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of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

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Author: imír Stenchlák

  • INNOVATION POLICY AND INNOVATION MANAGEMENT

    Development of predictive maintenance based on artificial intelligence methods

    • Ivan Kuric
    • Daria Fedorová
    • imír Stenchlák
    • Martin Bohušík
    • Michal Bartoš
    • Milan Sága Jr.
    Innovations, Vol. 10 (2022), Issue 2, pg(s) 57-60
    • Abstract
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    •  Article PDF

    Artificial intelligence become more widespread in all manufacturing subjects. In manufacturing artificial intelligence deals with such tasks as quality control, robot navigation, computer vision, processes controlling, etc. The area of maintenance in machining is a great prospect for implementing artificial intelligence tools for analysis, prediction of monitored parameters, optimization, and improvement of the quality of the maintenance process. In particular, the article refers to predictive maintenance as a modern trend in mechanical engineering. In this article, a quick review of using methods of artificial intelligence and predictive analytics in maintenance and one p ractical implementation case of NAR network for time-series prediction was provided.

  • TECHNOLOGICAL BASIS OF “INDUSTRY 4.0”

    Trends and applications of artificial intelligence methods in industry

    • Ivan Kuric
    • Martin Bohušík
    • imír Stenchlák
    • Michal Bartoš
    • Daria Fedorová
    • Milan Sága Jr.
    Industry 4.0, Vol. 7 (2022), Issue 2, pg(s) 42-45
    • Abstract
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    •  Article PDF

    This article describes the actual trends and applications in industry where artificial intelligence models are deployed. This paper provides a more detailed description of the principles and methods of deploying models in the field of quality evaluation in industry and also in the areas of predictive maintenance and data analytics in the manufacturing process. Computer vision is increasingly coming to the fore due to its wide range of applications – object detection, categorisation of objects, reading QR codes and others. The area of predictive maintenance is important in terms of reducing downtime and saving costs for machine components. Models designed for data analytics, in turn, help to optimize the parameters of the production process so that the desired parameter is maximized or its optimal value is achieved.

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  • VII International Scientific Conference
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    07.-10.03.2022 - Borovets, Bulgaria
  • XV International Conference for Young Researchers
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  • XIX International Congress
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