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Reduction of Human Effort in Technical Cleanliness Inspection Through Advanced Image Processing Approaches

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Advances in Manufacturing, Production Management and Process Control (AHFE 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 274))

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Abstract

The inspection of component surfaces for size, number and type of particulate contamination is carried out using the standard cleanliness analysis described in ISO 16232 and VDA 19.1. Currently, the detection, measurement, counting and classification of particles is performed by an analysis-system comprised of an incident light microscope and corresponding software evaluation followed by manual results review. We propose advanced image processing algorithms to enhance the particle recognition for the technical cleanliness inspection. This includes extended-depth-of-field (EDoF), shape-from-focus (SFF) and periodic noise removing. Furthermore, a robust image stitching algorithm is introduced. Combined, these algorithms enable a higher degree of automation and enhance the information received by the human examiner. This leads to a significant reduction of human interaction and intervention during the technical cleanliness inspection.

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Authors and Affiliations

  1. Institute of Production Systems, TU Dortmund University, Leonhard-Euler-Straße 5, 44227, Dortmund, Germany

    Thorben Panusch, Roman Möhle, Ronny Zwinkau & Jochen Deuse

  2. Centre for Advanced Manufacturing, University of Technology Sydney, Ultimo, Australia

    Jochen Deuse

Authors
  1. Thorben Panusch
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  2. Roman Möhle
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  3. Ronny Zwinkau
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  4. Jochen Deuse
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Corresponding author

Correspondence to Thorben Panusch .

Editor information

Editors and Affiliations

  1. Poznan University of Technology, Poznan, Poland

    Stefan Trzcielinski

  2. Faculty of Engineering Management, Poznan University, Poznan, Poland

    Beata Mrugalska

  3. University of Central Florida, Cocoa Beach, FL, USA

    Waldemar Karwowski

  4. Lincoln School of Design, University of Lincoln, LINCOLN, UK

    Emilio Rossi

  5. Department of Architecture, University of Chieti-Pescara, Pescara, Pescara, Italy

    Massimo Di Nicolantonio

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Panusch, T., Möhle, R., Zwinkau, R., Deuse, J. (2021). Reduction of Human Effort in Technical Cleanliness Inspection Through Advanced Image Processing Approaches. In: Trzcielinski, S., Mrugalska, B., Karwowski, W., Rossi, E., Di Nicolantonio, M. (eds) Advances in Manufacturing, Production Management and Process Control. AHFE 2021. Lecture Notes in Networks and Systems, vol 274. Springer, Cham. https://doi.org/10.1007/978-3-030-80462-6_14

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  • DOI: https://doi.org/10.1007/978-3-030-80462-6_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-80461-9

  • Online ISBN: 978-3-030-80462-6

  • eBook Packages: EngineeringEngineering (R0)

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