Additive manufacturing of self-sensing parts through material extrusion

Jan Sher Akmal*, Mika Salmi

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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The objective of this study is to develop and evaluate self-sensing capabilities in additively manufactured parts by embedding conductive elements that are copper and continuous carbon fiber. Two sets of test specimen were manufactured using a custom g-code on material extrusion-based Anisoprint A4 machine. Each set contained copper and continuous carbon fiber in an amorphous thermoplastic matrix. A tailor-made test setup was developed by improvising the American Society for Testing and Materials (ASTM D790) three-point loading system. Electrical resistance measurements were conducted under flexural loads to evaluate the self-sensing capability of each test specimen. The results confirmed that material extrusion technology can allow production of self-sensing parts. The electrical resistance increases linearly (Sensing tolerance <±2.6%, R^2>93.8% p-value < 0.005), establishing a strong correlation with applied force and strain. The work allows for creating smart parts that can facilitate big data collection, analysis, and evidence-based decision-making for condition monitoring and preventive maintenance needed for Industry 4.0.
Original languageEnglish
Article numbere2321200
Number of pages10
Issue number1
Publication statusPublished - 28 Feb 2024
MoE publication typeA1 Journal article-refereed


  • 3D modeling
  • 3d printing
  • Self-sensing materials
  • Sensor technology
  • additive manufacturing
  • condition monitoring
  • embedding
  • industry 4.0
  • preventive maintenance
  • prototyping
  • smart parts


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