Defense of the dissertation of Kuzhukhanova Zhadra for the degree of Doctor of Philosophy (PhD) in the specialty «8D07102 - Automation and control»

L.N. Gumilyov Eurasian National University, a dissertation defense for the degree of Doctor of Philosophy (PhD) by Kuzhukhanova Zhadra on the topic «Decision support system for managing primary oil refining process control» to the educational program «8D07102 – Automation and control».

The dissertation was carried out at the «System analysis and management education department» of L.N. Gumilyov Eurasian National University.

The language of defense is kazakh

Official reviewers:

- Myrzasheva Aigul Narmaghanbetovna – Candidate of Technical Sciences, Associate Professor of the Department of Mathematics and Methods of Teaching Mathematics of the “Kh. Dosmukhamedov Atyrau University” (Atyrau, Republic of Kazakhstan) , H-index – 3;

- Begaliyeva Kalamkas Baltabekovna – PhD, S. Seifullin Kazakh Agrotechnical Research University, Senior Lecturer of the Department of Computer Science, H-index – 3  (Astana, Republic of Kazakhstan).

Temporary members of the Dissertation Committee:

- Sarsenbayev Nurlan Saduakasovich – candidate of technical sciences, NJSC “K.I. Satpayev Kazakh National Research Technical University”, Head of the Department of Automation and Control of the Institute of automation and information technologies, H-index – 4 (Almaty, Republic of Kazakhstan).

- Kylyshkanov Manarbek Kalymovich – doctor of physical and mathematical sciences, professor, Manager of the Department of Science, Rare Metals and Rare Earth Metals at JSC “NAC Kazatomprom”, H-index – 9 (Astana, Republic of Kazakhstan).

- Zimin Igor Viktorovich – candidate of technical sciences, professor, Vice-Rector for Science, Academy of Digital Innovations (Bishkek, Kyrgyz Republic).

Scientific advisors:

Orazbayev Batyrbai Bidaybekovich - Doctor of Technical Sciences, Professor of the Department of System Analysis and Control, L.N. Gumilyov Eurasian National University (Astana, Republic of Kazakhstan).

Markov Alexander Vladimirovich – candidate of technical sciences, Head of the Department of Control Systems, Belarusian State University of Informatics and Radioelectronics (Minsk, Republic of Belarus).

The defense will take place on June 17, 2026, at 04:00 PM in the Dissertation Council for the training direction «8D071 – Engineering and engineering trades» in the specialty «8D07102 – Automation and control» of L.N. Gumilyov Eurasian National University. The defense meeting is planned to be held online.

Link: https://teams.microsoft.com/meet/48209756303409?p=6sCPs0xt77sFTefsph 

Address: 11, Pushkin St., Astana, building, aud.222.

