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dc.contributor.authorRamón Lumbierres, Daniel Jacobo
dc.contributor.authorHeredia, F.-Javier (Francisco Javier)
dc.contributor.authorMinguella Canela, Joaquim
dc.contributor.authorMuguruza Blanco, Asier
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Mecànica
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Enginyeria Mecànica, Fluids i Aeronàutica
dc.date.accessioned2020-07-28T11:22:55Z
dc.date.available2020-07-28T11:22:55Z
dc.date.issued2020-06-17
dc.identifier.citationRamon, D. [et al.]. Optimal postponement in supply chain network design under uncertainty: an application for additive manufacturing. "International journal of production research", 17 Juny 2020,
dc.identifier.issn0020-7543
dc.identifier.urihttp://hdl.handle.net/2117/327874
dc.description.abstractThis study presents a new two-stage stochastic programming decision model for assessing how to introduce some new manufacturing technology into any generic supply and distribution chain. It additionally determines the optimal degree of postponement, as represented by the so-called customer order decoupling point (CODP), while assuming uncertainty in demand for multiple products. To this end, we propose here the formulation of a generic supply chain through an oriented graph that represents all the deployable alternative technologies, which are defined through a set of operations that are characterized by lead times and cost parameters. Based on this graph, we develop a mixed integer two-stage stochastic program that finds the optimal manufacturing technology for meeting each market’s demand, each operation’s optimal production quantity, and each selected technology’s optimal CODP. We also present and analyse a case study for introducing additive manufacturing technologies.
dc.description.sponsorshipThis work was developed under an Accenture Open Innovation University [grant number I-01326] and was also partially supported by grant RTI2018-097580-B-I00 of the Ministry of Economy and Competitiveness of Spain.
dc.language.isoeng
dc.publisherTaylor & Francis
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística
dc.subject.otherManufacturing
dc.subject.otherPostponement
dc.subject.otherStochastic programming
dc.subject.otherSupply chain network design
dc.subject.other3D printing
dc.subject.otherAdditive manufacturing
dc.titleOptimal postponement in supply chain network design under uncertainty: an application for additive manufacturing
dc.typeArticle
dc.contributor.groupUniversitat Politècnica de Catalunya. GNOM - Grup d'Optimització Numèrica i Modelització
dc.contributor.groupUniversitat Politècnica de Catalunya. TECNOFAB - Grup de Recerca en Tecnologies de Fabricació
dc.identifier.doi10.1080/00207543.2020.1775908
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::60 Probability theory and stochastic processes
dc.relation.publisherversionhttps://www.tandfonline.com/doi/abs/10.1080/00207543.2020.1775908
dc.rights.accessOpen Access
local.identifier.drac28933166
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-097580-B-I00/ES/MODELIZACION Y OPTIMIZACION DE PROBLEMAS ESTRUCTURADOS DE GRAN ESCALA Y APLICACIONES/
dc.relation.projectidinfo:eu-repo/grantAgreement/ACCENTURE TECHNOLOGY LABS/Strategic analytical models in supply chain design through mathematical optimization
local.citation.authorRamon, D.; Heredia, F.-Javier; Minguella-Canela, J.; Muguruza, A.
local.citation.publicationNameInternational journal of production research


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