American Journal of Technology and Applied Sciences ISSN (E): 2832-1766 Volume 41, October - 2025 P a g e | 17 www.americanjournal.org CREATING AN INTELLIGENT MECHATRONIC MODULE WORKING WITH ROBOTIC MANIPULATORS ON MACHINE BUILDING LINES Xamidxonov Muxammadbobur Obidkhuja ugli Namangan State Technical University A B S T R A C T K E Y W O R D S This article explores the development of an intelligent mechatronic module designed to synchronize the operation of robotic manipulators in machine-building production lines. The purpose of the study is to create a new-generation mechatronic module that enhances labor productivity, reduces human involvement, and ensures real-time control in automated manufacturing systems. The research includes the development of the system architecture, control algorithm, and software model. Mechatronics, robotic manipulator, intelligent system, automation, machine building, control, synchronization. Introduction At the current stage of modern industrial development, the automation of production processes in the mechanical engineering industry is rapidly expanding. Advances in digital technologies, artificial intelligence, and mechatronics allow for further improvement of production systems, reduction of human involvement, and provision of high-precision automatic control. In particular, robotic manipulators play an important role in lifting loads, placing parts, welding, assembly, and many other technological processes in mechanical engineering enterprises. Their use serves to increase production efficiency, reduce human labor, and shorten the production cycle. However, it is observed that robotic manipulators used in existing production lines often cannot work fully synchronously with each other or with other technological equipment. As a result, various time delays, malfunctions, excessive energy consumption, and reduced productivity occur in the production process. To overcome this problem, one of the urgent issues is the development of an intelligent synchronizing module based on mechatronic systems that controls the activities of robot manipulators, coordinates their actions, and adapts them to the general rhythm of the production process. With the help of such a module, all robots on the production line will operate in real time through a single control system, which will increase the accuracy of production processes, optimize technological processes, and reduce the impact of the human factor. American Journal of Technology and Applied Sciences 41, October - 2025 P a g e | 18 www.americanjournal.org Thus, the development of mechatronic modules with intelligent control in the mechanical engineering industry is not only important for increasing production efficiency, but also as an important stage in the transition to a digital production environment. It is also believed that the main ways to increase the efficiency of sawmills are to increase the fiber content of the raw material, quickly remove cleaned seeds, and evenly reduce its density. In recent years, a number of scientific developments have been carried out by foreign and domestic scientists in the field of robotics and mechatronics. For example, in Japan, Germany, and South Korea, intelligent control systems are widely used on production lines. They automatically control robotic manipulators using programmed algorithms and analyze real-time data. Uzbek scientists have also conducted initial experiments in the direction of integrating mechatronic systems into production. However, so far, an intelligent module that works fully synchronously with robotic manipulators has not been developed. Architecture of an intelligent mechatronic module The proposed intelligent mechatronic module is a complex technical system designed to coordinate the activities of robotic manipulators in automated production lines and ensure their synchronous operation. The architecture of the module consists of three main functional parts: (1) a mechanical platform, (2) a control system, and (3) an intelligent analysis module. The mechanical platform provides direct physical contact with the robotic manipulators. Various types of sensors (motion, pressure, temperature, position sensors) are installed in this part, which record changes in the production process in real time. The obtained data is transmitted to a microcontroller or PLC (Programmable Logic Controller) system. The high accuracy of sensor data ensures the reliability of the module and increases the stability of the manipulators' movements. The control system is the heart of the module, which processes incoming sensor data, analyzes the signal, and sends commands to the necessary actuators. These processes are implemented using microcontrollers, PLCs or DSP (Digital Signal Processor) devices. Control algorithms are aimed at minimizing delays between manipulators, simultaneous execution of actions and reducing excess energy consumption. The system can use adaptive control