Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/66808

TítuloSupply chain risk management: an interactive simulation model in a big data context
Autor(es)Vieira, António Amaro Costa
Dias, Luis S.
Santos, Maribel Yasmina
Pereira, Guilherme
Oliveira, José A.
Palavras-chaveBig Data
Industry 4.0
Simulation
Supply Chain
Data2020
EditoraElsevier B.V.
RevistaProcedia Manufacturing
Resumo(s)Peer-review under responsibility of the scientific committee of the International Conference on Industry 4.0 and Smart Manufacturing. Aligned with the Industry 4.0 research and innovation agenda, a Decision Support System is currently being developed with the purpose of enhancing decision-making in risk scenarios at Supply Chains. It is comprised of a Big Data Warehouse and a simulation model. The former stores and provides integrated real data to the simulation model, which models the respective materials and information flows. Thus, the purpose of this paper is to present such tool being used to test scenarios that, contrarily to the traditional simulation approach, incorporate disruptions in an interactive way, meaning that users may fire such events at any desired simulation time and with different parameters. Thus, the tool is used to assess the impact of disruptions in the performance of the system. The conclusions of this paper highlight the benefits that can be obtained with the proposed interactive approach, as it allows a virtualization of the real system to be obtained and, at the same time, use the simulation model to assess what would be the impact of certain disruptions.
TipoArtigo em ata de conferência
URIhttps://hdl.handle.net/1822/66808
DOI10.1016/j.promfg.2020.02.035
ISSN2351-9789
Versão da editorahttps://www.sciencedirect.com/science/article/pii/S2351978920305849
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

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