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https://hdl.handle.net/10316/102071
Title: | Improving Supply Chain Visibility With Artificial Neural Networks | Authors: | Silva, Nathalie Santos da Ferreira, Luis Miguel D. F. Silva, Cristovão Magalhães, Vanessa Sofia Melo Neto, Pedro |
Keywords: | Artificial neural networks; experimental; simulation; Supply chain; visibility | Issue Date: | 2017 | Project: | Portugal 2020 project DM4Manufacturing POCI-01-0145-FEDER-016418 by UE/FEDER through the program COMPETE2020 | metadata.degois.publication.title: | Procedia Manufacturing | metadata.degois.publication.volume: | 11 | Abstract: | The vulnerability of supply chains has been increasing and to properly respond to disruptions, visibility across the supply chain is required. This paper addresses these challenges by relying on the use of artificial neural networks to predict the capacity of a simulated supply chain to fulfil incoming orders and to anticipate which supply chain nodes will receive an order for the next period. To assess the effectiveness of the approach two experiments were conducted. The findings contribute to the understanding of on how artificial neural networks can be applied to reduce the vulnerability of supply chains. | URI: | https://hdl.handle.net/10316/102071 | ISSN: | 23519789 | DOI: | 10.1016/j.promfg.2017.07.329 | Rights: | openAccess |
Appears in Collections: | FCTUC Eng.Mecânica - Artigos em Revistas Internacionais |
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