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  • Skoda utilises AI to identify maintenance needs at its Mlada Boleslav plant

    23 Feb 2023

    |

    1,605 views

    The AI-based image recognition system to continuously monitor assembly line equipment and flag worn components up for maintenance work.

    Skoda Auto is now using Artificial Intelligence-based image recognition to ensure timely identification of maintenance needs on the assembly line.

    The new technology is being put to work at the firm's main plant in Mlada Boleslav. It utilises cameras to continuously monitor assembly line equipment subject to wear, such as girders, bolts, or cabling.

    The system compares its high-precision photographs against thousands of stored images, allowing it to detect departures from optimal baseline conditions and identify sources of error. This is done via the use of blue light, which allows the system to reliably differentiates between cracks and scratches and to make the correct diagnosis. Detected irregularities in the processes can then be quickly identified and flagged for required maintenance work.

    The system will also gradually expand its knowledge base. If it finds a worn bolt, for example, it marks the spot as error-free as soon as the part has been replaced and checked again, while it can also use information on irregularities it has identified in the past to evaluate new, detected deviations.
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    Skoda utilises AI to identify maintenance needs at its Mlada Boleslav plant

    23 Feb 2023

    |

    1,605 views

    The AI-based image recognition system to continuously monitor assembly line equipment and flag worn components up for maintenance work.

    Skoda Auto is now using Artificial Intelligence-based image recognition to ensure timely identification of maintenance needs on the assembly line.

    The new technology is being put to work at the firm's main plant in Mlada Boleslav. It utilises cameras to continuously monitor assembly line equipment subject to wear, such as girders, bolts, or cabling.

    The system compares its high-precision photographs against thousands of stored images, allowing it to detect departures from optimal baseline conditions and identify sources of error. This is done via the use of blue light, which allows the system to reliably differentiates between cracks and scratches and to make the correct diagnosis. Detected irregularities in the processes can then be quickly identified and flagged for required maintenance work.

    The system will also gradually expand its knowledge base. If it finds a worn bolt, for example, it marks the spot as error-free as soon as the part has been replaced and checked again, while it can also use information on irregularities it has identified in the past to evaluate new, detected deviations.
    24.4k

    Tags

    skoda mlada boleslav ai artificial intelligence maintainence

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