The cutting stock problem applied to the hardening process in an automotive spring factory
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1007/s10100-022-00826-0 http://hdl.handle.net/11449/246338 |
Resumo: | In this paper, an automotive spring factory is studied to optimize its hardening process. The assignment of items to the hardening furnace is treated as a one-dimensional cutting stock problem, an approach not found in the literature. To make a feasible decision in this assignment, the activity that follows the furnace, i.e. the bending of the items, is also analyzed. In order to consider practical constraints of the company, as the position of items on the furnace, the proposed mathematical model is based on an arc flow formulation and it is validated through instances with real and random data. A heuristic approach was developed to simulate the company's decision, and to compare the random instances results. Results with real data demonstrate that the model found, in viable computational time, a solution significantly better than that of current company practice, increasing the production by 51.2%. This increase was mainly made possible by a 71.5% reduction in wasted space in the furnace and by a 26.2% reduction of time spent on setups. In random instances, the mathematical model also far outperformed the company's practice, finding the optimal solution in 98.9% of the cases. It was identified that computational time is the most sensitive criterion to the variation in the parameters and the length of the items is the parameter that most influences the results. |
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The cutting stock problem applied to the hardening process in an automotive spring factoryArc flow modelAutomotive spring industryHardening furnaceMathematical modelingOne-dimensional cutting stock problemIn this paper, an automotive spring factory is studied to optimize its hardening process. The assignment of items to the hardening furnace is treated as a one-dimensional cutting stock problem, an approach not found in the literature. To make a feasible decision in this assignment, the activity that follows the furnace, i.e. the bending of the items, is also analyzed. In order to consider practical constraints of the company, as the position of items on the furnace, the proposed mathematical model is based on an arc flow formulation and it is validated through instances with real and random data. A heuristic approach was developed to simulate the company's decision, and to compare the random instances results. Results with real data demonstrate that the model found, in viable computational time, a solution significantly better than that of current company practice, increasing the production by 51.2%. This increase was mainly made possible by a 71.5% reduction in wasted space in the furnace and by a 26.2% reduction of time spent on setups. In random instances, the mathematical model also far outperformed the company's practice, finding the optimal solution in 98.9% of the cases. It was identified that computational time is the most sensitive criterion to the variation in the parameters and the length of the items is the parameter that most influences the results.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Paraná Federal University of Technology (UTFPR), Avenida Dos Pioneiros, 3131, Jardim Morumbi, PRSão Paulo State University (UNESP) Mathematics Department, Avenida Eng. Luís Edmundo Carrijo Coube, 14-01, Vargem Limpa, SPSão Paulo State University (UNESP) Mathematics Department, Rua Cristóvão Colombo, 2265, Jardim Nazareth, SPSão Paulo State University (UNESP) Mathematics Department, Avenida Eng. Luís Edmundo Carrijo Coube, 14-01, Vargem Limpa, SPSão Paulo State University (UNESP) Mathematics Department, Rua Cristóvão Colombo, 2265, Jardim Nazareth, SPFAPESP: 2013/07375-0FAPESP: 2016/01860-1CNPq: 305261/2018-5CNPq: 306558/2018-1CNPq: 406335/2018-4CNPq: 421130/2018-0Paraná Federal University of Technology (UTFPR)Universidade Estadual Paulista (UNESP)de Lara Andrade, Pedro Rochavetz [UNESP]de Araujo, Silvio Alexandre [UNESP]Cherri, Adriana Cristina [UNESP]Lemos, Felipe Kesrouani [UNESP]2023-07-29T12:38:12Z2023-07-29T12:38:12Z2023-06-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article637-664http://dx.doi.org/10.1007/s10100-022-00826-0Central European Journal of Operations Research, v. 31, n. 2, p. 637-664, 2023.1613-91781435-246Xhttp://hdl.handle.net/11449/24633810.1007/s10100-022-00826-02-s2.0-85142219674Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCentral European Journal of Operations Researchinfo:eu-repo/semantics/openAccess2023-07-29T12:38:12Zoai:repositorio.unesp.br:11449/246338Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-07-29T12:38:12Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
The cutting stock problem applied to the hardening process in an automotive spring factory |
title |
The cutting stock problem applied to the hardening process in an automotive spring factory |
spellingShingle |
The cutting stock problem applied to the hardening process in an automotive spring factory de Lara Andrade, Pedro Rochavetz [UNESP] Arc flow model Automotive spring industry Hardening furnace Mathematical modeling One-dimensional cutting stock problem |
title_short |
The cutting stock problem applied to the hardening process in an automotive spring factory |
title_full |
The cutting stock problem applied to the hardening process in an automotive spring factory |
title_fullStr |
The cutting stock problem applied to the hardening process in an automotive spring factory |
title_full_unstemmed |
The cutting stock problem applied to the hardening process in an automotive spring factory |
title_sort |
The cutting stock problem applied to the hardening process in an automotive spring factory |
author |
de Lara Andrade, Pedro Rochavetz [UNESP] |
author_facet |
de Lara Andrade, Pedro Rochavetz [UNESP] de Araujo, Silvio Alexandre [UNESP] Cherri, Adriana Cristina [UNESP] Lemos, Felipe Kesrouani [UNESP] |
author_role |
author |
author2 |
de Araujo, Silvio Alexandre [UNESP] Cherri, Adriana Cristina [UNESP] Lemos, Felipe Kesrouani [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Paraná Federal University of Technology (UTFPR) Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
de Lara Andrade, Pedro Rochavetz [UNESP] de Araujo, Silvio Alexandre [UNESP] Cherri, Adriana Cristina [UNESP] Lemos, Felipe Kesrouani [UNESP] |
dc.subject.por.fl_str_mv |
Arc flow model Automotive spring industry Hardening furnace Mathematical modeling One-dimensional cutting stock problem |
topic |
Arc flow model Automotive spring industry Hardening furnace Mathematical modeling One-dimensional cutting stock problem |
description |
In this paper, an automotive spring factory is studied to optimize its hardening process. The assignment of items to the hardening furnace is treated as a one-dimensional cutting stock problem, an approach not found in the literature. To make a feasible decision in this assignment, the activity that follows the furnace, i.e. the bending of the items, is also analyzed. In order to consider practical constraints of the company, as the position of items on the furnace, the proposed mathematical model is based on an arc flow formulation and it is validated through instances with real and random data. A heuristic approach was developed to simulate the company's decision, and to compare the random instances results. Results with real data demonstrate that the model found, in viable computational time, a solution significantly better than that of current company practice, increasing the production by 51.2%. This increase was mainly made possible by a 71.5% reduction in wasted space in the furnace and by a 26.2% reduction of time spent on setups. In random instances, the mathematical model also far outperformed the company's practice, finding the optimal solution in 98.9% of the cases. It was identified that computational time is the most sensitive criterion to the variation in the parameters and the length of the items is the parameter that most influences the results. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-07-29T12:38:12Z 2023-07-29T12:38:12Z 2023-06-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1007/s10100-022-00826-0 Central European Journal of Operations Research, v. 31, n. 2, p. 637-664, 2023. 1613-9178 1435-246X http://hdl.handle.net/11449/246338 10.1007/s10100-022-00826-0 2-s2.0-85142219674 |
url |
http://dx.doi.org/10.1007/s10100-022-00826-0 http://hdl.handle.net/11449/246338 |
identifier_str_mv |
Central European Journal of Operations Research, v. 31, n. 2, p. 637-664, 2023. 1613-9178 1435-246X 10.1007/s10100-022-00826-0 2-s2.0-85142219674 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Central European Journal of Operations Research |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
637-664 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1799965656314019840 |