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Please use this identifier to cite or link to this item: http://10.10.120.238:8080/xmlui/handle/123456789/192
Title: Geometrical Form Deviation and Defect Analysis of SLM Processed Slender Parts Using Computer Vision Methodology
Authors: Kaushik B.
Anand Kumar S.
Rajkumar V.
Keywords: Additive manufacturing
Deviation assessment
Grayscale pixel value
In situ monitoring
Quality assessment
Selective laser melting
Issue Date: 2023
Publisher: Springer Science and Business Media Deutschland GmbH
Abstract: The proposed work shows the application of a computer vision algorithm in the selective laser melting (SLM) process for in situ monitoring of additively manufactured products. This method provided real-time monitoring of each deposited layer. Real-time monitoring facilitates the decisions regarding the continuation or termination of the production process, resulting in waste management. The approach proposed is independent of layer number, which makes this assessment more robust. The monitoring is performed by capturing the layer image after completing the laser melting process. The captured image is analyzed with the help of computer vision algorithms. The proposed approach is demonstrated using a CAD model of T-joint. This CAD model is sliced into a total of 10 layers. These ten layers are simulated and analyzed considering all possible defects conditions. An additional approach is also showcased to help identify the deviation caused by any possible errors during the process. This deviation analysis can capture the deviation present in any location of the layer. This approach works on the sectional analysis of the layer. All the results show the potential of quality control for bulk manufacturing and industrial application. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
URI: https://dx.doi.org/10.1007/978-981-19-7612-4_13
http://localhost:8080/xmlui/handle/123456789/192
ISBN: 978-9811976117
ISSN: 2195-4356
Appears in Collections:Conference Paper

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