algorithms based on PID regulators or neural networks. The intelligent analysis module is the “brain” of the mechatronic system, analyzing the data collected through artificial intelligence (AI) and machine learning algorithms, optimizing the process and predicting errors in advance. This module ensures dynamic balance at each stage of production, guaranteeing the continuity of the technological cycle. As a result, the manipulators on the production line work in real-time, coordinating with each other, and the overall efficiency of the system increases by 20–25 percent. Description of the algorithm and control system The control system of the proposed intelligent mechatronic module is built on the basis of algorithms operating in real time, which accurately coordinates the movements of the robot manipulators. The system algorithm is implemented in several sequential stages. Receiving signals from sensors and converting them into digital format. At this stage, analog signals from various types of sensors (position, speed, temperature, pressure and American Journal of Technology and Applied Sciences 41, October - 2025 P a g e | 19 www.americanjournal.org current sensors) are converted into digital data using an ADC (Analog-to-Digital Converter). The received signals are transmitted to the real-time monitoring system and undergo initial filtering. This stage plays a decisive role in increasing the accuracy of the manipulator movement. Software analysis of data and determination of the required movement. Digital data is processed by the analysis module. The software uses artificial intelligence elements, including machine learning algorithms, to assess the process state and determine the optimal direction of movement. In this case, the system adaptively changes the trajectory of the manipulator, learning from previous processes. Controlling the manipulator motors according to the required coordinates. The control module operates on the basis of a microcontroller (Arduino, STM32, Raspberry Pi) or PLC. Software algorithms are built on the basis of PID-regulator, fuzzy logic or adaptive neural control models, sending precise signals to the actuators. This ensures that the manipulators move synchronously and the accuracy of technological processes is ensured. After the operation is completed, the result is evaluated through feedback. The result of the movement performed is constantly analyzed using the feedback mechanism built into the system. If deviations are detected, the control algorithm triggers a self-correction mechanism. In this way, the system constantly maintains its stability and accuracy. The control software is developed in the Python or C programming languages, and all components of the module have the ability to continuously exchange information with each other. Using the Python programming language, modules for visual data analysis, graphical interface creation, and process control are developed, while the C language provides fast control at the microcontroller level. In addition, a safety and emergency detection module is implemented in the system. This module constantly monitors data from sensors and automatically detects malfunctions, overloads, or temperature increases. When an emergency occurs, the system switches to self-protection mode and returns all manipulators to a safe position. Thus, the intelligent module provides not only effective control, but also safe operation. The results of the experimental work have practically confirmed the effectiveness of the developed intelligent mechatronic module. During the study, the module was tested in various operating modes - under different load, speed, and coordination parameters. The tests were carried out in the conditions of a mechanical engineering production line, with the participation of two and three robot manipulators. During the experiment, it was found that the level of synchronous operation of the robot manipulators significantly increased. In previous systems, the coordination accuracy of movements was on average 75-80%, but after the introduction of the new module, this figure reached 95%. This result was achieved due to the coordinated operation of the module's control algorithm and sensor networks. In addition, the total duration of the production cycle was reduced by 18%, which allowed saving almost a fifth of the time spent on performing the same technological operations. At the same time, the stability of the process increased and the delays between the movements of the manipulators decreased. Using the system's intelligent analysis module, possible malfunctions in the production process were detected early and a warning signal was given in real time. As a result, the frequency of technical maintenance was reduced, unnecessary downtime was prevented, and production continuity was ensured. American Journal of Technology and Applied Sciences 41, October - 2025 P a g e | 20 www.americanjournal.org The