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of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

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Author: Jan Przepióra

  • TECHNOLOGICAL BASIS OF “INDUSTRY 4.0”

    Application of Neural Networks in Underwater Drone Control

    • Jan Przepióra
    • Krzysztof Mamcarz
    Industry 4.0, Vol. 9 (2024), Issue 2, pg(s) 52-55
    • Abstract
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    The integration of neural networks has revolutionised various technological domains, including the control mechanisms of underwater drones, especially in the context of Industry 4.0. This review explores the application of neural network architectures to improve the navigation, stability and overall performance of underwater drones. A systematic analysis of current methods is provided, focusing on their effectiveness in addressing challenges such as dynamic underwater environments, sensor noise, and real-time decision making. Key advances in neural network-based control strategies are discussed. Furthermore, the integration of these networks with traditional control systems to achieve robust and adaptive control frameworks is highlighted. Through the examination of case studies and experimental results, this review identifies potential areas for future research and development to further the advancement of autonomous underwater vehicles through intelligent control systems.

  • TECHNOLOGICAL BASIS OF “INDUSTRY 4.0”

    Industry 4.0 assembly line using mixed reality and data lake systems.

    • Michał Pietrzak
    • Jan Przepióra
    • Paweł Pasławski
    Industry 4.0, Vol. 8 (2023), Issue 4, pg(s) 113-115
    • Abstract
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    This article presents an Industry 4.0 assembly line that employs mixed reality (MR) and data lake systems to optimize the assembly process. MR devices such as HoloLens are used to provide operators with real-time assistance. The data generated by the MR devices is stored in a data lake system, which allows for real-time monitoring of the assembly process. This case study demonstrates the potential for MR and data lake systems to revolutionize traditional manufacturing processes and improve productivity and quality in Industry 4.0.

  • TRANSPORT TECHNICS. INVESTIGATION OF ELEMENTS. RELIABILITY

    Self-Excited Acoustic System: enhancing quality control

    • Jan Przepióra
    • Michał Pietrzak
    Trans Motauto World, Vol. 8 (2023), Issue 2, pg(s) 40-42
    • Abstract
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    This article discusses the use of self-excited acoustical systems (SAS) for the non-invasive and quick study of aluminium castings used in the automotive industry. The SAS system is incorporated into the industry 4.0 standard production line and provides valuable insights into the quality and reliability of the aluminium castings. This approach is innovative and aims to enhance the efficiency of the production process.

Congresses and conferences

  • International Scientific Conference
    "ARTIFICIAL INTELLIGENCE"
    07.03-10.10.2026 - Borovets, Bulgaria
  • IX International Scientific Conference
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    09.-12.03.2026 - Borovets, Bulgaria
  • XXIII International Congress
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    Winter session
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  • XI International Scientific Conference
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    Summer session
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  • XIV International Scientific Conference
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  • XXIII International Congress
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    Summer session
    02.-05.09.2026 - Varna, Bulgaria
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  • XIX International Conference for Young Researchers
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    11.-14.09.2026 - Varna, Bulgaria
  • XI International Scientific Conference
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    07.-10.12.2026 - Borovets, Bulgaria
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  • XI International Scientific Conference
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    Winter session
    09.-12.12.2026 - Borovets, Bulgaria
  • V International Scientific Conference
    "Mathematical Modeling"
    09.-12.12.2026 - Borovets, Bulgaria

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