Sciences of the USSR, 1969.
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V. S. Medynskii. Automation of chemical processes using computing technology and its economic efficiency. In: Automation of chemical processes using computing technology and its economic efficiency (Conference abstracts). Kiev, 1969.
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S. I. Lukashevich. Determining the economic efficiency of automation of production management. Moscow, 1969.