Production system in a collaborative supply chain considering deterioration

This research presents a mathematical model for a collaborative planning of the supply chain involving four echelons (supplier, production plants, distribution, retails, or clients). The model seeks to maximize profit (utility) when all members of the chain share information related to demand. It is...

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Autores:
Acevedo-Chedid, Jaime
Salas-Navarro, Katherinne
Villalobo, Alina
Sana, Shib
Tipo de recurso:
Article of journal
Fecha de publicación:
2021
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/8346
Acceso en línea:
https://hdl.handle.net/11323/8346
https://doi.org/10.1007/s40819-021-00965-z
https://repositorio.cuc.edu.co/
Palabra clave:
Collaborative supply chain
Deteriorating products
Reverse flow
Cadena de suministro colaborativa
Productos en deterioro
Flujo inverso
Rights
embargoedAccess
License
Attribution-NonCommercial-NoDerivatives 4.0 International
id RCUC2_7f279d28dd709a31f251e8ea51a61dc4
oai_identifier_str oai:repositorio.cuc.edu.co:11323/8346
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.eng.fl_str_mv Production system in a collaborative supply chain considering deterioration
dc.title.translated.spa.fl_str_mv Sistema de producción en una cadena de suministro colaborativa considerando el deterioro
title Production system in a collaborative supply chain considering deterioration
spellingShingle Production system in a collaborative supply chain considering deterioration
Collaborative supply chain
Deteriorating products
Reverse flow
Cadena de suministro colaborativa
Productos en deterioro
Flujo inverso
title_short Production system in a collaborative supply chain considering deterioration
title_full Production system in a collaborative supply chain considering deterioration
title_fullStr Production system in a collaborative supply chain considering deterioration
title_full_unstemmed Production system in a collaborative supply chain considering deterioration
title_sort Production system in a collaborative supply chain considering deterioration
dc.creator.fl_str_mv Acevedo-Chedid, Jaime
Salas-Navarro, Katherinne
Villalobo, Alina
Sana, Shib
dc.contributor.author.spa.fl_str_mv Acevedo-Chedid, Jaime
Salas-Navarro, Katherinne
Villalobo, Alina
Sana, Shib
dc.subject.eng.fl_str_mv Collaborative supply chain
Deteriorating products
Reverse flow
topic Collaborative supply chain
Deteriorating products
Reverse flow
Cadena de suministro colaborativa
Productos en deterioro
Flujo inverso
dc.subject.spa.fl_str_mv Cadena de suministro colaborativa
Productos en deterioro
Flujo inverso
description This research presents a mathematical model for a collaborative planning of the supply chain involving four echelons (supplier, production plants, distribution, retails, or clients). The model seeks to maximize profit (utility) when all members of the chain share information related to demand. It is developed for the aggregate consolidation of different raw materials in cement production. The novelty of the model is the consideration of products that deteriorate in the process and thus it has effect on the production times in the plant and lead time. In this supply chain, quality and compliant products and the return of deteriorated products are two flows. The considerations are lead time, inventories with shortages and excesses, production times in normal and extra days, and subcontracting, among others. A mixed integer linear programming with demand scenario analysis is used to optimize and analyze the uncertainty that is consistent with the performance of the construction sector. The model is formed considering two suppliers, two production plants, two distributors, two retailers and two end customers. Four manufacturing inputs (raw materials) are considered for the manufacture of two types of products. A case study of the cement production supply chain of Cartagena (Colombia) is illustrated. The shared benefit is generated around 5 billion pesos (COP) for all members of the chain in a period of 6 months.
