Industrial Technology Commons^™

Structural Decomposition-Based Control Synthesis For Multivariable Systems Using Oblique Projection Operators, Abdukaxxarov Inomjon Ilxom Ugli Mr, Oripjon Olimovich Zaripov, Jasur Usmonovich Sevinov

Chemical Technology, Control and Management

This paper proposes a novel approach to control synthesis for multivariable systems with algebraic constraints using oblique projection operators and their structural decomposition. The method transforms a standard control law into a structured form by decomposing the control input into constraint-satisfying and null-space components. A generalized oblique projector is constructed using a dual matrix, ensuring flexibility in shaping system properties. Furthermore, a recursive decomposition algorithm is developed, allowing the global projector to be represented as a sum of local operators corresponding to subsystem structures. The proposed framework enables modular control design, decoupling of interactions, and efficient implementation for large-scale systems. …

Conceptual Model For Protecting Personal Data By Depersonalization In Information Systems: Principles, Components, And Life Cycle, Zarina Ildarovna Azizova

Chemical Technology, Control and Management

This article presents a systematic approach to personal data protection through depersonalization in the context of regulatory pressure and growing cyber threats. It proposes a comprehensive conceptual model that formalizes the de-identification process as a manageable sequence of steps, from attribute classification and method selection to mandatory verification of the result. The article also provides a comparative analysis of existing depersonalization methods in terms of their applicability within the proposed model. The model serves as a basis for the development of specific algorithms, as demonstrated by the example of a data shuffling approach.

Project Management Practices In Manufacturing: An Analytical Case Study, Margaret Randle, Robert Reynolds

Honors Capstones

Global industries are undergoing significant transitions in organizational models, technological innovation, and non-economic indicators of product quality, including sustainability and operational efficiency. The current workforce needs to not only develop competency of these technical skills, but also an adaptive, system-oriented approach to problem-solving as well. This case study, which highlights a manufacturing company’s project of increasing production efficiency, presents concepts learned through the textbook Project Management: Achieving Competitive Advantage by Jeffrey K. Pinto. The study thoroughly breaks down the full project lifecycle and the integration of systems of people, data, and initiatives in a framework that can be used to …

Dynamic Cushioning Performance And Sustainability Implications Of Recycled-Content Expanded Polyethylene Foams, Jay Singh, Pratish Patel, Emily Recinos, Paulina Goncharov

Industrial Technology and Packaging

The transition toward circular materials in protective packaging requires empirical evidence that recycled-content foams can satisfy stringent shock-attenuation requirements. This study evaluates the dynamic cushioning performance of expanded polyethylene (EPE) foams formulated with 0%, 30% and 40% recycled content under controlled impact conditions following ASTM D1596. A total of 1100 drop tests were conducted across combinations of density, thickness, static load and drop height representative of distribution hazards in parcel and freight supply chains. Peak transmitted acceleration (G) was measured as the primary performance response variable.

Across the configurations evaluated, recycled-content EPE foams exhibited cushioning performance comparable to virgin materials. …

Implementation Of The Fourth Industrial Revolution Technologies In Tanzania’S Downstream Oil And Gas Industries, Vitalis John Mwinyi

Tanzania Journal of Engineering and Technology (TJET)

The advent of the fourth industrial revolution (IR4.0) has resulted in the digital transformation of multiple sectors of the economy due to the disruptive nature of the technologies driving the revolution. The technologies have already found their way into the oil and gas industries across the globe, especially in upstream, midstream, and downstream operations. However, the degree of implementation is not the same for these operations, considering the complexities involved, integrated process, the associated risk and investment cost, among others. This study aimed to establish the implementation level of IR4.0 technologies in the downstream operations. A survey method was employed …

Analysis And Study Of Telemetry Systems For Directional And Horizontal Well Drilling, Jahongir Abdiganiyev Erkin Ugli, Sherali Halloqovich Umedov

Technical science and innovation

The article discusses the issues of reducing non-productive drilling time during the construction of directional and horizontal wells. The main focus is on the analysis of drilling conditions in complex geological and high-temperature environments. Particular attention is paid to drilling conditions in the territory of the Republic of Uzbekistan, with a specific study of data from the Boysun and Ustyurt regions. An analysis and study of the performance of telemetry systems available on the market, as well as their main technical characteristics, have been conducted. Key factors affecting the accuracy of wellbore trajectory measurements under various geological and technical conditions …

Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park

Annual Research Symposium

Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …

Algorithms Of Stable Adaptive Observation Of A Multidimensional Undefinite Object, Tursunova Sadoqat Abdusalom Qizi

Chemical Technology, Control and Management

This article presents an algorithm for simultaneously estimating the parameters and state coordinates of a multidimensional control object when some of its state variables are not directly measured. The inability to measure all state variables (coordinates) of an object is a well-known drawback of identification schemes. Such conditions require the construction of adaptive state observers. This work demonstrates that when identifying the parameters of a mathematical model for an uncertain multidimensional object, the asymptotic stability of the object and the convergence of its parameters to the model parameters are ensured, provided the input vector is sufficiently informative. The construction of …

Analysis Of The Carbonization Process Of Ammoniated Brine In Ammonia-Soda Production, Nadirbek Rustambekovich Yusupbekov, Djalolitdin Paxritdinovich Mukhitdinov, Fotima Faxritdinovna Iskhakova

Chemical Technology, Control and Management

The work provides an analytical review of the current state of modeling and controlling the carbonization process of ammoniated brine. It analyzes modern methods of mathematical, simulation, and intelligent modeling of heat and mass transfer, hydrodynamics, carbonation kinetics, and crystallization. The paper considers the potential of using digital twins, neural network models, fuzzy logic devices, and hybrid models to improve forecasting accuracy and the adaptability of process solutions. Modern carbonation process control strategies are also considered. A detailed analysis is provided of predictive control (MPC), neuro-fuzzy controllers, decentralized and multivariate control systems that ensure stable column operation under disturbances, optimize …

Inductive Transducers For Measuring Vibrations, S.F. Amirov, A.Kh. Sulliev, A.A. Shoimkulov

Chemical Technology, Control and Management

A new design of an induction transducer has been developed for measuring linear and torsional vibrations in different directions with high sensitivity by constructing an inertial element consisting of four mutually perpendicular sectors and making the masses of two adjacent sectors different from the masses of the other two adjacent sectors. By constructing an inertial element in the form of a sector with two mutually diametric magnetic cores and different masses, and placing it between the horizontal and vertical axes, a design of an induction transducer has been developed that highly sensitively measures linear and torsional vibrations in different directions, …

Research Of Logic Elements Based On Complementary Bipolar Transistors, Nodira Batirdjanovna Alimova, Nilufar Baxtiyorovna Gulyamova

Chemical Technology, Control and Management

Important parameters for any type of inverter – a NOT logic gate – are the power consumption during switching and the supply voltage. The proposed connection of complementary (two different types) bipolar transistors reduces the current consumption and supply voltage by simultaneously using the cutoff and saturation modes of the bipolar transistors. It has been theoretically and experimentally established that an inverter using complementary bipolar transistors operates at low supply voltages, approximately 0.7 V. Power consumption is virtually independent of the inverter's static state. A method for calculating the transfer characteristic of an inverter using complementary bipolar transistors is developed, …

The Main Errors Of The Ultrasonic Sensor In Measuring Water Flow In Open Channels, Anvar Urolovich Djalilov

Chemical Technology, Control and Management

This article analyzes the use of ultrasonic sensors in measuring water flow and the main errors that may occur in this process. In the conducted scientific research, a time-pulse ultrasonic sensor was tested. The absolute, relative and repeatability errors of the sensor during water flow measurement were studied. The absolute error represents the largest difference between the value recorded by the sensor and the real value, affecting the overall accuracy of the measurement system. This error can vary depending on environmental factors, the design and operating principles of the sensor. During the experiment, the performance of this sensor was …

Synthesis Of An Adaptive Synergistic Fuzzy Discrete Controller For Nonlinear Systems, Isamidin Xakimovich Sidikov, Gulruxsor Murot Qizi Nashvandova, Feruzakhon Botirxon Qizi Sodiqova

Chemical Technology, Control and Management

The paper considers the issues of synthesizing an adaptive fuzzy synergetic controller with discrete time for nonstationary nonlinear dynamic objects. The proposed approach is based on the integrated use of synergetic control principles and fuzzy logic methods, which ensure the formation of a control law for nonlinear dynamic objects that provides asymptotic stability of the control system. Such a hybrid combination makes it possible to guarantee the asymptotic stability of the closed-loop system and to shape the required dynamic behavior of the object over a wide range of operating modes. In addition, this approach provides the ability to adapt to …

