Improving Supply Chain Visibility With Artificial Neural Networks

被引:25
|
作者
Silva, Nathalie
Ferreira, Luis Miguel D. F. [1 ]
Silva, Cristovao [1 ]
Magalhaes, Vanessa [1 ]
Neto, Pedro [1 ]
机构
[1] Univ Coimbra, Dept Mech Engn, Rua Luis Reis Santos Pinhal Marrocos, P-3030788 Coimbra, Portugal
关键词
Supply chain; visibility; Artificial neural networks; simulation; experimental;
D O I
10.1016/j.promfg.2017.07.329
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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. (C) 2017 The Authors. Published by Elsevier B.V.
引用
收藏
页码:2083 / 2090
页数:8
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