AUTOMAÇÃO APLICADA A MANUTENÇÃO INDUSTRIAL

Ademilson Donizete Brandini; Gilson José  da Silva

doi:10.31510/infa.v19i2.1539

Authors

Ademilson Donizete Brandini Faculdade de Tecnologia de Catanduva (Fatec) – Catanduva – SP – Brasil , Faculdade de Tecnologia de Catanduva (Fatec) – Catanduva – SP – Brasil https://orcid.org/0000-0001-9386-9634 (unauthenticated)
Gilson José da Silva Faculdade de Tecnologia de Catanduva (Fatec) – Catanduva – SP – Brasil , Faculdade de Tecnologia de Catanduva (Fatec) – Catanduva – SP – Brasil https://orcid.org/0000-0002-2565-8955 (unauthenticated)

DOI:

https://doi.org/10.31510/infa.v19i2.1539

Keywords:

automation, industrial maintenence, maintenance management

Abstract

The new technologies of the fourth industrial revolution have enormous benefits. By analyzing the data stored in your systems, processes can continually improve. This also allows for better maintenance schedules and lower risk of unplanned system failures. Consequently, increases in productivity allow production chains to have immense dynamism. Within this context, the objective of this work is to evaluate the impact of automation and its technologies on industrial maintenance. For this, a bibliographic research was carried out through the analysis of books and articles on the subject. It is possible to conclude that maintenance workers are included in the growing effects of industrial automation. The low costs of building automated systems make it possible for more processes to be automated. Due to resistance to new methods, many activities within maintenance generally do not adopt changes. However, the implementation of computerized systems has managed the tasks through automation in the maintenance process. This includes data collection, management, analysis, inventory scheduling, resource allocation and work orders. Automation has impacted maintenance, improving productivity, security and overall data management.

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References

ALMEIDA, J. S. G.; CAGNIN, R. F. A Indústria do Futuro no Brasil e no Mundo. São Paulo: IEDI, 2019. Disponível em:

<https://iedi.org.br/media/site/artigos/20190311_industria_do_futuro_no_brasil_e_no_mundo.pdf> Acesso em: 20 Mai. 2022.

BARTELT, T. L. M. Industrial Automated Systems: Instrumentation and Motion Control (Book Only). Cengage Learning, 2011.

CIVERCHIA, F.; BOCCHINO, S.; SALVADORI, C.; ROSSI, E.; MAGGIANI, L.; PETRACCA, M. Industrial Internet of Things monitoring solution for advanced predictive maintenance applications. Journal of Industrial Information Integration, v. 7, p. 4-12, 2017. DOI: https://doi.org/10.1016/j.jii.2017.02.003

FRANCIOSI, C.; LUNG, B.; MIRANDA, S.; RIEMMA, S. Maintenance for sustainability in the industry 4.0 context: A scoping literature review. IFAC-PapersOnLine, v. 51, n. 11, p. 903-908, 2018. DOI: https://doi.org/10.1016/j.ifacol.2018.08.459

GIL, A. C. Como elaborar projetos de pesquisa. 4 Ed. São Paulo: Atlas, 2010.

GIL, A. C. Métodos e técnicas de pesquisa social. 6 Ed. São Paulo: Atlas, 2006.

KARDEC, A., NASCIF, J. Manutenção: Função estratégica. 4. Ed. Rio de Janeiro: Editora Qualitymark, 2013.

LAKATOS, E. Metodologia científica. 1991. São Paulo: Atlas.

LAKATOS, E. M. Metodologia do trabalho científico: projetos de pesquisa/pesquisa bibliográfica/teses de doutorado, dissertações de mestrado, trabalhos de conclusão de curso. São Paulo: Atlas, 2017.

MOURTZIS, D. Introduction to cloud technology and Industry 4.0. In: Design and Operation of Production Networks for Mass Personalization in the Era of Cloud Technology. Elsevier, 2022. p. 1-12. DOI: https://doi.org/10.1016/B978-0-12-823657-4.00011-7

PINTO, A. K., XAVIER, J. N. Manutenção: função estratégica. Rio de Janeiro: Qualitymark, 2001.

POÓR, P.; BASL, J.; ZENISEK, D. Predictive Maintenance 4.0 as next evolution step in industrial maintenance development. In: 2019 International Research Conference on Smart Computing and Systems Engineering (SCSE). IEEE, 2019. p. 245-253. DOI: https://doi.org/10.23919/SCSE.2019.8842659

RAMANI, B. V.; AMITH, C. A.; OOMMEN, J. M.; BABU, J.; PAUL, T.; SANKAR, V. Predictive analysis for industrial maintenance automation and optimization using a smart sensor network. In: 2016 International Conference on Next Generation Intelligent Systems (ICNGIS). IEEE, 2016. p. 1-5. DOI: https://doi.org/10.1109/ICNGIS.2016.7854004

RUIZ-SARMIENTO, J.; MONROY, J.; MORENO, F.; GALINDO, C.; BONELO, J.; GONZALEZ-JIMENEZ, J. A predictive model for the maintenance of industrial machinery in the context of industry 4.0. Engineering Applications of Artificial Intelligence, v. 87, 2020. DOI: https://doi.org/10.1016/j.engappai.2019.103289

SALERMO, L. S.; PEDROSO, L. P. Aplicação de ferramentas da mentalidade enxuta (lean thinking) em processo de manutenção predial. In: SIMPÓSIO BRASILEIRO DE GESTÃO E ECONOMIA DA CONSTRUÇÃO, 4., ENCONTRO LATINO-AMERICANO DE GESTÃO E ECONOMIA DA CONSTRUÇÃO, 2005, Porto Alegre. Anais... Porto Alegre: UFRGS, 2005. p. 1-10.

SHERWIN, D. J. A review of overall models for maintence management. Journal of Quality in Maintenance Engineering. v. 6, p. 138-164, 2000. DOI: https://doi.org/10.1108/13552510010341171

WANG, K.; WANG, Y. Como a IA afeta a manutenção preditiva futura: uma cartilha de aprendizado profundo. In: Workshop Internacional de Manufatura Avançada e Automação. Springer, Cingapura, 2017. p. 1-9.