Optimal Postponement in Supply Chain Network Design Under Uncertainty: An Application for Additive Manufacturing

Publication TypeJournal Article
Year of Publication2020
AuthorsDaniel Ramón-Lumbierres; F.-Javier Heredia; Joaquim Minguella-Canela; Asier Muguruza-Blanco
Journal TitleInternational Journal of Production Research
Pages5198-5215
Journal Date07/2020
PublisherTaylor&Francis
ISSN Number0020-7543
Key Wordsmanufacturing; postponement; stochastic programming; supply chain network design; 3D printing; additive manufacturing; research; paper
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.
URLClick Here
DOI10.1080/00207543.2020.1775908
Preprinthttp://hdl.handle.net/2117/327874
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