Bibliometric Analysis of Maintenance Management: from corrective to asset management

Authors

DOI:

https://doi.org/10.9771/cp.v17i3.56602

Keywords:

Management, Maintenance, Bibliometrics.

Abstract

Over time, industrial maintenance management methodologies have gone through generations, evolving from basic repair techniques to the level of asset lifecycle management. This article aimed to analyze the evolution of these methodologies through bibliometric prospecting, analyzing articles available in the Scopus database, produced from 1966 to 2022. The data was analyzed in Bibliometrix, a package for the R programming language applied in Bibliometrics. The analysis sought to correlate this data with the development stages of maintenance management, from a support process to a strategic process, highlighting the methods used. The results pointed to maintenance management as an expanding process, associated with the development of monitoring technologies and advanced statistical analyses, while consolidating itself as a strategic methodology for asset management, creating yet another vector for business performance.

Downloads

Download data is not yet available.

Author Biographies

Olnei Martins de Lisboa, Federal Institute of Bahia

Bachelor in Production Engineering from the Centro de Ensino Superior de Maringá University in 2023.

Jonei Marques da Costa, Federal Institute of Bahia

PhD in Industrial Engineering from the Federal University of Bahia in 2021.

Ângela Maria Ferreira Lima, Federal Institute of Bahia

PhD in Energy and Environment from the Federal University of Bahia in 2017.

References

ARIA, M.; CUCCURULLO; C. Bibliometrix: An R-tool for comprehensive science mapping analysis: Journal of Informetrics, [s.l.], v. 11, n. 4, p. 959-975, 2017. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S1751157717300500. Acesso em: 17 ago. 2023.

BRAX, S. A manufacturer becoming service provider – challenges and a paradox. Managing Service Quality: An International Journal, [s.l.], v. 15, n. 2, p. 142-155, 1º abr. 2005. Disponível em: https://www.researchgate.net/publication/242336218_A_manufacturer_becoming_service_provider_-_Challenges_and_a_paradox. Acesso em: 10 ago. 2023.

CIMINO, C.; NEGRI, E.; FUMAGALLI, L. Review of digital twin applications in manufacturing. Computers in Industry, [s.l.], v. 113, p. 103130, dez. 2019. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S0166361519304385. Acesso em: 15 jul. 2023.

CRAN. The Comprehensive R Archive Network. 2023. Disponível em: https://cran.r-project.org. Acesso em: 17 ago. 2023.

DEKKER, R. Applications of maintenance optimization models: a review and analysis. Reliability Engineering & System Safety, [s.l.], v. 51, n. 3, p. 229–240, mar. 1996. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/0951832095000763. Acesso em: 31 jul. 2023.

ELLIS, L.; JOHNSON, R. Engine Maintenance Management Program Requires Information. SAE Technical Paper, [s.l.], 750613, 1975. Disponível em: https://www.sae.org/publications/technical-papers/content/750613/. Acesso em: 23 jun. 2023.

FERNANDEZ, O. et al. A decision support maintenance management system: Development and implementation. International Journal of Quality & Reliability Management, [s.l.], v. 20, n. 8, p. 965-979, 2003. Disponível em: https://www.emerald.com/insight/content/doi/10.1108/02656710310493652/full/html. Acesso em: 30 jul. 2023.

FOGLIATTO, F. S.; RIBEIRO, J. L. D. Confiabilidade e Manutenção Industrial. Rio de Janeiro: IDOC.PUB, [s.l.], 2009. Disponível em: https://idoc.pub/queue/confiabilidade-e-manutenao-industrialpdf-vnd5wjj7z9lx. Acesso em: 30 jul. 2023.

FRASER, K.; HVOLBY, H. H.; TSENG, T. L. (B) Maintenance management models: a study of the published literature to identify empirical evidence: A greater practical focus is needed. International Journal of Quality & Reliability Management, [s.l.], v. 32, n. 6, p. 635-664, 2015. Disponível em: https://doi.org/10.1108/IJQRM-11-2013-0185. Acesso em: 30 jul. 2023.

GARCÍA MÁRQUEZ, F. P. et al. Condition monitoring of wind turbines: Techniques and methods. Renewable Energy, [s.l.], v. 46, p. 169-178, out. 2012. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S0960148112001899?via%3Dihub. Acesso em: 10 jul. 2023

GARG, A.; DESHMUKH, S. G. Maintenance management: literature review and directions. Journal of Quality in Maintenance Engineering, [s.l.]v. 12, n. 3, p. 205–238, 1 jul. 2006.

GOEKING, W. Da máquina à vapor aos softwares de automação. O Setor Elétrico, p. 70-77, maio de 2010. Disponível em: https://www.voltimum.com.br/sites/www.voltimum.com.br/files/memoria_maio_10.pdf. Acesso em: 30 jul. 2023.

IEDI – INSTITUTO DE ESTUDOS PARA O DESENVOLVIMENTO INDUSTRIAL. Instituto de Estudos para o Desenvolvimento Industrial. Edição 968, 2019. Disponível em: https://iedi.org.br/cartas/carta_iedi_n_968.html. Acesso em 30 jul. 2023.

KARDEC, A.; NASCIF, J. Manutenção: função estratégica. 3. ed. rev. e ampliada. Rio de Janeiro: Qualymark, 2009.

LIMA; J. R. T. de; SANTOS, A. A. B.; SAMPAIO, R. R. Sistemas de Gestão da Manutenção – Uma Revisão Bibliográfica Visando Estabelecer Critérios para Avaliação de Maturidade. In: XXX ENCONTRO NACIONAL DE ENGENHARIA DE PRODUÇÃO, São Carlos, SP, Brasil. 12 a 15 out. 2010. Anais [...]. São Carlos, SP, 2010. Disponível em: http://repositoriosenaiba.fieb.org.br/bitstream/fieb/429/1/Sistemas%20de%20gest%C3%A3o%20....pdf. Acesso em: 30 jul. 2023.

