Improving Supply Chain Visibility With Artificial Neural Networks

• Autor(a) principal: Silva, Nathalie Santos da
• Data de Publicação: 2017
• Outros Autores: Ferreira, Luis Miguel D. F., Silva, Cristovão, Magalhães, Vanessa Sofia Melo, Neto, Pedro
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10316/102071; https://doi.org/10.1016/j.promfg.2017.07.329
• topic: Artificial neural networks; experimental; simulation; Supply chain; visibility

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.