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    Wyświetlanie 1-2 z 2
    Tytuł:
    Solving the Spatial Relationships in Manufacturing Systems
    Autorzy:
    Daneshjo, Naqib
    Mareš, Albert
    Dudáš-Pajerká, Erika
    Powiązania:
    https://bibliotekanauki.pl/articles/102404.pdf
    Data publikacji:
    2020
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    manufacturing systems
    highly flexible
    NC machine
    industry
    systemy produkcyjne
    wysoka elastyczność
    maszyna NC
    przemysł
    Opis:
    Markets are already dynamic, and will continue to be so in the future. The pressure of customers / users for substantial product and service customization increases. Therefore, their demands must be met in a highly flexible, responsive and adaptable manner. The structural changes in company manufacturing systems need to be quickly adapted to the changing requirements and responded to in real-time. Production must not only be highly flexible with high-quality services, but it must be ready for work in integrated network structures. A logical response to these demands is the further development of industrial production ready for the changes presented in the forecasts of the fourth industrial revolution. In essence, it is a project of digitalization and sophistication of the industry. The new designs of highly integrated manufacturing systems and their clusters will ensure communication between the people and the means of production, as well as the production systems and other physical objects.
    Źródło:
    Advances in Science and Technology. Research Journal; 2020, 14, 2; 120-130
    2299-8624
    Pojawia się w:
    Advances in Science and Technology. Research Journal
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Intelligent Visual Quality Control System Based on Convolutional Neural Networks for Holonic Shop Floor Control of Industry 4.0 Manufacturing Systems
    Autorzy:
    Oborski, Przemysław
    Wysocki, Przemysław
    Powiązania:
    https://bibliotekanauki.pl/articles/2181746.pdf
    Data publikacji:
    2022
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    quality control
    manufacturing systems
    Industry 4.0
    artificial intelligence
    convolutional neural networks
    deep learning
    process monitoring
    holonic shop floor control
    integrated IT systems
    Opis:
    The article presents research on industrial quality control system based on AI deep learning method. They are a part of larger project focusing on development of Holonic Shop Floor Control System for integration of machines, machine operators and manufacturing process monitoring with information flow in whole production process according to Industry 4.0 requirements. A system connecting together machine operators, machine control, process and machine monitoring with companywide IT systems is developed. It is an answer on manufacture of airplane industry requirements. The main aim of the system is full automation of information flow between a management level and manufacturing process level. Intelligent, flexible quality control system allowing for active manufacturing optimization on the base of achieved results as well as a historical data collection for further Big Data analysis is the main aim of the current research. During research number of selected AI algorithms were tested for assessing their suitability for performing tasks identified in real manufacturing environment. As a result of the conducted analyzes, Convolutional Neural Networks were selected for further study. Number of built Convolutional Neural Networks algorithms were tested using sets of data and photos from the production line. A further step of research will be focused on testing a system in real manufacturing process for able possible construct a fully functional quality control system based on the use of Convolutional Neural Networks.
    Źródło:
    Advances in Science and Technology. Research Journal; 2022, 16, 2; 89--98
    2299-8624
    Pojawia się w:
    Advances in Science and Technology. Research Journal
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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