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Visual Product Inspection Based on Deep Learning Methods

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Book cover Advanced Manufacturing Processes (InterPartner 2019)

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

Abstract

Nowadays, when high industrial productivity is connected with high quality and low product faults, it is common practice to use 100% product quality control. Since the quantities of products are high in mass production and inspection time must be as low as possible, the solution may be to use visual inspection of finished parts via camera systems and subsequent image processing using artificial intelligence. Recently, deep learning has shown itself to be the most appropriate and effective method for this purpose. The present article deals with the above-mentioned method of deep learning, and especially with its application when recognizing certain objects and elements during the visual product inspection.

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Acknowledgment

The research was supported by the Research Grant Agency under contract No. VEGA 1/0504/17 “Research and development of methods for multicriteria accuracy diagnostics of CNC machines”.

Author information

Authors and Affiliations

  1. University of Žilina, Univerzitná 1, Žilina, 010 26, Slovak Republic

    Ivan Kuric, Matej Kandera & Jaromír Klarák

  2. Sumy State University, 2 Rymskogo-Korsakova Street, Sumy, 40007, Ukraine

    Vitalii Ivanov

  3. University of Bielsko Biala, Willowa 2, 43-309, Bielsko-Biala, Poland

    Dariusz Więcek

Authors
  1. Ivan Kuric
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  2. Matej Kandera
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  3. Jaromír Klarák
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  4. Vitalii Ivanov
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  5. Dariusz Więcek
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Corresponding author

Correspondence to Ivan Kuric .

Editor information

Editors and Affiliations

  1. Odessa National Polytechnic University, Odessa, Ukraine

    Volodymyr Tonkonogyi

  2. Sumy State University, Sumy, Ukraine

    Vitalii Ivanov

  3. Poznan University of Technology, Poznan, Poland

    Justyna Trojanowska

  4. Odessa National Polytechnic University, Odessa, Ukraine

    Gennadii Oborskyi

  5. University of West Bohemia, Plzeň, Czech Republic

    Milan Edl

  6. University of Zilina, Zilina, Slovakia

    Ivan Kuric

  7. Sumy State University, Sumy, Ukraine

    Ivan Pavlenko

  8. High Technical Mechanical School of Professional Studies, Trstenik, Serbia

    Predrag Dasic

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Kuric, I., Kandera, M., Klarák, J., Ivanov, V., Więcek, D. (2020). Visual Product Inspection Based on Deep Learning Methods. In: Tonkonogyi, V., et al. Advanced Manufacturing Processes. InterPartner 2019. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-40724-7_15

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  • DOI: https://doi.org/10.1007/978-3-030-40724-7_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-40723-0

  • Online ISBN: 978-3-030-40724-7

  • eBook Packages: EngineeringEngineering (R0)

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