Performance Evaluation and Operational Availability of a Textile Manufacturing 4.0 Using Stochastic Petri Nets

Edson Moura Silva; Danilo Araújo; Ermeson Andrade

doi:10.22456/2175-2745.135781

Authors

Edson Moura Silva UFRPE - Federal Rural University of Pernambuco, Department of Computing, PO Box 52171-900, Recife, PE, Brazil. https://orcid.org/0000-0001-8084-610X
Danilo Ricardo Barbosa de Araújo UFRPE - Federal Rural University of Pernambuco, Department of Computing, PO Box 52171-900, Recife, PE, Brazil. https://orcid.org/0000-0002-4822-0390
Ermeson Carneiro de Andrade UFRPE - Federal Rural University of Pernambuco, Department of Computing, PO Box 52171-900, Recife, PE, Brazil. https://orcid.org/0000-0002-9614-4492

DOI:

https://doi.org/10.22456/2175-2745.135781

Keywords:

Textile Manufacturing 4.0, Performance Evaluation, Availability Assessment, Stochastic Petri Nets

Abstract

The Brazilian clothing industry is the 7th largest globally, generating an annual revenue of USD 10 billion. However, Brazil is only 54th in industrial innovation investments. The constraint on industrial innovation investments represents a challenge for the implementation of Industry 4.0, especially in local garment manufacturing hubs. It is crucial to assess the impact of Industry 4.0 in these hubs in order to highlight its benefits. The study proposes the development of an approach based on Stochastic Petri Nets to model production processes in the textile industry, applied to a company in the garment manufacturing hub of the Agreste region of Pernambuco. The results demonstrate that this approach has the potential to assist garment administrators in optimizing production processes and making more informed decisions. Additionally, the approach allows administrators to maintain resources balanced, efficient, and available in accordance with the production goals of the modern market.

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Author Biographies

Edson Moura Silva, UFRPE - Federal Rural University of Pernambuco, Department of Computing, PO Box 52171-900, Recife, PE, Brazil.

Is a master student in Computer Science at the Federal Rural University of Pernambuco. His research interest is focused on industrial process modeling and data analysis.

Danilo Ricardo Barbosa de Araújo, UFRPE - Federal Rural University of Pernambuco, Department of Computing, PO Box 52171-900, Recife, PE, Brazil.

Is an associate professor at the Department of Computing at the Federal Rural University of Pernambuco, Brazil. In 2015, he completed his PhD in Computer Science from the Federal University of Pernambuco. His research interest is focused in High Capacity Networks, Artificial Intelligence and Complex Networks.

Ermeson Carneiro de Andrade, UFRPE - Federal Rural University of Pernambuco, Department of Computing, PO Box 52171-900, Recife, PE, Brazil.

Is an associate professor at the Department of Computing at the Federal Rural University of Pernambuco, Brazil. In 2014, he completed his PhD in Computer Science from the Federal University of Pernambuco. His research interest is focused in performance, Dependability, Critical infrastructure, Data science and Modeling.

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