Process Control and Systems Commons^™

Novel Methods For Environmental Fluoride Measurement, Cable Warren

Chemistry & Biochemistry Dissertations

Fluoride analysis has been an important focus of analytical analysis for many years and will continue to be so going forward. Today, fluorinated compounds, specifically per/polyfluoroalkyl substances (PFAS), better known as “forever chemicals” have captured the moment and are the subject of vast research and regulation. Under this context, I have researched new methods of fluoride separation and concentration in complex media as well as a novel method of PFAS destruction and total organic fluorine analysis for screening of PFAS in aqueous samples. Through research and work on micro-scale detection methods, an understanding of the state of the art and …

Plant-Wide Process Modeling, Techno-Economic Optimization, And Bayesian Uncertainty Quantification For Manufacturing Value-Added Products From Lignocellulosic Biomass, Poulomi Das

Graduate Theses, Dissertations, and Problem Reports (ETD)

For decades, many chemicals have been produced from fossil resources, contributing to resource depletion, pollution from extraction and refining, and hazardous byproducts. Growing environmental concerns and declining fossil reserves have intensified the search for sustainable sources of fuels, energy, and chemicals. Lignocellulosic biomass, the only abundant renewable carbon source, is therefore being explored as a feedstock for second-generation biofuels and high-value chemicals.

Currently, global wood-panel industry heavily depends on petroleum-derived commercial adhesives like phenol-formaldehyde, urea-formaldehyde, etc. These formaldehyde-based chemicals cause hazards to both human health and environment through emission of toxic volatile organic compounds. Typically, lignin is considered as one …

De Novo Protein Binding To Zinc Oxide Through Biomineralization Pathways, Jean-Mark A. Francis

Theses and Dissertations

De novo proteins are structurally distinct from proteins found in nature and thus capable of having their amino acid sequence modified to accomplish tasks such as increasing protein-nanoparticle binding without unfolding or decomposing. Zinc Oxide nanoparticles are functionally distinct from their bulk counterparts and are widely used as semiconductors in a variety of fields such as medicine and agriculture. With demand for these nanoparticles increasing, environmentally sustainable methods of Zinc Oxide nanoparticle synthesis are being investigated as an eco-friendly alternative to currently utilized but environmentally hazardous chemical and physical techniques. This research investigates the binding characteristics between Zinc Oxide nanoparticles …

Analog Systems Of Physical Quantities And Their Graph Models In Determining The Parameters Of Mechatronic Modules, Temurbek Omonboevich Rakhimov, Elmira Eshmurod Qizi Raxmanova, Guzal Khujaniyazova

Chemical Technology, Control and Management

This article is dedicated to the analogy systems of physical quantities and their graph models in determining the parameters of mechatronic modules. It presents the general sets and fundamental laws of analogy systems of physical quantities and their elements for determining the parameters of mechatronic modules. Based on the general sets and fundamental laws of analogy systems of physical quantities and their elements, principles have been developed for mechatronic modules with a heterogeneous structure consisting of electrical, magnetic, and mechanical parts. In these modules, the field as a form of matter exists, forming the basis for developing mathematical models to …

Investigation Of Nonlinear Magnetic Circuits Of Measuring Transducers With A Special Parameter Distribution Structure, Javhar Sulton O'G'Li Fayzullayev

Chemical Technology, Control and Management

The article proposes a new analytical method for investigating nonlinear magnetic circuits with a special structure of parameter distribution. The method is based on introducing into the system of nonlinear differential equations of such circuits the condition that the second derivative of the magnetic flux along the length of the circuit is equal to zero, as well as on the assumption that one of the geometric parameters of the studied magnetic circuit – the size of the air gap between the ferromagnetic rods, their thickness, width, or the linear value of the number of turns of the distributed excitation winding …

Expansion Of The Functionality Of Discrete Fiber-Optic Liquid Level Sensors, Azimjon Mamadaliyevich Khusanov, Yuriy Gennadyevich Shipulin

Chemical Technology, Control and Management

The article examines the problems and prospects of creating discrete fiber-optic liquid level gauges. Functional diagrams of single-channel and multi-channel discrete fiber-optic liquid level meters are presented. Examining the challenges of keeping this system running continuously reveals that sustaining its required reliability necessitates replacing malfunctioning measurement systems with operational ones. Investigations into differential equation models demonstrate that system recovery and failure events occur independently and follow a Poisson distribution pattern.

