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A novel heuristic approach to detect induced forming defects using point cloud scans

Published online by Cambridge University Press:  16 May 2024

Muhammad Shahrukh Saeed*
Affiliation:
Swinburne University of Technology, Australia University of Stuttgart, Germany
Sheharyar Faisal
Affiliation:
National University of Science and Technology, Pakistan
Boris Eisenbart
Affiliation:
Swinburne University of Technology, Australia
Matthias Kreimeyer
Affiliation:
University of Stuttgart, Germany
Muhammad Hamas Khan
Affiliation:
Technical University of Munich, Germany
Muhammad Zeeshan Arshad
Affiliation:
Technical University of Munich, Germany
Racim Radjef
Affiliation:
Swinburne University of Technology, Australia
Markus Wagner
Affiliation:
University of Stuttgart, Germany
Eiman Nadeem
Affiliation:
National University of Science and Technology, Pakistan

Abstract

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The research paper delves into the importance of point cloud data obtained from 3D scanning technology ensuring quality control in industrial settings. It presents a new heuristic approach that utilizes the wavelet algorithm and other techniques to detect and characterize induced forming defects accurately. The proposed approach offers more flexibility, ease of use, and better results based on descriptive and prescriptive analyses from DRM. The results demonstrate that the wavelet algorithm was successful in identifying and characterizing forming defects in point cloud data.

Type
Design Methods and Tools
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2024.

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