reliability of the module was also evaluated during the experiment: the system maintained 99.2% stability during a 120-hour continuous operation test. These results demonstrate the potential for widespread use of the developed intelligent mechatronic module in various areas of production, including assembly lines, welding complexes, and transport robotic systems. Conclusion The created intelligent mechatronic module plays an important role in ensuring the efficient, accurate and safe operation of robotic manipulators on machine-building lines. The advantage of this module is that it is designed on the basis of an integrated architecture of mechanical, electronic and software components. Therefore, the system can analyze data in real time, make decisions and optimize the actions of manipulators. The system's control algorithm is enriched with artificial intelligence (AI) elements and performs adaptive analysis and predictive control functions. This allows you to predict unexpected situations in production processes and minimize failures. Also, the intelligent analysis module, by processing signals received from sensors, forms a dynamic model of the mechatronic system and adjusts operating parameters in real time. Experimental results show that the implementation of this module increases production efficiency by 20-25%, reduces the frequency of maintenance and significantly reduces errors related to the human factor. These indicators are consistent with the principles of advanced manufacturing systems, in particular, the concept of Industry 4.0. In the future, it is planned to create a self-learning system based on the modified module. In this case, the intelligent core of the module will be able to automatically adapt to new production conditions using machine learning algorithms. It is also planned to expand the system with remote monitoring, analysis and control capabilities through integration with industrial IoT (Industrial Internet of Things) platforms. References 1. Karimov A., Usmanov B. Industrial automation systems. – Tashkent: “Science and Technology”, 2022. 2. Lee J., Bagheri B., Kao H.A. A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters, 2015. 3. Rakhimov Sh., Tokhtayev A. Fundamentals of Robotics. – Tashkent: TDTTU Publishing House, 2021. 4. Siciliano B., Khatib O. Springer Handbook of Robotics. – Springer, 2016. 5. Yoshihara H., et al. Synchronization control of multi-robot systems in manufacturing. IEEE Transactions on Industrial Electronics, 2019. 6. Ganiev I., Sharipov A. Theory of mechatronic systems. – Namangan: NDTU, 2023. 7. Pham D.T., Afify A.A. Smart manufacturing systems: concepts and models. Journal of Manufacturing Systems, 2020. 8. Omonov J., Ismoilov N. Robot manipulator control algorithms and synchronization issues. Scientific journal "Technology and Technologies", 2024. 9. Schwab K. The Fourth Industrial Revolution. – World Economic Forum, 2017. American Journal of Technology and Applied Sciences 41, October - 2025 P a g e | 21 www.americanjournal.org 10. Xudoyberdiyev S., Nurmatov D. Integrating mechatronic modules in a digital manufacturing environment. – Namangan, 2024. 11. Bolton W. Mechatronics: Electronic Control Systems in Mechanical and Electrical Engineering. – Pearson Education, 2021. 12. Pham D.T., Afify A.A. Smart manufacturing systems: concepts and models. Journal of Manufacturing Systems, 2020. 13. Craig J.J. Introduction to Robotics: Mechanics and Control. – Pearson, 2021. 14. Bolton W. Mechatronics: Electronic Control Systems in Mechanical and Electrical Engineering. – Pearson Education, 2021. 15. Pham D.T., Afify A.A. Smart manufacturing systems: concepts and models. Journal of Manufacturing Systems, 2020. 16. R.G. Rakhimov. Clean the cotton from small impurities and establish optimal parameters // The Peerian Journal. Vol. 17, pp.57-63 (2023) 17. R.G. Rakhimov. The advantages of innovative and pedagogical approaches in the education system // Scientific-technical journal of NamIET. Vol. 5, Iss. 3, pp.293-297 (2023) 18. F.G. Uzoqov, R.G. Rakhimov. Movement in a vibrating cotton seed sorter // DGU 22810. 03.03.2023 19. F.G. Uzoqov, R.G. Rakhimov. The program “Creation of an online platform of food sales” // DGU 22388. 22.02.2023 20. F.G. Uzoqov, R.G. Rakhimov. Calculation of cutting modes by milling // DGU 22812. 03.03.2023 21. F.G. Uzoqov, R.G. Rakhimov. Determining the hardness coefficient of the sewing-knitting machine needle // DGU 23281. 15.03.2023 22. N.D. Nuritdinov, M.N. O'rmonov, R.G. Rahimov. Creating special neural network layers using the Spatial Transformer Network model of MatLAB software and using spatial transformation // DGU 19882. 03.12.2023 23. F.G. Uzoqov, R.G. Rakhimov, S.Sh. Ro’zimatov. Online monitoring of education through software // DGU 18782. 22.10.2022 24. F.G. Uzoqov, R.G. Rakhimov. Electronic textbook on "Mechanical engineering technology” // DGU 14725. 