Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/66811
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Campo DC | Valor | Idioma |
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dc.contributor.author | Vieira, António Amaro Costa | por |
dc.contributor.author | Dias, Luis S. | por |
dc.contributor.author | Santos, Maribel Yasmina | por |
dc.contributor.author | Pereira, Guilherme | por |
dc.contributor.author | Oliveira, José A. | por |
dc.date.accessioned | 2020-09-07T10:22:31Z | - |
dc.date.available | 2020-09-07T10:22:31Z | - |
dc.date.issued | 2020 | - |
dc.identifier.issn | 1569-190X | - |
dc.identifier.uri | https://hdl.handle.net/1822/66811 | - |
dc.description.abstract | Simulation stands out as an appropriate method for the Supply Chain Management (SCM) field. Nevertheless, to produce accurate simulations of Supply Chains (SCs), several business processes must be considered. Thus, when using real data in these simulation models, Big Data concepts and technologies become necessary, as the involved data sources generate data at increasing volume, velocity and variety, in what is known as a Big Data context. While developing such solution, several data issues were found, with simulation proving to be more efficient than traditional data profiling techniques in identifying them. Thus, this paper proposes the use of simulation as a semantic validator of the data, proposed a classification for such issues and quantified their impact in the volume of data used in the final achieved solution. This paper concluded that, while SC simulations using Big Data concepts and technologies are within the grasp of organizations, their data models still require considerable improvements, in order to produce perfect mimics of their SCs. In fact, it was also found that simulation can help in identifying and bypassing some of these issues. | por |
dc.description.sponsorship | This work has been supported by FCT (Fundacao para a Ciencia e Tecnologia) within the Project Scope: UID/CEC/00319/2019 and by the Doctoral scholarship PDE/BDE/114566/2016 funded by FCT, the Portuguese Ministry of Science, Technology and Higher Education, through national funds, and co-financed by the European Social Fund (ESF) through the Operational Programme for Human Capital (POCH). | por |
dc.language.iso | eng | por |
dc.publisher | Elsevier 1 | por |
dc.relation | UID/CEC/00319/2019 | por |
dc.relation | PDE/BDE/114566/2016 | por |
dc.rights | openAccess | por |
dc.subject | Simulation | por |
dc.subject | Big Data | por |
dc.subject | Data issues | por |
dc.subject | Semantic validation | por |
dc.subject | Supply chain management | por |
dc.subject | Industry 4.0 | por |
dc.title | On the use of simulation as a Big Data semantic validator for supply chain management | por |
dc.type | article | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S1569190X19301182 | por |
oaire.citationVolume | 98 | por |
dc.date.updated | 2020-09-07T10:14:35Z | - |
dc.identifier.doi | 10.1016/j.simpat.2019.101985 | por |
dc.subject.wos | Science & Technology | - |
sdum.export.identifier | 5669 | - |
sdum.journal | Simulation Modelling Practice and Theory | por |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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2019_SIMPAT_manuscript.pdf | 900,91 kB | Adobe PDF | Ver/Abrir |