Layered image collection for real-time defective inspection in additive manufacturing

Jinwoo Song, Harika Bandaru, Xinyu He, Zhenyang Qiu, Young B. Moon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In Additive Manufacturing (AM), detecting cyber-attacks on infill structure is difficult because interior defects can occur without affecting the exterior. To detect the infill defectives quickly, layer-by-layer image inspection in real-time can be conducted. However, collecting the layered images from the top view in real-time is challenging because the 3D printer's extruder interferes with objects from being perfectly scanned. Using a dummy model to move the extruder out of the object's layer has been proposed. However, it is not practical because it creates printing delays and wasted printing materials. To enable infill layered image collection in real-time without delays and material waste, this research proposes a layered image collection method using an algorithm identifying a pseudo area in a layered image. The algorithm detects the pseudo area-the area covered by the extruder-using an image processing technique, such as an average pooling and max pooling. It accumulates the non-pseudo areas until a complete layered image is acquired. To validate and evaluate the proposed method, captured images were evaluated with various machine learning algorithms.

Original languageEnglish (US)
Title of host publicationAdvanced Manufacturing
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791884492
DOIs
StatePublished - 2020
EventASME 2020 International Mechanical Engineering Congress and Exposition, IMECE 2020 - Virtual, Online
Duration: Nov 16 2020Nov 19 2020

Publication series

NameASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
Volume2B-2020

Conference

ConferenceASME 2020 International Mechanical Engineering Congress and Exposition, IMECE 2020
CityVirtual, Online
Period11/16/2011/19/20

Keywords

  • 3D-printer
  • Additive manufacturing
  • Cyber-Attack
  • Cyber-physical attack
  • Cyber-physical system
  • Image processing
  • Infill
  • Layered image
  • Machine learning

ASJC Scopus subject areas

  • Mechanical Engineering

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