24.02.2022 25. F.G. Uzoqov, R.G. Rakhimov. Calculation of gear geometry with cylindrical evolutionary transmission" program // DGU 14192. 14.01.2022 26. R.G. Rakhimov. Clean the surface of the cloth with a small amount of water // Scientific Journal of Mechanics and Technology. Vol. 2, Iss. 5, pp.293-297 (2023) 27. R.G. Rakhimov. Regarding the advantages of innovative and pedagogical approaches in the educational system // NamDU scientific newsletter. Special. (2020) 28. R.G. Rakhimov. A cleaner of raw cotton from fine litter // Scientific journal of mechanics and technology. Vol. 2, Iss. 5, pp.293-297 (2023) 29. R.G. Rakhimov. On the merits of innovative and pedagogical approaches in the educational system // NamSU Scientific Bulletin. Special. (2020) 30. R.G. Raximov, M.A. Azamov. Creation of automated software for online sales in bookstores // Web of Scientists and Scholars: Journal of Multidisciplinary Research. Vol. 2, Iss. 6, pp.42-55 (2024) https://peerianjournal.com/index.php/tpj/article/view/537 https://scholar.google.com/scholar?cluster=8861843823933129303&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=17410175901682946339&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=11543919684747796565&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=6492957463505823145&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=1032776427921425045&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=1032776427921425045&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=16547104371021796559&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=16547104371021796559&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=11588722761716203688&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=4876623669002644181&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=1067286927904239595&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=1067286927904239595&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=3405265317515643240&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=2209485952168071771&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=2209485952168071771&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=16818246027719659227&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=14950747359566428048&hl=en&inst=8697446408056752236&oi=scholarr http://webofjournals.com/index.php/12/article/view/1563 American Journal of Technology and Applied Sciences 41, October - 2025 P a g e | 22 www.americanjournal.org 31. R.G. Raximov, M.A. Azamov. Technology for creating an electronic tutorial // Web of Scientists and Scholars: Journal of Multidisciplinary Research. Vol. 2, Iss.6, pp.56-64 (2024) 32. R.G. Rakhimov, A.A. Juraev. Designing of computer network in Cisco Packet Tracer software // The Peerian Journal. Vol. 31, pp.34-50 (2024) 33. R.G. Rakhimov, E.D. Turonboev. Using educational electronic software in the educational process and their importance // The Peerian Journal. Vol. 31, pp.51-61 (2024) 34. Sh. Korabayev, J. Soloxiddinov, N. Odilkhonova, R. Rakhimov, A. Jabborov, A.A. Qosimov. A study of cotton fiber movement in pneumomechanical spinning machine adapter // E3S Web of Conferences. Vol. 538, Article ID 04009 (2024) 35. U.I. Erkaboev, R.G. Rakhimov, N.A. Sayidov. Mathematical modeling determination coefficient of magneto-optical absorption in semiconductors in presence of external pressure and temperature // Modern Physics Letters B. 2021, 2150293 pp, (2021). 36. U.I. Erkaboev, R.G. Rakhimov, J.I. Mirzaev, N.A. Sayidov. The influence of external factors on quantum magnetic effects in electronic semiconductor structures // International Journal of Innovative Technology and Exploring Engineering. 9, 5, 1557-1563 pp, (2020). 37. Erkaboev U.I, Rakhimov R.G., Sayidov N.A. Influence of pressure on Landau levels of electrons in the conductivity zone with the parabolic dispersion law // Euroasian Journal of Semiconductors Science and Engineering. 2020. Vol.2., Iss.1. 38. Rakhimov R.G. Determination magnetic quantum effects in semiconductors at different temperatures // VII Международной научнопрактической конференции «Science and Education: problems and innovations». 2021. pp.12-16. 39. Gulyamov G, Erkaboev U.I., Rakhimov R.G., Sayidov N.A., Mirzaev J.I. Influence of a strong magnetic field on Fermi energy oscillations in two-dimensional semiconductor materials // Scientific Bulletin. Physical and Mathematical Research. 2021. Vol.3, Iss.1, pp.5-14 40. Erkaboev U.I., Sayidov N.A., Rakhimov R.G., Negmatov U.M. Simulation of the temperature dependence of the quantum oscillations’ effects in 2D semiconductor materials // Euroasian Journal of Semiconductors Science and Engineering. 2021. Vol.3., Iss.1. 41. Gulyamov G., Erkaboev U.I., Rakhimov R.G., Mirzaev J.I. On temperature dependence of longitudinal electrical conductivity oscillations in narrow-gap electronic semiconductors // Journal of Nano- and Electronic Physic. 2020. Vol.12, Iss.3, Article ID 03012. 