Abstract (English): ANNOTATION of the dissertation work of Kuzhukhanova Zhadra Asautayevna on the topic «Decision support system for managing primary oil refining process control», ubmitted for the degree of doctor of Philosophy (PhD) in the educational program «8D07102 – Automation and Control» Objective of the dissertation research. To develop a system of models and decision-making algorithms based on supplementary fuzzy information for the effective management of primary oil refining processes, and to apply them in the development of a decision support system for managing primary oil refining processes. Research objectives. Within the framework of this scientific research, a set of interrelated tasks has been formulated and systematically developed to ensure the achievement of the stated objective on a comprehensive and methodologically sound basis. - research, analysis, and description of decision-making approaches for modeling and effectively managing a processing plant and primary oil refining processes; - development of a suite of models for the atmospheric unit of a primary oil refining plant, enabling the determination of volumes and qualities of target petroleum products under conditions of scarce and uncertain input data. - development of hybrid models, including deterministic, statistical, fuzzy, and linguistic models of the main units of the atmospheric section where primary oil refining processes take place, as well as the development of a principle for integrating them into a single model complex; - formulate mathematical formulations of decision-making problems and propose effective heuristic algorithms for controlling the operating modes of the atmospheric unit under conditions of multi-criteria analysis and uncertainty in the initial data. - develop the architecture and define the main components of a decision support system for managing the primary oil refining processes occurring in the atmospheric unit of the plant. Research Methods. To develop a set of models for the main components of the AT block in the primary processing process, we employed a systems approach methodology, traditional methods for constructing statistical models, and the systems approach proposed in this dissertation. Based on the developed set of models, heuristic methods and well-known methods of multi-criteria conditional optimization, as well as analytical methods and methods of fuzzy set theory, are applied to solve decision-making problems regarding the effective management of primary processing operations under conditions of uncertainty. Key points to be defended: 1. A systematic approach to developing a suite of models for the atmospheric unit of a crude oil primary processing plant, enabling the determination of the volumes and qualities of target crude oil under conditions of data scarcity and uncertainty. 2. The principle of a hybrid model incorporating deterministic, statistical, fuzzy, and linguistic models of the main units of the atmospheric unit, where primary oil refining processes take place, as well as the development of a principle for integrating them into a single model complex. 3. Formulation of mathematical decision-making problems for the effective management of operating modes of the atmospheric tower (AT) unit in a primary oil refining plant under multi-criteria and uncertainty conditions; heuristic algorithms NK+IT and GP+OP for effective solution. 4. Architecture and main components of a decision support system for managing primary oil refining processes occurring in the atmospheric unit of the plant. Description of the main research findings. The study examined and resolved the key issues involved in developing a decision support system for managing crude oil primary processing operations in the AT unit of the ELST-AT plant. Theoretical results obtained during the research: a systematic approach to creating a set of models for complex technological systems; proposed effective heuristic decision-making algorithms under conditions of uncertainty, enabling the effective management of production facilities based on system modeling under conditions of fuzziness and a lack of initial information. The practical significance of the research lies in the development of decision-making systems for managing industrial facilities, such as integrated AT blocks, based on the results obtained. Decision support systems for managing such complex systems provide substantial assistance to the decision-maker—the process engineer—in effectively managing the operating modes of technological facilities in various industrial sectors under conditions of insufficient and fuzzy information. In this dissertation, the set of AT block models and the results of testing the decision support system for managing primary oil refining processes under industrial conditions—developed based on heuristic decision-making algorithms—demonstrated a high degree of consistency with actual production data, with deviations not exceeding 3.5%. In addition, the study yielded scientifically sound results in addressing key scientific challenges in the field of systematic modeling of oil refining processes, managerial decision-making under conditions of information scarcity and uncertainty, as well as the most pressing issues related to the practical and effective management of operating modes for oil refining plants. Justification of the novelty and significance of the results obtained The main scientific propositions and research findings obtained in the course of this dissertation possess scientific novelty and are as follows: - the novelty of the systematic approach to creating a complex of models for complex technological objects, demonstrated using the example of an atmospheric unit under conditions of scarcity and uncertainty of initial information, lies in the ability to construct an effective model for each unit of a poorly formalized technological object under conditions of uncertainty and to integrate the created models into a single complex. As a result, a model complex is formed that contains effective and adequate models of a complex technological object consisting of interconnected units, which, in the absence and ambiguity of initial information, allows its effective operating mode to be determined through system modeling. – the distinctive features and novelty of the hybrid model of the main units of the AT unit, where primary oil refining processes take place, lie in the synthesis of deterministic, statistical, fuzzy, and linguistic models based on diverse available information, followed by their integration into a single modeling framework. As a result of systematic modeling of the AT unit, it becomes possible to identify its “bottlenecks” that lead to reduced operational efficiency. Eliminating these problems contributes to improving the operational efficiency