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2021-06-02T22:34:16Z
dc.date.available.none.fl_str_mv 2021-06-02T22:34:16Z
dc.date.issued.none.fl_str_mv 2021-01-24
dc.date.embargoEnd.none.fl_str_mv 2022-01-24
dc.type.spa.fl_str_mv Artículo de revista
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
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dc.type.content.spa.fl_str_mv Text
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
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dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
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dc.identifier.issn.spa.fl_str_mv 21995796
dc.identifier.uri.spa.fl_str_mv https://hdl.handle.net/11323/8346
dc.identifier.doi.spa.fl_str_mv https://doi.org/10.1007/s40819-021-00965-z
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 21995796
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/8346
https://doi.org/10.1007/s40819-021-00965-z
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
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spelling Acevedo-Chedid, JaimeSalas-Navarro, KatherinneVillalobo, AlinaSana, Shib2021-06-02T22:34:16Z2021-06-02T22:34:16Z2021-01-242022-01-2421995796https://hdl.handle.net/11323/8346https://doi.org/10.1007/s40819-021-00965-zCorporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/This research presents a mathematical model for a collaborative planning of the supply chain involving four echelons (supplier, production plants, distribution, retails, or clients). The model seeks to maximize profit (utility) when all members of the chain share information related to demand. It is developed for the aggregate consolidation of different raw materials in cement production. The novelty of the model is the consideration of products that deteriorate in the process and thus it has effect on the production times in the plant and lead time. In this supply chain, quality and compliant products and the return of deteriorated products are two flows. The considerations are lead time, inventories with shortages and excesses, production times in normal and extra days, and subcontracting, among others. A mixed integer linear programming with demand scenario analysis is used to optimize and analyze the uncertainty that is consistent with the performance of the construction sector. The model is formed considering two suppliers, two production plants, two distributors, two retailers and two end customers. Four manufacturing inputs (raw materials) are considered for the manufacture of two types of products. A case study of the cement production supply chain of Cartagena (Colombia) is illustrated. The shared benefit is generated around 5 billion pesos (COP) for all members of the chain in a period of 6 months.Esta investigación presenta un modelo matemático para una planificación colaborativa de la cadena de suministro. involucrando cuatro escalones (proveedor, plantas de producción, distribución, ventas al por menor o clientes). La El modelo busca maximizar las ganancias (utilidad) cuando todos los miembros de la cadena comparten información. relacionados con la demanda. Está desarrollado para la consolidación agregada de diferentes materias primas en producción de cemento. La novedad del modelo es la consideración de productos que se deterioran en el proceso y por lo tanto tiene efecto sobre los tiempos de producción en la planta y el tiempo de entrega. En esto cadena de suministro, productos de calidad y conformes y la devolución de productos deteriorados son dos fluye. Las consideraciones son tiempo de entrega, inventarios con faltas y excesos, producción tiempos en días normales y extras, y subcontratación, entre otros. Un entero mixto lineal La programación con análisis de escenarios de demanda se utiliza para optimizar y analizar la incertidumbre. que sea consistente con el desempeño del sector de la construcción. El modelo está formado considerando dos proveedores, dos plantas de producción, dos distribuidores, dos minoristas y dos finales clientes. Se consideran cuatro insumos de fabricación (materias primas) para la fabricación. de dos tipos de productos. Un estudio de caso de la cadena de suministro de la producción de cemento de Cartagena (Colombia) se ilustra. El beneficio compartido se genera alrededor de 5 mil millones de pesos (COP) para todos los integrantes de la cadena en un plazo de 6 meses.Acevedo-Chedid, Jaime-will be generated-orcid-0000-0001-8318-2636-600Salas-Navarro, Katherinne-will be generated-orcid-0000-0002-6290-3542-600Villalobo, AlinaSana, Shib-will be generated-orcid-0000-0002-7834-8969-600application/pdfengInternational Journal of Applied and Computational MathematicsAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/embargoedAccesshttp://purl.org/coar/access_right/c_f1cfCollaborative supply chainDeteriorating productsReverse flowCadena de suministro colaborativaProductos en deterioroFlujo inversoProduction system in a collaborative supply chain considering deteriorationSistema de producción en una cadena de suministro colaborativa considerando el deterioroArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionhttps://link.springer.com/article/10.1007/s40819-021-00965-z1. Angerhofer, B.J., Angelides, M.C.: A model and a performance measurement system for collaborative supply chains. Decis. Support Syst. 42(1), 283–301 (2006)2. Arns, M., Fischer, M., Kemper, P., Tepper, C.: Supply chain modelling and its analytical evaluation. J. Oper. Res. Soc. 53(8), 885–894 (2002)3. Aviv, Y.: The effect of collaborative forecasting on supply chain performance. Manag. Sci. 47(10), 1326–1343 (2001)4. Aviv, Y.: Gaining benefits from joint forecasting and replenishment processes: the case of auto-correlated demand. Manuf. Serv. Oper. Manag. 4(1), 55–74 (2002)5. Aviv, Y.: On the benefits of collaborative forecasting partnerships between retailers and manufacturers. Manag. Sci. 53(5), 777–794 (2007)6. Barratt, M.: Understanding the meaning of collaboration in the supply chain. Supply Chain Manag. Int. J. 9(1), 30–42 (2004)7. Binder, M., Clegg, B.: Enterprise management: a new frontier for organisations. Int. J. Prod. Econ. 106(2), 409–430 (2007)8. 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