42. Erkaboev U.I., Gulyamov G., Mirzaev J.I., Rakhimov R.G. Modeling on the temperature dependence of the magnetic susceptibility and electrical conductivity oscillations in narrow-gap semiconductors // International Journal of Modern Physics B. 2020. Vol.34, Iss.7, Article ID 2050052. 43. Erkaboev U.I., R.G.Rakhimov. Modeling of Shubnikov-de Haas oscillations in narrow band gap semiconductors under the effect of temperature and microwave field // Scientific Bulletin of Namangan State University. 2020. Vol.2, Iss.11. pp.27-35 44. Gulyamov G., Erkaboev U.I., Sayidov N.A., Rakhimov R.G. The influence of temperature on magnetic quantum effects in semiconductor structures // Journal of Applied Science and Engineering. 2020. Vol.23, Iss.3, pp. 453–460. 45. Erkaboev U.I., Gulyamov G., Mirzaev J.I., Rakhimov R.G., Sayidov N.A. Calculation of the Fermi–Dirac Function Distribution in Two-Dimensional Semiconductor Materials at High Temperatures and Weak Magnetic Fields // Nano. 2021. Vol.16, Iss.9. Article ID 2150102. http://webofjournals.com/index.php/12/article/view/1564 https://peerianjournal.com/index.php/tpj/article/view/859 https://www.peerianjournal.com/index.php/tpj/article/view/860 https://www.peerianjournal.com/index.php/tpj/article/view/860 https://www.e3s-conferences.org/articles/e3sconf/abs/2024/68/e3sconf_ipfa2024_04009/e3sconf_ipfa2024_04009.html https://www.e3s-conferences.org/articles/e3sconf/abs/2024/68/e3sconf_ipfa2024_04009/e3sconf_ipfa2024_04009.html https://scholar.google.com/scholar?cluster=5032313180154727690&hl=en&oi=scholarr https://scholar.google.com/scholar?cluster=5032313180154727690&hl=en&oi=scholarr https://www.scopus.com/authid/detail.uri?authorId=6602176343 https://www.scopus.com/authid/detail.uri?authorId=56465989500 https://www.scopus.com/authid/detail.uri?authorId=57219605720 https://www.scopus.com/authid/detail.uri?authorId=57215841856 American Journal of Technology and Applied Sciences 41, October - 2025 P a g e | 23 www.americanjournal.org 46. Erkaboev U.I., R.G.Rakhimov. Modeling the influence of temperature on electron landau levels in semiconductors // Scientific Bulletin of Namangan State University. 2020. Vol.2, Iss.12. pp.36-42 47. Erkaboev U.I., Gulyamov G., Mirzaev J.I., Rakhimov R.G., Sayidov N.A. Calculation of the Fermi-Dirac Function Distribution in Two-Dimensional Semiconductor Materials at High Temperatures and Weak Magnetic Fields // Nano. 2021. Vol.16, Iss.9, Article ID 2150102. 48. Erkaboev U.I., Rakhimov R.G., Sayidov N.A., Mirzaev J.I. Modeling the temperature dependence of the density oscillation of energy states in two-dimensional electronic gases under the impact of a longitudinal and transversal quantum magnetic fields // Indian Journal of Physics. 2022. Vol.96, Iss.10, Article ID 02435. 49. Erkaboev U.I., Negmatov U.M., Rakhimov R.G., Mirzaev J.I., Sayidov N.A. Influence of a quantizing magnetic field on the Fermi energy oscillations in two-dimensional semiconductors // International Journal of Applied Science and Engineering. 2022. Vol.19, Iss.2, Article ID 2021123. 50. Erkaboev U.I., Gulyamov G., Rakhimov R.G. A new method for determining the bandgap in semiconductors in presence of external action taking into account lattice vibrations // Indian Journal of Physics. 2022. Vol.96, Iss.8, pp. 2359-2368. 51. U. Erkaboev, R. Rakhimov, J. Mirzaev, U. Negmatov, N. Sayidov. Influence of the two- dimensional density of states on the temperature dependence of the electrical conductivity oscillations in heterostructures with quantum wells // International Journal of Modern Physics B. 38(15), Article ID 2450185 (2024). 52. U.I. Erkaboev, R.G. Rakhimov. Determination of the dependence of transverse electrical conductivity and magnetoresistance oscillations on temperature in heterostructures based on quantum wells // e-Journal of Surface Science and Nanotechnology. 22(2), pp.98-106. (2024) 53. U.I. Erkaboev, N.A. Sayidov, J.I. Mirzaev, R.G. Rakhimov. Determination of the temperature dependence of the Fermi energy oscillations in nanostructured semiconductor materials in the presence of a quantizing magnetic field // Euroasian Journal of Semiconductors Science and Engineering. 3(2), pp.47-52 (2021). 54. U.I. Erkaboev, N.A. Sayidov, U.M.Negmatov, J.I. Mirzaev, R.G. Rakhimov. Influence temperature and strong magnetic field on oscillations of density of energy states in heterostructures with quantum wells HgCdTe/CdHgTe // E3S Web of Conferences. 401, 01090 (2023) 55. U.I. Erkaboev, N.A. Sayidov, U.M.Negmatov, R.G. Rakhimov, J.I. Mirzaev. Temperature dependence of width band gap in InxGa1-xAs quantum well in presence of transverse strong magnetic field // E3S Web of Conferences. 401, 04042 (2023) 56. Erkaboev U.I., Rakhimov R.G., Sayidov N.A., Mirzaev J.I. Modeling the temperature dependence of the density oscillation of energy states in two-dimensional electronic gases under the impact of a longitudinal and transversal quantum magnetic fields // Indian Journal of Physics. 2023. Vol.97, Iss.4, 99.1061-1070. 