Supply Chain Design and Inventory Management Optimization in the Motors Industry

Autores
Rodriguez, Maria Analia; Vecchietti, Aldo; Grossmann, Ignacion E.; Harjunskonsky, Liro
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This article studies the supply chain redesign under demand uncertainty over a multi-period planning. We propose an optimization model to solve the problem taking into account strategic and tactical plans. This model is applied to the electric motors industry but it can be easily extended to other supply chains. Long term decisions involve new installations, expansions and elimination of warehouses. Tactical decisions include deciding inventory levels (safety stock and expected inventory) for each type of product in distribution centers and customer plants, as well as the connection links between the supply chain nodes. Capacity constraints are also considered when planning inventory levels. At the tactical level it is analyzed how demand of failing motors is satisfied, and whether to use new or used motors. The uncertain demand is addressed by defining the optimal amount of safety stock that guarantees certain service level at a customer plant. In addition, the risk-pooling effect is taken into account when defining inventory levels in distribution centers and customer zones. Due to the nonlinear nature of the original formulation, a piecewise linearization approach is applied to obtain a tight lower bound of the optimal solution.
Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina
Fil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina
Fil: Grossmann, Ignacion E.. University Of Carnegie Mellon; Estados Unidos
Fil: Harjunskonsky, Liro. ABB AG, Corporate Research Germany; Alemania
Materia
Optimization
Supply Chain
Inventory Management
Electrical Motors Industry
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/6958
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/6958
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Supply Chain Design and Inventory Management Optimization in the Motors IndustryRodriguez, Maria AnaliaVecchietti, AldoGrossmann, Ignacion E.Harjunskonsky, LiroOptimizationSupply ChainInventory ManagementElectrical Motors Industryhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2This article studies the supply chain redesign under demand uncertainty over a multi-period planning. We propose an optimization model to solve the problem taking into account strategic and tactical plans. This model is applied to the electric motors industry but it can be easily extended to other supply chains. Long term decisions involve new installations, expansions and elimination of warehouses. Tactical decisions include deciding inventory levels (safety stock and expected inventory) for each type of product in distribution centers and customer plants, as well as the connection links between the supply chain nodes. Capacity constraints are also considered when planning inventory levels. At the tactical level it is analyzed how demand of failing motors is satisfied, and whether to use new or used motors. The uncertain demand is addressed by defining the optimal amount of safety stock that guarantees certain service level at a customer plant. In addition, the risk-pooling effect is taken into account when defining inventory levels in distribution centers and customer zones. Due to the nonlinear nature of the original formulation, a piecewise linearization approach is applied to obtain a tight lower bound of the optimal solution.Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); ArgentinaFil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); ArgentinaFil: Grossmann, Ignacion E.. University Of Carnegie Mellon; Estados UnidosFil: Harjunskonsky, Liro. ABB AG, Corporate Research Germany; AlemaniaItalian Association of Chemical Engineering2013-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/6958Rodriguez, Maria Analia; Vecchietti, Aldo; Grossmann, Ignacion E.; Harjunskonsky, Liro; Supply Chain Design and Inventory Management Optimization in the Motors Industry; Italian Association of Chemical Engineering; Chemical Engineering Transactions; 32; 6-2013; 1171-11761974-9791enginfo:eu-repo/semantics/altIdentifier/url/http://www.aidic.it/cet/13/32/196.pdfinfo:eu-repo/semantics/altIdentifier/doi/info:eu-repo/semantics/altIdentifier/doi/10.3303/cet1332196info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:42:00Zoai:ri.conicet.gov.ar:11336/6958instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:42:00.586CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Supply Chain Design and Inventory Management Optimization in the Motors Industry
title Supply Chain Design and Inventory Management Optimization in the Motors Industry
spellingShingle Supply Chain Design and Inventory Management Optimization in the Motors Industry
Rodriguez, Maria Analia
Optimization
Supply Chain
Inventory Management
Electrical Motors Industry
title_short Supply Chain Design and Inventory Management Optimization in the Motors Industry
title_full Supply Chain Design and Inventory Management Optimization in the Motors Industry
title_fullStr Supply Chain Design and Inventory Management Optimization in the Motors Industry
title_full_unstemmed Supply Chain Design and Inventory Management Optimization in the Motors Industry
title_sort Supply Chain Design and Inventory Management Optimization in the Motors Industry
dc.creator.none.fl_str_mv Rodriguez, Maria Analia
Vecchietti, Aldo
Grossmann, Ignacion E.
