Sustainable short-term production planning optimization

Detalhes bibliográficos
Autor(a) principal: Zanella, Fernando
Data de Publicação: 2023
Outros Autores: Vaz, Clara B.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10198/29487
Resumo: This study proposes a framework for short-term production planning of a Portuguese company operating as a tier 2 supplier in the automotive sector. The framework is intended to support the decision-making process regarding a single progressive hydraulic press, which is used to manufacture cold-stamped parts for exhaust systems. The framework consists of two sequential levels: (1) a Mixed-Integer Linear Programming (MILP) model to determine the optimal production quantities per week while minimizing the total cost; (2) a dynamic production sequencing rule for scheduling operations on the hydraulic press. The two levels are combined and implemented in Excel, where the MILP model is solved using the Solver add-in, and the second level uses the optimal production quantities as inputs to determine the production sequence using a dynamic priority rule. To validate the framework, a proposed optimal plan was compared to a real plan executed by the company, and it was found that the framework could save up to 22.1% of the total cost observed in reality while still satisfying demand. To address uncertainties, the framework requires a rolling weekly planning horizon.
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spelling Sustainable short-term production planning optimizationMixed-integer linear programmingShort-term production planningResponsible productionThis study proposes a framework for short-term production planning of a Portuguese company operating as a tier 2 supplier in the automotive sector. The framework is intended to support the decision-making process regarding a single progressive hydraulic press, which is used to manufacture cold-stamped parts for exhaust systems. The framework consists of two sequential levels: (1) a Mixed-Integer Linear Programming (MILP) model to determine the optimal production quantities per week while minimizing the total cost; (2) a dynamic production sequencing rule for scheduling operations on the hydraulic press. The two levels are combined and implemented in Excel, where the MILP model is solved using the Solver add-in, and the second level uses the optimal production quantities as inputs to determine the production sequence using a dynamic priority rule. To validate the framework, a proposed optimal plan was compared to a real plan executed by the company, and it was found that the framework could save up to 22.1% of the total cost observed in reality while still satisfying demand. To address uncertainties, the framework requires a rolling weekly planning horizon.This work has been supported by Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021).Springer NatureBiblioteca Digital do IPBZanella, FernandoVaz, Clara B.2024-02-15T14:58:38Z20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10198/29487engZanella, Fernando; Vaz, Clara B. (2023). Sustainable short-term production planning optimization. SN Computer Science. ISSN 2662-995X. 4:6, p. 1-122662-995X10.1007/s42979-023-02261-72661-8907info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-21T01:19:15Zoai:bibliotecadigital.ipb.pt:10198/29487Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:39:15.988818Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Sustainable short-term production planning optimization
title Sustainable short-term production planning optimization
spellingShingle Sustainable short-term production planning optimization
Zanella, Fernando
Mixed-integer linear programming
Short-term production planning
Responsible production
title_short Sustainable short-term production planning optimization
title_full Sustainable short-term production planning optimization
title_fullStr Sustainable short-term production planning optimization
title_full_unstemmed Sustainable short-term production planning optimization
title_sort Sustainable short-term production planning optimization
author Zanella, Fernando
author_facet Zanella, Fernando
Vaz, Clara B.
author_role author
author2 Vaz, Clara B.
author2_role author
dc.contributor.none.fl_str_mv Biblioteca Digital do IPB
dc.contributor.author.fl_str_mv Zanella, Fernando
Vaz, Clara B.
dc.subject.por.fl_str_mv Mixed-integer linear programming
Short-term production planning
Responsible production
topic Mixed-integer linear programming
Short-term production planning
Responsible production
description This study proposes a framework for short-term production planning of a Portuguese company operating as a tier 2 supplier in the automotive sector. The framework is intended to support the decision-making process regarding a single progressive hydraulic press, which is used to manufacture cold-stamped parts for exhaust systems. The framework consists of two sequential levels: (1) a Mixed-Integer Linear Programming (MILP) model to determine the optimal production quantities per week while minimizing the total cost; (2) a dynamic production sequencing rule for scheduling operations on the hydraulic press. The two levels are combined and implemented in Excel, where the MILP model is solved using the Solver add-in, and the second level uses the optimal production quantities as inputs to determine the production sequence using a dynamic priority rule. To validate the framework, a proposed optimal plan was compared to a real plan executed by the company, and it was found that the framework could save up to 22.1% of the total cost observed in reality while still satisfying demand. To address uncertainties, the framework requires a rolling weekly planning horizon.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-01-01T00:00:00Z
2024-02-15T14:58:38Z
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://hdl.handle.net/10198/29487
url http://hdl.handle.net/10198/29487
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Zanella, Fernando; Vaz, Clara B. (2023). Sustainable short-term production planning optimization. SN Computer Science. ISSN 2662-995X. 4:6, p. 1-12
2662-995X
10.1007/s42979-023-02261-7
2661-8907
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
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