Please use this identifier to cite or link to this item: 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

Files in This Item:
File Description SizeFormat
1-s2.0-S2351978917305371-main.pdf347.72 kBAdobe PDFView/Open
Show full item record

SCOPUSTM   
Citations

33
checked on Nov 4, 2024

WEB OF SCIENCETM
Citations

23
checked on Nov 2, 2024

Page view(s)

117
checked on Oct 30, 2024

Download(s)

84
checked on Oct 30, 2024

Google ScholarTM

Check

Altmetric

Altmetric


This item is licensed under a Creative Commons License Creative Commons