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Accuracy Evaluation of Dense Matching Techniques for Casting Part Dimensional Verification

Product optimization for casting and post-casting manufacturing processes is becoming compulsory to compete in the current global manufacturing scenario. Casting design, simulation and verification tools are becoming crucial for eliminating oversized dimensions without affecting the casting componen...

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Detalles Bibliográficos
Autores principales: Kortaberria, Gorka, Mutilba, Unai, Gomez-Acedo, Eneko, Tellaeche, Alberto, Minguez, Rikardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164126/
https://www.ncbi.nlm.nih.gov/pubmed/30217026
http://dx.doi.org/10.3390/s18093074
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author Kortaberria, Gorka
Mutilba, Unai
Gomez-Acedo, Eneko
Tellaeche, Alberto
Minguez, Rikardo
author_facet Kortaberria, Gorka
Mutilba, Unai
Gomez-Acedo, Eneko
Tellaeche, Alberto
Minguez, Rikardo
author_sort Kortaberria, Gorka
collection PubMed
description Product optimization for casting and post-casting manufacturing processes is becoming compulsory to compete in the current global manufacturing scenario. Casting design, simulation and verification tools are becoming crucial for eliminating oversized dimensions without affecting the casting component functionality. Thus, material and production costs decrease to maintain the foundry process profitable on the large-scale component supplier market. New measurement methods, such as dense matching techniques, rely on surface texture of casting parts to enable the 3D dense reconstruction of surface points without the need of an active light source as usually applied with 3D scanning optical sensors. This paper presents the accuracy evaluation of dense matching based approaches for casting part verification. It compares the accuracy obtained by dense matching technique with already certified and validated optical measuring methods. This uncertainty evaluation exercise considers both artificial targets and key natural points to quantify the possibilities and scope of each approximation. Obtained results, for both lab and workshop conditions, show that this image data processing procedure is fit for purpose to fulfill the required measurement tolerances for casting part manufacturing processes.
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spelling pubmed-61641262018-10-10 Accuracy Evaluation of Dense Matching Techniques for Casting Part Dimensional Verification Kortaberria, Gorka Mutilba, Unai Gomez-Acedo, Eneko Tellaeche, Alberto Minguez, Rikardo Sensors (Basel) Article Product optimization for casting and post-casting manufacturing processes is becoming compulsory to compete in the current global manufacturing scenario. Casting design, simulation and verification tools are becoming crucial for eliminating oversized dimensions without affecting the casting component functionality. Thus, material and production costs decrease to maintain the foundry process profitable on the large-scale component supplier market. New measurement methods, such as dense matching techniques, rely on surface texture of casting parts to enable the 3D dense reconstruction of surface points without the need of an active light source as usually applied with 3D scanning optical sensors. This paper presents the accuracy evaluation of dense matching based approaches for casting part verification. It compares the accuracy obtained by dense matching technique with already certified and validated optical measuring methods. This uncertainty evaluation exercise considers both artificial targets and key natural points to quantify the possibilities and scope of each approximation. Obtained results, for both lab and workshop conditions, show that this image data processing procedure is fit for purpose to fulfill the required measurement tolerances for casting part manufacturing processes. MDPI 2018-09-13 /pmc/articles/PMC6164126/ /pubmed/30217026 http://dx.doi.org/10.3390/s18093074 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kortaberria, Gorka
Mutilba, Unai
Gomez-Acedo, Eneko
Tellaeche, Alberto
Minguez, Rikardo
Accuracy Evaluation of Dense Matching Techniques for Casting Part Dimensional Verification
title Accuracy Evaluation of Dense Matching Techniques for Casting Part Dimensional Verification
title_full Accuracy Evaluation of Dense Matching Techniques for Casting Part Dimensional Verification
title_fullStr Accuracy Evaluation of Dense Matching Techniques for Casting Part Dimensional Verification
title_full_unstemmed Accuracy Evaluation of Dense Matching Techniques for Casting Part Dimensional Verification
title_short Accuracy Evaluation of Dense Matching Techniques for Casting Part Dimensional Verification
title_sort accuracy evaluation of dense matching techniques for casting part dimensional verification
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164126/
https://www.ncbi.nlm.nih.gov/pubmed/30217026
http://dx.doi.org/10.3390/s18093074
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