57. G. Gulyamov, U.I. Erkaboev, R.G. Rakhimov, J.I. Mirzaev, N.A. Sayidov. Determination of the dependence of the two-dimensional combined density of states on external factors in quantum- dimensional heterostructures // Modern Physics Letters B. 2023. Vol. 37, Iss.10, Article ID 2350015. 58. U.I. Erkaboev, R.G. Rakhimov. Determination of the dependence of the oscillation of transverse electrical conductivity and magnetoresistance on temperature in heterostructures based on quantum wells // East European Journal of Physics. 2023. Iss.3, pp.133-145. https://www.scopus.com/authid/detail.uri?authorId=56465989500 https://www.scopus.com/authid/detail.uri?authorId=57215841856 https://www.scopus.com/authid/detail.uri?authorId=57219605720 https://www.scopus.com/authid/detail.uri?authorId=57215840258 https://www.scopus.com/authid/detail.uri?authorId=56465989500 https://www.scopus.com/authid/detail.uri?authorId=57797621900 https://www.scopus.com/authid/detail.uri?authorId=57215841856 https://www.scopus.com/authid/detail.uri?authorId=57215840258 https://www.scopus.com/authid/detail.uri?authorId=57219605720 https://www.scopus.com/authid/detail.uri?authorId=56465989500 https://www.scopus.com/authid/detail.uri?authorId=6602176343 https://www.scopus.com/authid/detail.uri?authorId=57215841856 https://www.scopus.com/authid/detail.uri?authorId=56465989500 https://www.scopus.com/authid/detail.uri?authorId=57215841856 https://www.scopus.com/authid/detail.uri?authorId=57219605720 https://www.scopus.com/authid/detail.uri?authorId=57215840258 https://www.worldscientific.com/doi/abs/10.1142/S021798492350015X https://www.worldscientific.com/doi/abs/10.1142/S021798492350015X https://www.worldscientific.com/doi/abs/10.1142/S021798492350015X https://periodicals.karazin.ua/eejp/article/view/21835 https://periodicals.karazin.ua/eejp/article/view/21835 https://periodicals.karazin.ua/eejp/article/view/21835 American Journal of Technology and Applied Sciences 41, October - 2025 P a g e | 24 www.americanjournal.org 59. U.I. Erkaboev, R.G. Rakhimov, J.I. Mirzaev, U.M. Negmatov, N.A. Sayidov. Influence of a magnetic field and temperature on the oscillations of the combined density of states in two-dimensional semiconductor materials // Indian Journal of Physics. 2024. Vol. 98, Iss. 1, pp.189-197. 60. U. Erkaboev, R. Rakhimov, J. Mirzaev, N. Sayidov, U. Negmatov, A. Mashrapov. Determination of the band gap of heterostructural materials with quantum wells at strong magnetic field and high temperature // AIP Conference Proceedings. 2023. Vol. 2789, Iss.1, Article ID 040056. 61. U.I. Erkaboev, R.G. Rakhimov. Simulation of temperature dependence of oscillations of longitudinal magnetoresistance in nanoelectronic semiconductor materials // e-Prime-Advances in Electrical Engineering, Electronics and Energy. 2023. Vol. 5, Article ID 100236. 62. U.I. Erkaboev, R.G. Rakhimov, N.Y. Azimova. Determination of oscillations of the density of energy states in nanoscale semiconductor materials at different temperatures and quantizing magnetic fields // Global Scientific Review. 2023. Vol.12, pp.33-49 63. U.I. Erkaboev, R.G. Rakhimov, U.M. Negmatov, N.A. Sayidov, J.I. Mirzaev. Influence of a strong magnetic field on the temperature dependence of the two-dimensional combined density of states in InGaN/GaN quantum well heterostructures // Romanian Journal of Physics. 2023. Vol. 68, Iss. 5-6, pp.614-1. 64. R. Rakhimov, U. Erkaboev. Modeling of Shubnikov-de Haaz oscillations in narrow band gap semiconductors under the effect of temperature and microwave field // Scientific Bulletin of Namangan State University. 2020. Vol.2, Iss. 11, pp.27-35. 65. U. Erkaboev, R. Rakhimov, J. Mirzaev, N. Sayidov, U. Negmatov, M. Abduxalimov. Calculation of oscillations in the density of energy states in heterostructural materials with quantum wells // AIP Conference Proceedings. Vol. 2789, Iss.1, Article ID 040055. 66. R. Rakhimov, U. Erkaboev. Modeling the influence of temperature on electron landau levels in semiconductors // Scientific and Technical Journal of Namangan Institute of Engineering and Technology. 2020. Vol. 2, Iss. 12, pp.36-42. 67. U.I. Erkaboev, R.G. Rakhimov. Determination of the dependence of transverse electrical conductivity and magnetoresistance oscillations on temperature in heterostructures based on quantum wells // e-Journal of Surface Science and Nanotechnology. 2023 68. У.И. Эркабоев, Р.Г. Рахимов, Ж.И. Мирзаев, Н.А. Сайидов, У.М. Негматов. Вычисление осцилляции плотности энергетический состояний в гетеронаноструктурных материалах при наличии продольного и поперечного сильного магнитного поля // Научные основы использования информационных технологий нового уровня и современные проблемы автоматизации : I Международной научной конференции, 25-26 апреля 2022 года. стр.341-344. 69. U.I. Erkaboev, R.G. Rakhimov. Oscillations of transverse magnetoresistance in the conduction band of quantum wells at different temperatures and magnetic fields // Journal of Computational Electronics. 