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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/6958
Ver los metadatos del registro completo
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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 Técnicas2025-09-03T10:10:08Zoai: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:34982025-09-03 10:10:09.191CONICET 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 |
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CONICET Digital (CONICET) |
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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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13.13397 |