How to ensure bad quality in metal additive manufacturing: In-situ infrared thermography from the security perspective

Andrew Slaughter, Mark Yampolskiy, Manyalibo Matthews, Wayne E. King, Gabe Guss, Yuval Elovici

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Additive Manufacturing, a.k.a. 3D Printing, is increasingly used to manufacture functional parts, including components of safety critical systems. therefore, assuring part quality has become of paramount importance. In-situ infrared (IR) imaging systems are a promising solution to increase final build quality and minimize time-consuming and costly post processing and characterization. However, it also raises novel security concerns. We argue that, if compromised, the same in-situ quality control can be abused to sabotage manufactured parts. As a basis for our discussion, we first detail how IR thermography is used in open-loop and, experimentally, in closed-loop quality control for powder bed fusion (PBF) systems. We then identify malicious manipulations that an adversary can perform. We discuss the consequences of the manipulations on the manufactured part's quality. For selected attacks, we also provide experimental proof of the identified manipulations and their consequences.

Original languageAmerican English
Title of host publicationARES 2017 - Proceedings of the 12th International Conference on Availability, Reliability and Security
ISBN (Electronic)9781450352574
DOIs
StatePublished - 29 Aug 2017
Event12th International Conference on Availability, Reliability and Security, ARES 2017 - Reggio Calabria, Italy
Duration: 29 Aug 20171 Sep 2017

Publication series

NameACM International Conference Proceeding Series
VolumePart F130521

Conference

Conference12th International Conference on Availability, Reliability and Security, ARES 2017
Country/TerritoryItaly
CityReggio Calabria
Period29/08/171/09/17

Keywords

  • Additive manufacturing
  • Infrared thermography
  • Powder bed fusion
  • Sabotage
  • Safety
  • Security
  • Tampering

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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