Harjunskonsky, Liro
author Rodriguez, Maria Analia
author_facet Rodriguez, Maria Analia
Vecchietti, Aldo
Grossmann, Ignacion E.
Harjunskonsky, Liro
author_role author
author2 Vecchietti, Aldo
Grossmann, Ignacion E.
Harjunskonsky, Liro
author2_role author
author
author
dc.subject.none.fl_str_mv Optimization
Supply Chain
Inventory Management
Electrical Motors Industry
topic Optimization
Supply Chain
Inventory Management
Electrical Motors Industry
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This article studies the supply chain redesign under demand uncertainty over a multi-period planning. We propose an optimization model to solve the problem taking into account strategic and tactical plans. This model is applied to the electric motors industry but it can be easily extended to other supply chains. Long term decisions involve new installations, expansions and elimination of warehouses. Tactical decisions include deciding inventory levels (safety stock and expected inventory) for each type of product in distribution centers and customer plants, as well as the connection links between the supply chain nodes. Capacity constraints are also considered when planning inventory levels. At the tactical level it is analyzed how demand of failing motors is satisfied, and whether to use new or used motors. The uncertain demand is addressed by defining the optimal amount of safety stock that guarantees certain service level at a customer plant. In addition, the risk-pooling effect is taken into account when defining inventory levels in distribution centers and customer zones. Due to the nonlinear nature of the original formulation, a piecewise linearization approach is applied to obtain a tight lower bound of the optimal solution.
Fil: Rodriguez, Maria Analia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina
Fil: Vecchietti, Aldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentina
Fil: Grossmann, Ignacion E.. University Of Carnegie Mellon; Estados Unidos
Fil: Harjunskonsky, Liro. ABB AG, Corporate Research Germany; Alemania
description This article studies the supply chain redesign under demand uncertainty over a multi-period planning. We propose an optimization model to solve the problem taking into account strategic and tactical plans. This model is applied to the electric motors industry but it can be easily extended to other supply chains. Long term decisions involve new installations, expansions and elimination of warehouses. Tactical decisions include deciding inventory levels (safety stock and expected inventory) for each type of product in distribution centers and customer plants, as well as the connection links between the supply chain nodes. Capacity constraints are also considered when planning inventory levels. At the tactical level it is analyzed how demand of failing motors is satisfied, and whether to use new or used motors. The uncertain demand is addressed by defining the optimal amount of safety stock that guarantees certain service level at a customer plant. In addition, the risk-pooling effect is taken into account when defining inventory levels in distribution centers and customer zones. Due to the nonlinear nature of the original formulation, a piecewise linearization approach is applied to obtain a tight lower bound of the optimal solution.
publishDate 2013
dc.date.none.fl_str_mv 2013-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/6958
Rodriguez, Maria Analia; Vecchietti, Aldo; Grossmann, Ignacion E.; Harjunskonsky, Liro; Supply Chain Design and Inventory Management Optimization in the Motors Industry; Italian Association of Chemical Engineering; Chemical Engineering Transactions; 32; 6-2013; 1171-1176
1974-9791
url http://hdl.handle.net/11336/6958
identifier_str_mv Rodriguez, Maria Analia; Vecchietti, Aldo; Grossmann, Ignacion E.; Harjunskonsky, Liro; Supply Chain Design and Inventory Management Optimization in the Motors Industry; Italian Association of Chemical Engineering; Chemical Engineering Transactions; 32; 6-2013; 1171-1176
1974-9791
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.aidic.it/cet/13/32/196.pdf
info:eu-repo/semantics/altIdentifier/doi/
info:eu-repo/semantics/altIdentifier/doi/10.3303/cet1332196
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Italian Association of Chemical Engineering
publisher.none.fl_str_mv Italian Association of Chemical Engineering
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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