of the AT unit and increasing the yield of high-quality target products from primary oil refining. – mathematical formulations of decision-making problems for the effective control of operating modes in the atmospheric and vacuum distillation (AT) unit of a primary oil refinery under multi-criteria uncertainty, as well as innovations and features of the heuristic algorithms used to solve them, are presented below. Unlike known methods for solving decision-making problems, in the author’s proposed heuristic approach to managing primary oil refining processes under uncertainty—which is based on reducing fuzzy problems to a set of crisp problems—the fuzzy problem is solved in a fuzzy environment. This allows for the maximum utilization of available fuzzy information, which represents the experience, knowledge, and intuition of process operators and domain experts, thereby increasing the adequacy and effectiveness of the decisions made. This enables the formalization of available fuzzy information and its use for making well-founded and effective decisions under conditions of uncertainty. – the developed architecture and main subsystems of the decision support system for managing crude oil primary processing in the atmospheric unit. The proposed system offers advantages over known counterparts due to a set of synthesized models of the atmospheric unit’s main units based on various available information and the use of heuristic algorithms for effective decision-making regarding the control of the atmospheric unit’s operating modes. This set of models and heuristic algorithms provides significant support in making appropriate decisions under conditions of uncertainty while effectively managing primary oil refining processes based on fuzzy information, including the experience, knowledge, and intuition of the decision-maker, as well as experts, formalized in natural language. Thus, the set of models for the main units of the atmospheric unit of the decision support system, as well as the methods for solving decision-making problems and the heuristic algorithms that form its internal subsystems, are key elements in the intellectualization of the DSS under development. Alignment with scientific development priorities and government programs. This study is fully aligned with the strategic development priorities of the Republic of Kazakhstan. The research topic is consistent with the priorities outlined in the “Kazakhstan-2050” Strategy and the Strategic Development Plan of the Republic of Kazakhstan through 2025, including the digitalization of the economy, technological modernization of industry, and efficient use of resources. In addition, the work aligns with the objectives of developing the oil and gas sector and transforming the national economy, aimed at enhancing its competitiveness and technological level. Description of the candidate’s contribution to the preparation of each publication. All scientific publications on the topic of the dissertation research were prepared with the direct and decisive participation of the candidate and reflect the results of his independent scientific work in the field of developing a set of models and decision-making algorithms based on additional fuzzy information for the effective management of primary oil refining processes. The candidate independently formulated the scientific problem, scientifically justified and clearly defined the goal and objectives of the research, as well as the object and subject of the work. The publications presented at international scientific and practical conferences cover the stages of developing the concept of the scientific research and include works ranging from the study of the main AT unit of primary oil refining plants and its main components to the development of the architecture and key subsystems of a decision support system for managing primary oil refining processes in the AT unit. The following scientific findings were published in academic journals recommended by the Committee for Quality Assurance in Science and Higher Education of the Ministry of Science and Higher Education of the Republic of Kazakhstan: - the operating modes of the main columns K1 and K2 of the atmospheric unit of the primary oil refining plant were studied, and the data necessary for creating their models were collected and processed experimentally; - Based on the data and information obtained during the study, the structures and unknown parameters of the mathematical models for atmospheric units K1 and K2 were determined; - the main products of the atmospheric unit obtained as a result of simulation based on the developed models—the volumes of gasoline, kerosene, and fuel oil—were compared with their actual values using MATLAB, which confirmed the adequacy of the created models; In a scientific publication indexed in the international Scopus database, the author obtained the following scientific results: – mathematical formulations of decision-making problems for the effective control of operating modes in the atmospheric tower of a crude oil primary processing unit under multi-criteria and uncertainty conditions have been derived, and effective heuristic algorithms for solving these problems have been developed, based on modifications of various optimization principles; – the architecture and subsystems of a decision support system for managing primary oil refining processes in the atmospheric tower of the primary oil refining unit have been developed; – imulation interfaces and results based on the developed decision support system (DSS) models for managing crude oil primary processing operations occurring in the main units of the atmospheric tower section of the crude oil primary processing plant are presented, with the aim of making decisions regarding the management of these processes. In joint scientific publications, the candidate made a significant contribution to defining the research problem, developing the methodological framework, performing calculations, preparing illustrative material, and writing the main text of the articles. The published scientific works are logically interconnected, reflect the sequential development of the research idea, and are fully consistent with the topic of the dissertation. The integrated results presented in the publications confirm the independent nature of the research conducted, as well as the candidate’s significant personal contribution to the development of a set of models and decision-making algorithms based on additional fuzzy information for the effective management of primary oil refining processes and their application in the creation of a decision support system for managing primary oil refining processes

Dissertation

List of Scientific Works

Consultant's Review

Foreign Consultant's Review

Conclusion of the Research Ethics Committee