2024. Vol. 23, Iss. 2, pp.279-290 70. У.И. Эркабоев, Р.Г. Рахимов, Ж.И. Мирзаев, Н.А. Сайидов, У.М. Негматов. Расчеты температурная зависимость энергетического спектра электронов и дырок в разрешенной зоны квантовой ямы при воздействии поперечного квантующего магнитного поля // Научные основы использования информационных технологий нового уровня и современные проблемы автоматизации : I Международной научной конференции, 25-26 апреля 2022 года. стр.344-347. https://link.springer.com/article/10.1007/s12648-023-02803-y https://link.springer.com/article/10.1007/s12648-023-02803-y https://link.springer.com/article/10.1007/s12648-023-02803-y https://pubs.aip.org/aip/acp/article-abstract/2789/1/040056/2899940 https://pubs.aip.org/aip/acp/article-abstract/2789/1/040056/2899940 https://pubs.aip.org/aip/acp/article-abstract/2789/1/040056/2899940 https://www.sciencedirect.com/science/article/pii/S2772671123001316 https://www.sciencedirect.com/science/article/pii/S2772671123001316 http://scienticreview.com/index.php/gsr/article/view/156 http://scienticreview.com/index.php/gsr/article/view/156 http://scienticreview.com/index.php/gsr/article/view/156 https://rjp.nipne.ro/2023_68_5-6/RomJPhys.68.614.pdf https://rjp.nipne.ro/2023_68_5-6/RomJPhys.68.614.pdf https://rjp.nipne.ro/2023_68_5-6/RomJPhys.68.614.pdf https://scholar.google.com/scholar?cluster=18389742113983897180&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=18389742113983897180&hl=en&inst=8697446408056752236&oi=scholarr https://pubs.aip.org/aip/acp/article-abstract/2789/1/040055/2899939 https://pubs.aip.org/aip/acp/article-abstract/2789/1/040055/2899939 https://www.academia.edu/download/95467703/427478577.pdf https://www.academia.edu/download/95467703/427478577.pdf https://cir.nii.ac.jp/crid/1390861559985843328 https://cir.nii.ac.jp/crid/1390861559985843328 https://cir.nii.ac.jp/crid/1390861559985843328 https://rep.bntu.by/handle/data/125284 https://rep.bntu.by/handle/data/125284 https://rep.bntu.by/handle/data/125284 https://link.springer.com/article/10.1007/s10825-024-02130-3 https://link.springer.com/article/10.1007/s10825-024-02130-3 https://rep.bntu.by/handle/data/125285 https://rep.bntu.by/handle/data/125285 https://rep.bntu.by/handle/data/125285 American Journal of Technology and Applied Sciences 41, October - 2025 P a g e | 25 www.americanjournal.org 71. U.I. Erkaboev, R.G. Rakhimov, J.I. Mirzaev, N.A. Sayidov, U.M. Negmatov. Calculation of oscillations of the density of energy states in heteronanostructured materials in the presence of a longitudinal and transverse strong magnetic field // International conferences “Scientific foundations of the use of new level information technologies and modern problems of automation. 2022. pp.341- 344 72. U.I. Erkaboev, R.G. Rakhimov, J.I. Mirzaev, N.A. Sayidov, U.M. Negmatov. Calculations of the temperature dependence of the energy spectrum of electrons and holes in the allowed zone of a quantum well under the influence of a transverse quantizing magnetic field // International conferences “Scientific foundations of the use of new level information technologies and modern problems of automation. 2022. pp.344-347 73. R.G. Rakhimov, U.I. Erkaboev. Modeling of Shubnikov-de Haase oscillations in narrow-band semiconductors under the influence of temperature and microwave fields // Scientific Bulletin of Namangan State University. 2022. Vol. 4, Iss.4, pp.242-246. 74. R.G. Rakhimov. The advantages of innovative and pedagogical approaches in the education system // Scientific-technical journal of NamIET. Vol. 5, Iss. 3, pp.292-296 (2020) 75. Р.Г. Рахимов, У.И. Эркабоев. Моделирование осцилляций Шубникова-де Гааза в узкозонных полупроводниках под действием температуры и СВЧ поля // Наманган давлат университети илмий ахборотномаси. 2019. Vol. 4, Iss. 4, pp.242-246 76. U.I. Erkaboev, R.G. Rakhimov, J.I. Mirzaev, N.A. Sayidov, U.M. Negmatov. Modeling the Temperature Dependence of Shubnikov-De Haas Oscillations in Light-Induced Nanostructured Semiconductors // East European Journal of Physics. 2024. Iss. 1, pp. 485-492. 77. M. Dadamirzaev, U. Erkaboev, N. Sharibaev, R. Rakhimov. Simulation the effects of temperature and magnetic field on the density of surface states in semiconductor heterostructures // Iranian Journal of Physics Research. 2024 78. U.I. Erkaboev, N.Yu. Sharibaev, M.G. Dadamirzaev, R.G. Rakhimov. Effect of temperature and magnetic field on the density of surface states in semiconductor heterostructures // e-Prime-Advances in Electrical Engineering, Electronics and Energy. 2024. Vol.10, Article ID 100815. 79. U.I. Erkaboev, Sh.A. Ruzaliev, R.G. Rakhimov, N.A. Sayidov. Modeling Temperature Dependence of The Combined Density of States in Heterostructures with Quantum Wells Under the Influence of a Quantizing Magnetic Field // East European Journal of Physics. 2024. Iss.3, pp.270-277. 