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Vision-based real-time monitoring of extrusion additive manufacturing processes for automatic manufacturing error detection

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Abstract

The scientific fields of additive manufacturing and especially the extrusion-based technologies have gained immense attention in numerous commercial and research areas in the past decades. However, monitoring the manufacturing procedure and detecting errors during the process remain a technological challenge in the field. Generally, defect detection and dimensional accuracy inspection of the produced component is applied after the manufacturing has been completed and is accomplished via on-site manual monitoring. Hereupon, these approaches could affect the manufacturing production cost via the increase of feedstock material, waste parts, manpower, and machine rates. To overcome these issues, the present paper introduces a vision-based method to scan, filter, segment, and correlate in real-time the physical printed part with the digital 3D model as well as to evaluate the performance of the additive manufacturing process. More specifically, high-resolution point cloud data of the printed part are automatically captured, filtered, segmented, reconstructed, and compared with the corresponding digital 3D model in various stages of the procedure. Finally, the effectiveness of the suggested automatic monitoring and error detection methodology is experimentally validated.

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Acknowledgements

This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: T1EDK- 04928).

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Authors and Affiliations

  1. Centre for Research and Technology Hellas– Information Technologies Institute (CERTH/ITI), Thessaloniki, Greece

    Paschalis Charalampous, Ioannis Kostavelis, Charalampos Kopsacheilis & Dimitrios Tzovaras

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  1. Paschalis Charalampous
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  2. Ioannis Kostavelis
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  3. Charalampos Kopsacheilis
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  4. Dimitrios Tzovaras
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Contributions

Paschalis Charalampous: Writing—original draft, writing—review and editing, investigation, methodology, experiments conduction

Ioannis Kostavelis: Writing—review and editing, project administration, methodology, visualization, validation of the software tools

Charalampos Kopsacheilis: Investigation, software development, visualization, data analysis, experiments conduction

Dimitrios Tzovaras: Project administration, supervision

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Correspondence to Paschalis Charalampous.

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Charalampous, P., Kostavelis, I., Kopsacheilis, C. et al. Vision-based real-time monitoring of extrusion additive manufacturing processes for automatic manufacturing error detection. Int J Adv Manuf Technol 115, 3859–3872 (2021). https://doi.org/10.1007/s00170-021-07419-2

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  • DOI: https://doi.org/10.1007/s00170-021-07419-2

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