Optimal Supply Chain Strategy and Postponement Degree with 3D Printing
Mon, 07/18/2016 - 19:04 — admin
| Publication Type | Conference Paper |
| Year of Publication | 2016 |
| Authors | Daniel Ramon Lumbierres; Asier Muguruza; Robert Gimeno Feu; Ping Guo; Mary Hamilton; Kiron Shastry; Sunny Webb; Joaquim Minguella; F.-Javier Heredia |
| Conference Name | 28th European Conference on Operational Research |
| Series Title | Conference Handbook |
| Pagination | 330 |
| Conference Date | 3-6/07/2016 |
| Conference Location | Poznan, Poland |
| Type of Work | contributed presentation. |
| Key Words | research; supply chain; 3D printing; stochastic programming; postponment; modeling; additive manufacturing |
| Abstract | In this contribution we would like to present the results of a research project developed by Accenture and BarcelonaTech aiming at studying the advantages of ultra-postponement with 3D printing using the analytical tools of operational research. In this project a new two-stage stochastic programming decision model has been developed to assess (a) the convenience of the introduction of 3D printing in any generic supply chain and (b) the optimal degree of postponement, the so called Customer Order Decoupling Point (CODP), assuming uncertainty in demand for multiple markets. To this end we propose the formulation
of a generic supply chain through an oriented graph that represents all the alternative technologies that can be deployed, defined through a set of operations for manufacturing, assembly and distribution, each one characterized by a lead time and cost parameters. Based on this graph we develop a mixed integer two-stage stochastic program that finds the optimal manufacturing technology to meet the demand of each market, the optimal production quantity for each operation and the optimal CODP for each technology. The results obtained with several case studies from real manufacturing companies are presented and analyzed. |
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