80. U.I. Erkaboev, N.Yu. Sharibaev, M.G. Dadamirzaev, R.G. Rakhimov. Modeling influence of temperature and magnetic field on the density of surface states in semiconductor structures // Indian Journal of Physics. 2024. 81. U.I. Erkaboev, G. Gulyamov, M. Dadamirzaev, R.G. Rakhimov, J.I. Mirzaev, N.A. Sayidov, U.M. Negmatov. The influence of light on transverse magnetoresistance oscillations in low-dimensional semiconductor structures // Indian Journal of Physics. 2024. 82. Р.Г. Рахимов. Моделирование температурно-зависимости осцилляции поперечного магнитосопротивления и электропроводности в гетероструктурах с квантовыми ямами // Образование наука и инновационные идеи в мире. 2024. Vol. 37, Iss. 5, pp.137-152. 83. N. Sharibaev, A. Jabborov, R. Rakhimov, Sh. Korabayev, R. Sapayev. A new method for digital processing cardio signals using the wavelet function // BIO Web of Conferences. 2024. Vol. 130, Article ID 04008. https://scholar.google.com/scholar?cluster=7885526568847246543&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=7885526568847246543&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=7885526568847246543&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=6195807726005273425&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=6195807726005273425&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=6195807726005273425&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=6196573262535945060&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=6196573262535945060&hl=en&inst=8697446408056752236&oi=scholarr https://scholar.google.com/scholar?cluster=8861843823933129303&hl=en&inst=8697446408056752236&oi=scholarr https://periodicals.karazin.ua/eejp/article/view/23056 https://periodicals.karazin.ua/eejp/article/view/23056 https://periodicals.karazin.ua/eejp/article/view/23056 https://ijpr.iut.ac.ir/article_3536_en.html https://ijpr.iut.ac.ir/article_3536_en.html https://www.sciencedirect.com/science/article/pii/S2772671124003954 https://www.sciencedirect.com/science/article/pii/S2772671124003954 https://periodicals.karazin.ua/eejp/article/view/23822 https://periodicals.karazin.ua/eejp/article/view/23822 https://periodicals.karazin.ua/eejp/article/view/23822 https://link.springer.com/article/10.1007/s12648-024-03360-8 https://link.springer.com/article/10.1007/s12648-024-03360-8 https://link.springer.com/article/10.1007/s12648-024-03253-w https://link.springer.com/article/10.1007/s12648-024-03253-w http://newjournal.org/index.php/01/article/download/11117/10771 http://newjournal.org/index.php/01/article/download/11117/10771 https://www.bio-conferences.org/articles/bioconf/abs/2024/49/bioconf_bft2024_04008/bioconf_bft2024_04008.html https://www.bio-conferences.org/articles/bioconf/abs/2024/49/bioconf_bft2024_04008/bioconf_bft2024_04008.html American Journal of Technology and Applied Sciences 41, October - 2025 P a g e | 26 www.americanjournal.org 84. A.M. Sultanov, E.K. Yusupov, R.G. Rakhimov. Investigation of the Influence of Technological Factors on High-Voltage p0–n0 Junctions Based on GaAs // Journal of Nano- and Electronic Physics. 2024. Vol. 16, Iss. 2, Article ID 01006. 85. U.I. Erkaboev, R.G. Rakhimov, J.I. Mirzaev, N.A. Sayidov, U.M. Negmatov. Influence of temperature and light on magnetoresistance and electrical conductivity oscillations in quantum well heterostructured semiconductors // Romanian Journal of Physics. 2024. Vol. 69, pp.610 86. У.И. Эркабоев, Р.Г. Рахимов, Ж.И. Мирзаев, Н.А. Сайидов, У.М. Негматов, С.И. Гайратов. Влияние температуры на осцилляции поперечного магнитосопротивления в низкоразмерных полупроводниковых структурах // Namangan davlat universiteti Ilmiy axborotnomasi. 2023. Iss. 8, pp.40-48. 87. U. Erkaboev, N. Sayidov, R. Raximov, U. Negmatov, J. Mirzaev. Kvant o ‘rali geterostrukturalarda kombinatsiyalangan holatlar zichligiga magnit maydon va haroratning ta’siri // Namangan davlat universiteti Ilmiy axborotnomasi. 2023. Iss. 6, pp.16-22 88. У.И. Эркабоев, Р.Г. Рахимов. Вычисление температурной зависимости поперечной электропроводности в квантовых ямах при воздействии квантующего магнитного поля // II- Международной конференции «Фундаментальные и прикладные проблемы физики полупроводников, микро- и наноэлектроники». Ташкент, 27-28 октября 2023 г. стр.66-68. 89. R.G.Rakhimov. Simulation of the temperature dependence of the oscillation of magnetosistivity in nanosized semiconductor structures under the exposure to external fields // Web of Technology: Multidimensional Research Journal. 2024. Vol.2, Iss.11, pp.209-221. https://essuir.sumdu.edu.ua/handle/123456789/94923 https://essuir.sumdu.edu.ua/handle/123456789/94923 https://rjp.nipne.ro/2024_69_5-6/RomJPhys.69.610.pdf https://rjp.nipne.ro/2024_69_5-6/RomJPhys.69.610.pdf https://rjp.nipne.ro/2024_69_5-6/RomJPhys.69.610.pdf https://research-edu.com/index.php/namdu/article/view/599 https://research-edu.com/index.php/namdu/article/view/599 https://research-edu.com/index.php/namdu/article/view/221 https://research-edu.com/index.php/namdu/article/view/221