Improving Self-Diagnostic Methods Of Flow Measurement Systems Based On Artificial Intelligence, Elbek Ortikov

Chemical Technology, Control and Management

The article examines methods for improving self-diagnostics of consumption measurement systems based on artificial intelligence in the context of industry digitalization and the development of cyber-physical systems. It has been shown that traditional flow meters used to measure the flow rate of liquids and gases are subject to mechanical, hydraulic, electronic, and hidden failures, which reduce the accuracy and reliability of measurements. A justification for the need to transition from classical maintenance methods to intelligent self-control methods that ensure the detection of anomalies and hidden malfunctions in real time is presented. A multi-level architecture of intelligent self-diagnosis is proposed, including …

Improvement Of Technology And Control And Management Systems Of The Plant Oil Refination Process, Elyor Samadov

Chemical Technology, Control and Management

The article examines modern approaches to modernizing vegetable oil refining processes from the perspective of increasing energy efficiency, environmental friendliness, and final product quality. Traditional and innovative technologies are analyzed, with a focus on the implementation of membrane filtration, automated control systems, heat exchange complexes, and renewable energy sources. It has been shown that the use of intelligent control systems, high-precision membrane filters, and heat regeneration allows for a 25% reduction in energy consumption, a 20% reduction in greenhouse gas emissions, and a significant improvement in acidity, color, and impurity content in the product. The obtained results show the effectiveness …

Comprehensive Mechatronic Design Methodology For 6-Dof Stationary Lower Limb Rehabilitation Exoskeleton Robot With Safety-Integrated Control Architecture, Javlonbek Rakhmatillaev Mr., Nodirbek Kimsanboyev Mr., Umidjon Takabaev Mr., Zafar Juraev Dr.

Chemical Technology, Control and Management

This paper presents the mechatronic design of a proposed six-degree-of-freedom (6-DOF) stationary lower limb rehabilitation exoskeleton (SLLRE) robot, developed through a comprehensive mechatronic design methodology that includes mechanical design, actuator and sensor selection, and the development of a control structure based on a safety-oriented control approach. The proposed 6-DOF SLLRE mechanical design introduces a comprehensive mechanical structure comprising bilateral hip, knee, and ankle joints, degrees of freedom, joint ranges of motion, human parameters for rehabilitation training, as well as the frames and structural elements of the proposed system. Furthermore, the selection of appropriate sensors, actuators, and control architecture for the …

Empirical Analysis Of Machine Learning Models For Predicting Equipment Failures Using Iot Sensor Data, Yusuf Shodiyevich Avazov

Chemical Technology, Control and Management

This article examines the problem of detecting and predicting industrial equipment faults using IoT sensor data through machine learning techniques. Sensor readings such as temperature, vibration, pressure, voltage, and current, as well as FFT-based features, were statistically analyzed. Class imbalance and low signal informativeness were identified as key factors limiting model accuracy. Results obtained from Logistic Regression, Random Forest, and XGBoost models were comparatively evaluated, showing that when ROC-AUC values remain around 0.5, distinguishing fault and non-fault states becomes challenging. Correlation and feature-importance analyses confirmed the absence of strong dominant indicators. The findings highlight the need to improve sensor architecture …

Current Trends In Industrial Gas Furnace Control And Monitoring Systems, Utkir Uktam O'Gli Kholmanov

Chemical Technology, Control and Management

This paper presents a critical review of modern control methods applied to industrial gas-fired furnaces. Conventional PID controllers and their advanced modifications, including Advanced Process Control (APC) and cascade control schemes, are analyzed alongside Model Predictive Control (MPC) approaches. In addition, intelligent control algorithms—such as fuzzy logic and neuro-fuzzy systems (Fuzzy, ANFIS)—are examined. The study also considers advanced sensing technologies, including Tunable Diode Laser Absorption Spectroscopy (TDLAS), acoustic pyrometry, and infrared pyrometers, as well as digital twins and CFD-based modeling techniques. Particular attention is given to a comparative evaluation of control strategies based on key performance criteria, including energy efficiency, …

Skeleton-Based Human Action Recognition Using Spatio-Temporal Latent Features With A Gcn Model, Avazjon Marakhimov, Kabul Khudaybergenov, Mominov Zakhriddin

Chemical Technology, Control and Management

Owing to its resilience to visual noise and viewpoint variations, skeleton-based analysis has become a cornerstone of human action recognition research. Despite its practical significance, existing methodologies often suffer from a reliance on single-stream skeletal representations, which fail to encompass the full complexity of action features. This study introduces Latent Features for Human Action Recognition (LFHAR), a novel architecture designed to overcome these limitations by utilizing diverse spatio-temporal latent representations for improved feature extraction. The approach applies graph-based transformations to individual skeletal frames in temporal sequences, then arranges the derived graph features into spatio-temporal matrices. Evaluation of standard datasets demonstrates …

Models And Algorithms Of Control Mechanisms In Information Exchange Processes, Madina M. Fozilova, Dilshoda N. Uchqunova

Chemical Technology, Control and Management

In modern digital systems, efficient and reliable information exchange is essential for the stability of corporate systems. Traditional data management models struggle to detect and eliminate invalid, incomplete data at early stages, resulting in reduced accuracy and system inefficiency. This article proposes an advanced framework for controlling information exchange processes through the development of a Verification and Filtering algorithm. The algorithm operates within a multi-layered conceptual model that includes data input, control, validation, optimization, and decision layers. Acting as the core component, the Verification and Filtering algorithm distinguishes valid from invalid records in real time, ensuring data integrity before storage. …

Performance Assessment Of Operators Under Digital Simulator-Based Training In Automated Industrial Systems, Kamola Abdullaeva

