Decision making in control systems based on data analysis

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.

Analysis of Satisfaction in the Use of Technological Simulation Tools in the Learning of the Automatic Process Control Course

The objective of this article is to describe the satisfaction of the students in the use of technological simulation tools in the learning of the automatic process control course, generated by distance education. The Academic Satisfaction Scale (ESA) was used as a measurement instrument. As the research was carried out, the re-sults revealed that of the indicators that present the highest degree of satisfaction, 56.8% of the student’s state that they strongly agree with what was learned through the use of technological simulation tools in the subject of the course of control of automatic processes and 54.5% indicate that the technological tools used in the contents of the subject excite them. Likewise, by means of the R squared, it can be indicated that the satisfaction of the students with the developed subject, in which technological simulation tools were used (I6), influences 0.637, that is, 63.7%, on the general satisfaction of academic experience in the virtual environment (I7); This is translated with the following equation: I7 = 0.309 + 0.637 * I6.

Demonstration of a Top-Lit Updraft Based Pyrolytic Burner with Low Emission Operation and Automatic Process Control

In this study, a small-scale (4.7 kWfuel) biomass burner based on “top-lit updraft” (TLUD) technology with automatic process control was developed for process heat generation. The combustion experiments were performed using wood pellets to gain more insights on the process, its repeatability and the behaviors of the emitted gaseous and particulate emissions under different combustion phases. The emission values were compared with similar small-scale combustion technologies as well as the emission limits defined in official regulations. The results showed that the average emissions (based on standardized 13 vol. % O2 content in the dry flue gas (STP)) over the entire process from start-up to switch-off were 29.4 mg/m3 for CO, 80 mg/m3 for NOx, and 3.6 mg/m3 for total particle matter (TPM) measured within the hot gas. These results were below the official limits for wood-fueled small-scale systems. The developed process control approach resulted in very low residual O2 content in the flue gas (approx. 2 vol. %), high flue gas temperatures and repetition accuracy. Thus, the process offers potential for further development in terms of process control, scale-up, and application in different areas.

Development of Arc Welding Technology with Support of Stability of Electrode Melting Process

Mechanized arc welding is divided into two main varieties: with self-regulation of the electrode melting process and with automatic process control. The common thing between self-regulating mechanized arc welding and manual arc welding is that in the welding equipment there are no means for automatic control with feedback from the arc. The difference between them is that stabilization of the electrode melting process in mechanized welding is carried out by the source itself, which has a particular volt-ampere characteristic (CVC), by a corresponding spontaneous reaction to a change in the situation in the arc. This method is significantly inferior to the method with automatic process control in precisely maintaining the specified parameters and has a limitation on the minimum current density on the electrode. The method of pulse self-regulation of the electrode melting process proposed in the E.O.Paton EWI removes this problem. However, it requires the use of power sources with a complicated, multi-link CVC curve. Further improvement is revealed through the use of digital controlled, programmable power supplies that have an automatically generated CVC. The combination of automatic source control and self-regulation by the spontaneous reaction to the situation in the arc creates a new hybrid way to stabilize the process of arc welding with a consumable electrode and other related arc processes (surfacing, soldering, re-melting).

Jet grinding as a control object

The relevance of the subject of this work is determined by the need to reduce the energy consumption of fine grinding by controlling the process, which is proposed to implement based on the results of acoustic monitoring. The paper describes the operation of a jet mill in a closed cycle. It is known that fine grinding refers to energy-intensive production, but jet grinding is indispensable in obtaining thin and ultra-thin "pure" materials, i.e. materials without the introduction of any impurities. And with the creation of a new way to control the process, there is a real opportunity to reduce energy consumption by jet mills while maintaining optimal performance. Based on the process parameter analysis input and output disturbing and control process parameters are selected. In this way, jet grinding is presented as a control object. The problems of jet grinding and ways to solve them are shown. This became the basis for further construction of automatic process control based on the acoustic signals of the grinding zone.

MAIN CHARACTERISTICS OF ELEMENTS OF A TWO-CIRCUIT AUTOMATIC

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.