Publicação
Simulation of an automotive supply chain in Simio: Data model validation
| Resumo: | This paper presents a simulation model of the supply chain of a company of the automotive industry. The purpose of this paper is to use the presented model to validate the considered set of variables that we think are relevant to the problem. This approach was important as it allowed to consider a set of variables that could have been ignored if a different approach had been followed. It should be stressed that, due to privacy concerns, real data was not used, but rather random distributions assigned by the modeler. Notwithstanding, by recognizing that, for the data used, the outputs are in accordance to what happens in the real system, the authors concluded that the set of variables can be considered as validated. Yet, it is still necessary to further complement the model with additional available variables that were not included at this stage, due to its complexity, e.g., customer demand variability, uncertainty associated to suppliers' and impact of external events, such as transportation delays. |
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| Autores principais: | Vieira, António Amaro Costa |
| Outros Autores: | Dias, Luis S.; Santos, Maribel Yasmina; Pereira, Guilherme; Oliveira, José A. |
| Assunto: | Big Data (BD) Discrete-event simulation Industry 4.0 Logistics Real-time Supply chain |
| Ano: | 2018 |
| País: | Portugal |
| Tipo de documento: | comunicação em conferência |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | This paper presents a simulation model of the supply chain of a company of the automotive industry. The purpose of this paper is to use the presented model to validate the considered set of variables that we think are relevant to the problem. This approach was important as it allowed to consider a set of variables that could have been ignored if a different approach had been followed. It should be stressed that, due to privacy concerns, real data was not used, but rather random distributions assigned by the modeler. Notwithstanding, by recognizing that, for the data used, the outputs are in accordance to what happens in the real system, the authors concluded that the set of variables can be considered as validated. Yet, it is still necessary to further complement the model with additional available variables that were not included at this stage, due to its complexity, e.g., customer demand variability, uncertainty associated to suppliers' and impact of external events, such as transportation delays. |
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