Chemical Technology, Control and Management

This article proposes a comprehensive approach to training process operators, based on computer simulators integrated with digital twins, SCADA/DCS systems, real production data, and artificial intelligence algorithms. This approach is particularly relevant given the increased requirements for safety, productivity, and reliability of industrial facilities, as human factors are often the main cause of accidents (up to 60-80% of cases). The architecture of the simulator complex is designed to accurately emulate steady-state, transient, and pre-emergency operating modes of equipment, which are not achievable under actual production conditions. The experiment compared the training effectiveness of two groups of operators: one that used …

Predicting Simulation Times For Multiphase Thermal-Hydraulic Models, Andrew Yule, Andrew Taylor

SMU Data Science Review

Addressing the challenge of computationally intensive OLGA

simulations in the oil and gas industry, a machine learning framework is

developed for accurate runtime prediction. A specialized feature extraction

pipeline identifies key parameters—such as simulation time, time step,

number of branches, and section count—from OLGA input files that serve as

high-impact predictors. Multiple predictive models, including regression,

tree-based ensembles, and neural networks, are implemented to validate

accuracy and robustness. Results reveal that prioritizing simulations based on

predicted runtimes optimizes licensing resources and reduces operational

costs, making real-time scheduling more efficient. This research demonstrates

the effectiveness of data-driven runtime prediction in enhancing …

Modern Significance And Development Trends In The Production Of Vegetable Oils, Umidjon Ruziev, F.O. Qosimov, M.K. Shodiev

Chemical Technology, Control and Management

This article provides a comprehensive analytical review of the current state of the global vegetable oil production market. It describes the diversity of raw materials supplied, which includes both traditional and emerging fat sources. The paper also describes the technological stages of production, emphasizing modern innovations that contribute to more efficient, high-quality, and safe production. The article also covers global trends by comparing production dynamics between countries, highlighting regions with the highest rates of production growth and explaining the reasons for their competitive advantages. Particular attention is paid to environmental and socio-economic aspects, including sustainable land use, certification, carbon footprint, …

Possibilities Of Digitizing And Applying Artificial Intelligence To National Occupational Classification (Noc-2025) In Uzbekistan, Shohrux Nurali O‘G‘Li Narzullayev

Chemical Technology, Control and Management

This article examines the process of digitizing National Occupational Classification (NOC-2025) in Uzbekistan, developed on the basis of the International Standard Classification of Occupations (ISCO-08), and the possibilities of applying artificial intelligence technologies to it. Although this classification exists today in a national form, and its digitization and the introduction of artificial intelligence elements to it based on modern technologies remain a pressing issue. In order to digitize the classification, international systems such as the International Standard Classification of Occupations (ISCO-08, ILO), European Skills, Competences, Qualifications and Occupations (ESCO), Occupational Information Network (O*NET, USA) and National Occupational Classification (NOC, Canada) …

Physicochemical Analysis Of Carbon-Containing Materials Obtained From Vulcanized Rubber Waste And Their Application As Filler Pigments, N.S. Baxranova, Sh.T. Jurayev, D.R. Muminova, Jurayev Shohruh Tulqinovich

Chemical Technology, Control and Management

The article presents the results of chemical and scanning electron microscopic analyses of the solid fraction of carbon-containing materials obtained through thermo-oxidative pyrolysis of vulcanized rubber waste. Elemental analysis of the solid product formed during high-temperature pyrolysis of rubber-technical products at 650–700 °C is provided. In addition, the potential use of the carbonaceous material as a pigment is examined. Raman spectroscopic analysis of worn automobile tires showed that their composition consists of approximately 80 wt.% C, 7 wt.% H, 0.4 wt.% N, 1.5 wt.% S, 3 wt.% O, and 8 wt.% inorganic substances.

Intelligent Decision-Making Systems In Smart Greenhouses, Muso Berdiyor Ugli Allanov

Chemical Technology, Control and Management

Smart greenhouses offer a solution to sustainable food production under climate uncertainty, yet their management often depends on fixed rules or human intuition. This study proposes an intelligent decision-making framework that integrates optimization, simulation, and a neural set into a self-learning system. By generating “conditionally real data” through simulation and evolutionary algorithms, the system can predict microclimatic changes and optimize control of water, energy, and nutrients. Continuous digital feedback enables adaptive, data-efficient operation even with limited real data. Experimental results demonstrate reduced resource use and improved yield stability, advancing the development of autonomous and resilient greenhouse ecosystems.

Development Of Fire Prediction And Prevention Digital System Algorithms, Oybek Zokirovich Koraboshev

Chemical Technology, Control and Management

This research work is devoted to the development of algorithms for a digital system aimed at early detection, prediction and prevention of fire hazards. In the work, the process of fire hazard assessment is modeled on the basis of modern information technologies and artificial intelligence tools. The main focus is on collecting data in real time, analyzing it and creating algorithms that determine the level of danger. In the process of research, methods of data cleaning, normalization and determination of correlation between variables were used to process multidimensional data streams obtained from various sensors (temperature, smoke, gas concentration and humidity …