Technological processes are always accompanied by deviations from the set mode, which is due to the influence of many external and internal factors. The environmental parameters, the components of input raw materials, and the condition of technological equipment are constantly changing, which requires solving the problem of finding the optimal control parameters and, in some cases, the parameters of the process itself.
Most industries are focused on obtaining the final product with a given level of quality. Changes in parameters of the technological process may deteriorate the quality of production and cause defects or even emergency situations. To prevent this, forecasting methods are used.
The task of constructing predictive models based on experimental data is relevant for a wide range of technological processes. Today, predictive models are widely used in management, diagnosis and identification. The vast majority of these models are based on artificial intelligence technologies or methods of mathematical statistics.
The most widespread forecasting models find application in areas such as banking, insurance, business economics, medicine, diagnostics of technical components and equipment, and forecasting the parameters of technological processes.
Despite the well-developed algorithm for model development and application, the main problem that remains is to acquire data, select an appropriate model structure, and integrate the model into existing control systems.
The paper will predict the parameters of the technological process of methanol production under reduced pressure. The production of methanol under reduced pressure is a multi-stage process, and the emergence of problems at some stage will adversely affect further work and the end result.
Note that there are all problems related to the performance of technological processes in the production of methanol, which are described above. Therefore, another task is to forecast emergencies, taking into account the indicators of all stages in the process. The development of models for forecasting emergencies and controlling thermal regimes and their further integration into the existing automatic process control system is proposed to be performed according to the principles of industrial revolution – Industry 4.0.
Important components of Industry 4.0 are the Internet of Things, data analysis, and digital duplicates. Each of these components solves a partial problem and, collectively, they provide full automation of production, forecasting of real-time process indicators, and calculation of optimal control.
The process of methanol production under reduced pressure can be fully automated in accordance with the components of Industry 4.0. First, there is instrumentation that allows the values of technological process to be obtained over time. Second, given a moderate size of these data, one can obtain models of control objects, perform their software implementation, and use them to calculate optimal control or predict the state of the process.
The paper proposes a variant of constructing a virtual model based on experimental data and its further use with actual values of process parameters.
A regression model was chosen to develop a model for predicting the temperature regime. Regression analysis allows checking the statistical significance of the parameters, assessing the adequacy and accuracy of the model, and establishing the nature and closeness of the relationship between the studied phenomena.
It is also important to predict the occurrence of emergency (adverse) situations at the workplace. For this purpose, it is necessary to determine a list of these situations according to the technological regulations and develop a model for forecasting emergencies. There are various forms of presenting a model for forecasting emergencies. A decision tree is one of them. It will be developed for the production of methanol.
The resulting tree is a graphical structure of the verbal (semantic) model relying on the expert's reasoning in solving problems related to emergencies. This is a network structure, whose nodes indicate potential deviations of the control object from the normal mode of operation. The resulting tree is used to solve forecasting and diagnosing problems.
For practical use, the decision tree is implemented in software as an "if - then" set of rules. The software is used as an element of a higher-level system in relation to the existing automatic process control system.
Uneven quality of ore feed to a milling plant makes considerable difficulties in processing. The national and foreign experience, analytical calculations and special experiments prove that reduction in quality variation of crude ore fed for the processing leads to an essential increase in production efficiency, to improvement of final product quality and to simultaneous economy. The article describes the research findings on implementation of a two-level management digitization model for a mining and processing integrated works based on the simulation and mathematical model of production cycle processes. With regard to the developed procedure for description of process flows, an automatic process control system is proposed for the underground and surface mine infrastructure management using a single information and maintenance support. Considering actual background of Belaruskali mines and mills in terms of local automation of certain processing circuits, as well as based on the development and introduction of the concept of digitization of rating, modeling and prediction of process flow parameters for ore preparation, extraction and milling, using the modern methods and means of the mining and processing works management, it is possible to create an integrated automated on-line management system for all process flows. This system allows following-up of operation in any face and on any level in a mine, as well as any process stage at a milling factory and checking their compliance with the control criteria.
The article presents the following materials:
1) Developed two-circuit automatic process control system on a lathe, designed to perform finishing types of treatments.
2) The developed automatic system provides regulation of two parameters of technological process: constancy of the tool feed and the gap in the hydrostatic guides is independent of changes in cutting forces, which ensures the accuracy of geometric dimensions and the quality of the product surface;
3) since one of the elements determining the high-quality operation of a hydrostatic pair is an information-measuring device-a differential inductive sensor, calculations of its parameters are given, as well as the characteristic of the amplifier to this sensor.
The paper presents a model of effective interaction between the test and measuring devices and automation (I) and the automatic process control system (APCS). The ”Upgrading software and hardware complex test stands № 2, 3, 4” is directed on the efficiency and reliability of constituent equipment used in the operation of the test rig with diesel generator sets trials.
Keywords: Automatic control and industrial control systems, instrumentation and automation, upgrades, software and hardware.
In this work, we have obtained multi-purpose optimization of the baklava production process based on technologies of agent systems and the intelligent process control environment. The general architecture of the control system intelligent environment with agent technologies for recognizing abnormal situations is developed and adaptive baklava production regulators are synthesized. The proposed approach to the construction of an automatic process control system with an intelligent environment is to increase the efficiency of baklava production.
This article contains materials on experimental research of efficiency of the automatic system developed by us at turning .
The processing of a step part was carried out on 1K62 lathe with and without automatic
Thus the corresponding results proving efficiency of application of automatic control system of machine operation modes were received: increase of accuracy of geometrical sizes, decrease of roughness of a surface of a detail.
The developed automatic system on the basis of received results of the experiment can be recommended for application on other types of machine tools.
Aluminium coatings that are formed by physical vapour deposition (PVD) on rolled steel products are more resistant to atmospheric and seawater corrosion than zinc coatings. We developed a coating thickness analyzer (CTA) with an X-ray fluorescence (XRF) measuring head, that is integrated into the PVD pilot line. In this study, to conduct measurements of elements with atomic numbers less than 20 while avoiding the problem of registration of light elements, the measuring head was integrated into a process vacuum chamber to maintain a vacuum during the measurements. To validate the proposed tool, cold-rolled steel strips of different grades are used as substrates, and aluminium was deposited on the surface via PVD in thicknesses ranging from 1 to 20 g/m2. The thin-film thickness measurements during a pre-acceptance test were found to have a relative accuracy of less than 5% and a relative precision of less than 1% – 2%. The proposed CTA can be readily integrated in the factory’s automatic process control system and the real-time measurements in operating and calibration modes, and the status of all spectrometric equipment (X-ray tube, detector etc.) can be transmitted to the upper-level computer. Thus, the process engineer can properly control the deposition process.