Adaptive-Robust Control Of Dynamic Systems Using Generalized Predictive Methods, Shuxrat Tulyaganov

Chemical Technology, Control and Management

This paper considers an approach to adaptive-robust control of dynamic systems using generalized anticipation, where the object is described by a locally linearized model. Known self-tuning algorithms show insufficient stability to inaccurate selection of delay or model order. A generalized predictive control approach is suggested, with simulation outcomes showing superiority over traditional methods like generalized minimum variance control and pole assignment.This sliding horizon algorithm is based on predicting future system output signals several steps ahead, based on assumptions about subsequent control actions. One effective assumption is the presence of a “control horizon,” beyond which control signal increments are assumed to …

Review Of Modern Methods For Identification, Forecasting, And Intelligent Control Of Wastewater Biological Treatment Processes, Mirkhalil Agzamovich Ismailov, Boburbek Zokirjon O'G'Li Mannobjonov

Chemical Technology, Control and Management

This article presents a comprehensive review of contemporary approaches to the automation and intelligent control of wastewater biological treatment processes. Particular emphasis is placed on the digitalisation of wastewater treatment plants, ranging from the implementation of automated process control systems (APCS/SCADA-based solutions) to the application of predictive algorithms and the development of digital twins of bioreactors.

Special attention is devoted to mathematical models that underpin the control of bioprocesses. The evolution of the most widely used activated sludge models—ASM1, ASM2d, and ASM3—is examined, as these models describe key processes such as microbial community growth, nitrification, denitrification, and phosphorus removal. It …

A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines

Dissertations

Artificial Intelligence (AI) is transforming Supply Chain Management (SCM), yet many organizations struggle to assess their readiness for AI adoption and to understand how AI capabilities develop across maturity stages. This dissertation addresses this gap by developing a Capability Maturity Model (CMM) for AI integration in SCM, grounded in Organizational Information Processing Theory (OIPT), the Resource-Based View, and related capability frameworks. The model provides a structured approach for evaluating an organization's information-processing requirements, resource configurations, and alignment needed for effective AI-enabled supply chain operations.

Using a design science research approach, the AI-SCM CMM and its associated assessment instrument were derived …

Ai-Based Porosity Detection In Babbitt Bore Turning, Kaylee Leggett, Hannah Adams Gemmell, Kaisa Shingleton

Williams Honors College, Honors Research Projects

For this project, an external company reached out to the University of Akron requesting assistance with defect detection during their vertical turning operations. As babbitt is removed in a vertical turning process, it occasionally reveals defects, mainly porosity, which can lead to costly downstream failures of the part. Current inspection techniques involve use of dye penetrant, which is time consuming, labor intensive, unergonomic, and a source of human error. The goal of the project is to create an alternative inspection method using an AI-based machine-learning model. After the turning operation, a camera is deployed to perform an in-place inspection, taking …

Sme Ai Outreach In Finland—A Case Study, Kaj Mikael Björk, Anton Akusok, Amaury Lendasse, Leonardo Espinosa-Leal

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper presents a project (work in progress) where entrepreneurship and higher education in AI (from Master level to postdoc level) are integrated in order to produce a dual effect; helping SMEs to gain insight in how AI can aid in the corporate environment and to expose AI researchers to the real-life situations in the company world. If successful, the companies are made ready for the AI revolution and the researchers more equipped for corporate settings. The project is ongoing, so this paper addresses a work-in-progress project. The paper reflects on the project as well on some aspects that need …

Work-In-Progress: Evaluating Feasibility Of Band Matrix Solvers For Scaling Up Extreme Learning Machine Method, Anton Akusok, Kaj Mikael Björk, Amaury Lendasse, Leonardo Espinosa Leal

Engineering Management and Systems Engineering Faculty Research & Creative Works

This work presents the results of the potential of band linear system solvers for improving the scalability of the Extreme Learning Machine (ELM) method at large model sizes. The model is tested on the standard MNIST dataset with a range of solvers provided by the SciPy Python library. The results are analyzed taking into consideration the overall performance and the performance impact of band solvers across different matrix bandwidths, as well as the performance versus runtime analysis. The findings show potential in applying the proposed method to very large ELM models with narrow band matrices.

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 …

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 …

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 …

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 …

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, …