In-Process Machining Distortion Prediction Method Based on Bulk Residual Stresses Estimation from Reduced Layer Removal

Manufacturing structural monolithic components for the aerospace market often involves machining distortion, which entails high costs and material and energy waste in industry. Despite the development of distortion calculation and avoidance tools, this issue remains unsolved due to the difficulties...

Descripción completa

Detalles Bibliográficos
Autores: Aurrekoetxea Totorikaguena, María, López de Lacalle Marcaide, Luis Norberto, Zelaieta, Oier, Llanos González de Durana, Iñigo
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Universidad del País Vasco
Repositorio:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/66576
Acceso en línea:http://hdl.handle.net/10810/66576
Access Level:acceso abierto
Palabra clave:machining distortion
airframe
residual stress
aluminium
id ES_0e7d2eb40be8e0d852c0e8fa8ec97d8c
oai_identifier_str oai:addi.ehu.eus:10810/66576
network_acronym_str ES
network_name_str España
repository_id_str
spelling In-Process Machining Distortion Prediction Method Based on Bulk Residual Stresses Estimation from Reduced Layer RemovalAurrekoetxea Totorikaguena, MaríaLópez de Lacalle Marcaide, Luis NorbertoZelaieta, OierLlanos González de Durana, Iñigomachining distortionairframeresidual stressaluminiumManufacturing structural monolithic components for the aerospace market often involves machining distortion, which entails high costs and material and energy waste in industry. Despite the development of distortion calculation and avoidance tools, this issue remains unsolved due to the difficulties in accurately and economically measuring the residual stresses of the machining blanks. In the last years, the on-machine layer removal method has shown its potential for industrial implementation, offering the possibility to obtain final components from blanks with measured residual stresses. However, this measuring method requires too long an implementation time to be used in-process as part of the manufacturing chains. In this sense, the objective of this paper is to provide a machining distortion prediction method based on bulk residual stress estimation and hybrid modelling. The bulk residual stresses estimation is performed using reduced layer removal measurements. Considering bulk residual stress data and machining-induced residual stress data, as well as geometry and material data, real-part distortion calculations can be performed. For this, a hybrid model based on the combination of an analytical formulation and finite element modelling is employed, which enables us to perform fast and accurate calculations. With the developments here presented, the machining distortion can be predicted, and its uncertainty range can be calculated, in a simple and fast way. The accuracy and practicality of these developments are evaluated by comparison with the experimental results, showing the capability of the proposed solution in providing distortion predictions with errors lower than 10% in comparison with the experimental results.This work was supported by the Centro para el Desarrollo Tecnológico Industrial (CDTI)—Acreditación y concesión de ayudas destinadas a centros tecnológicos de excelencia “CERVERA” under the framework of the project: “MIRAGED: Posicionamiento estratégico en modelos virtuales y gemelos digitales para una industria 4.0 [grant number CER-20191001].MDPI2024202420242024info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/66576reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoIngléshttps://www.mdpi.com/2504-4494/8/1/9info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/es/© 2024 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 (https://creativecommons.org/licenses/by/ 4.0/).oai:addi.ehu.eus:10810/665762026-06-18T09:23:17Z
dc.title.none.fl_str_mv In-Process Machining Distortion Prediction Method Based on Bulk Residual Stresses Estimation from Reduced Layer Removal
title In-Process Machining Distortion Prediction Method Based on Bulk Residual Stresses Estimation from Reduced Layer Removal
spellingShingle In-Process Machining Distortion Prediction Method Based on Bulk Residual Stresses Estimation from Reduced Layer Removal
Aurrekoetxea Totorikaguena, María
machining distortion
airframe
residual stress
aluminium
title_short In-Process Machining Distortion Prediction Method Based on Bulk Residual Stresses Estimation from Reduced Layer Removal
title_full In-Process Machining Distortion Prediction Method Based on Bulk Residual Stresses Estimation from Reduced Layer Removal
title_fullStr In-Process Machining Distortion Prediction Method Based on Bulk Residual Stresses Estimation from Reduced Layer Removal
title_full_unstemmed In-Process Machining Distortion Prediction Method Based on Bulk Residual Stresses Estimation from Reduced Layer Removal
title_sort In-Process Machining Distortion Prediction Method Based on Bulk Residual Stresses Estimation from Reduced Layer Removal
dc.creator.none.fl_str_mv Aurrekoetxea Totorikaguena, María
López de Lacalle Marcaide, Luis Norberto
Zelaieta, Oier
Llanos González de Durana, Iñigo
author Aurrekoetxea Totorikaguena, María
author_facet Aurrekoetxea Totorikaguena, María
López de Lacalle Marcaide, Luis Norberto
Zelaieta, Oier
Llanos González de Durana, Iñigo
author_role author
author2 López de Lacalle Marcaide, Luis Norberto
Zelaieta, Oier
Llanos González de Durana, Iñigo
author2_role author
author
author
dc.subject.none.fl_str_mv machining distortion
airframe
residual stress
aluminium
topic machining distortion
airframe
residual stress
aluminium
description Manufacturing structural monolithic components for the aerospace market often involves machining distortion, which entails high costs and material and energy waste in industry. Despite the development of distortion calculation and avoidance tools, this issue remains unsolved due to the difficulties in accurately and economically measuring the residual stresses of the machining blanks. In the last years, the on-machine layer removal method has shown its potential for industrial implementation, offering the possibility to obtain final components from blanks with measured residual stresses. However, this measuring method requires too long an implementation time to be used in-process as part of the manufacturing chains. In this sense, the objective of this paper is to provide a machining distortion prediction method based on bulk residual stress estimation and hybrid modelling. The bulk residual stresses estimation is performed using reduced layer removal measurements. Considering bulk residual stress data and machining-induced residual stress data, as well as geometry and material data, real-part distortion calculations can be performed. For this, a hybrid model based on the combination of an analytical formulation and finite element modelling is employed, which enables us to perform fast and accurate calculations. With the developments here presented, the machining distortion can be predicted, and its uncertainty range can be calculated, in a simple and fast way. The accuracy and practicality of these developments are evaluated by comparison with the experimental results, showing the capability of the proposed solution in providing distortion predictions with errors lower than 10% in comparison with the experimental results.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/66576
url http://hdl.handle.net/10810/66576
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://www.mdpi.com/2504-4494/8/1/9
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/es/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/es/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Addi. Archivo Digital para la Docencia y la Investigación
instname:Universidad del País Vasco
instname_str Universidad del País Vasco
reponame_str Addi. Archivo Digital para la Docencia y la Investigación
collection Addi. Archivo Digital para la Docencia y la Investigación
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869403400286765056
score 15.301603

Similares en LA Referencia