Optimal postponement in supply chain network design under uncertainty: an application for additive manufacturing

This 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.
This 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.
Peer Reviewed
Postprint (published version)