MARTÍN-MARTÍN, A. et al. Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories. Journal of Informetrics, [s.l.], v. 12, n. 4, p. 1.160-1.177, nov. 2018. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S1751157718303249. Acesso em: 20 jul. 2023.

MARINELLI, I. Da preventiva à preditiva, a evolução da gestão da manutenção. Revista Manutenção, [s.l.], 1º jul. 2021. Disponível em: https://www.revistamanutencao.com.br/literatura/tecnica/manutencao/entenda-a-evolucao-da-manutencao-preditiva.html. Acesso em: 30 jul. 2023.

MONCHY, F. A Função Manutenção: formação para a gerência da manutenção industrial. São Paulo: Ebras Editora Brasileira Ltda., 1989.

MONTGOMERY, D. C.; RUNGER, G. C. Applied statistics and probability for engineers, 3. ed. New York, NY: John Wiley & Sons Inc., 2002.

MOREIRA, P. S. C.; GUIMARÃES, A. J. R.; TSUNODA, D. F. Qual ferramenta bibliométrica escolher? Um estudo de comparativo entre softwares. P2P & Inovação, [s.l.], v. 6, n. 2, p. 140-158, 2020. Disponível em: https://revista.ibict.br/p2p/article/view/5098. Acesso em: 20 jul. 2023.

MORTELARI, D.; SIQUEIRA, K.; PIZZATI, N. O RCM na quarta geração da manutenção de ativos. São Paulo: RG Editores, 2011.

NOVAK, D.; BATKO, M. Metric Index: An Efficient and Scalable Solution for Similarity Search. In: SECOND INTERNATIONAL WORKSHOP ON SIMILARITY SEARCH AND APPLICATIONS (SISAP). Prague, Czech Republic, ago. 2009. Anais [...]. Prague, Czech Republic, 2009. Disponível em: http://ieeexplore.ieee.org/document/5272384/. Acesso em: 30 out. 2022.

PAIS, E.; FARINHA, J. T.; RAPOSO, H. ISO 55001 – Gestão de Activos. In: 15o CONGRESSO NACIONAL DE MANUTENÇÃO, 21 e 22 de novembro de 2019, Altice Forum Braga. Braga, Portugal. Disponível em: https://www.researchgate.net/publication/339363909_ISO_55001_-_Gestao_de_Activos. Acesso em: Acesso em: 9 jul. 2023.

PESCHERINE, T. F. A Case Study in the Application of Integrated Maintenance Management to a Limited Development Program. In: IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, v. AES-2, n. 4, p. 271-280, July, 1966. Anais [...]. [S.l.], 1966. Disponível em: https://ieeexplore.ieee.org/document/4501850. Acesso em: 20 jun. 2023.

RAJORA, G. L.; SANZ-BOBI, M. A.; DOMINGO, C. M. Application of Machine Learning Methods for Asset Management on Power Distribution Networks. Emerging Science Journal, [s.l.], v. 6, n. 4, p. 905-920, 31 maio, 2022. Disponível em: https://www.researchgate.net/publication/361112378_Application_of_Machine_Learning_Methods_for_Asset_Management_on_Power_Distribution_Networks. Acesso em: 10 jul. 2023.

RAUSAND, M.; HØYLAND, A. System Reliability Theory: Models, Statistical Methods, and Applications. 2. ed. Nova York: John Wiley, 2003. 664p.

RÊGO, S. A. T. G.; SOUZA, L. M. D.; JUIZ, P. J. L. Análise Exploratória de Patentes Relacionadas a Softwares de Gestão Estratégica. Cadernos de Prospecção, Salvador, v. 11, n. 5, p. 1.765-1.774, dez. 2018. Disponível em: https://periodicos.ufba.br/index.php/nit/article/view/27622. Acesso em: 20 abr. 2024

SUSTO, G. A. et al. Machine Learning for Predictive Maintenance: A Multiple Classifier Approach. IEEE Transactions on Industrial Informatics, [s.l.], v. 11, n. 3, p. 812-820, jun. 2015. Disponível em: https://www.researchgate.net/publication/277723565_Machine_Learning_for_Predictive_Maintenance_A_Multiple_Classifier_Approach. Acesso em: 10 jul. 2023

SWANSON, L. Linking maintenance strategies to performance. International Journal of Production Economics, [s.l.], v. 70, n. 3, p. 237-244, abr. 2001. Disponível em: https://www.sciencedirect.com/science/article/abs/pii/S0925527300000670?via%3Dihub. Acesso em: 20 jun. 2023.

THOMAZ, P. G.; ASSAD, R. S.; MOREIRA, F. F. P. Uso do Fator de Impacto e do Índice H para Avaliar Pesquisadores e Publicações. Arquivos Brasileiros de Cardiologia, [s.l.], v. 96, n. 2, p. 90-93, 2011. Disponível em: http://www.scielo.br/pdf/abc/v96n2/v96n2a01.pdf. Acesso em: 10 ago. 2023.

TSANG, A. H. C. Strategic dimensions of maintenance management. Journal of Quality in Maintenance Engineering, [s.l.], v. 8, n. 1, p. 7-39, 1º mar. 2002. Disponível em: https://www.emerald.com/insight/content/doi/10.1108/13552510210420577/full/html. Acesso em: 28 jun. 2023.

VIANA, H. R. G. PCM: Planejamento e Controle da Manutenção. Rio de Janeiro: Qualitymark, 2002.

WU, D. et al. A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests. Journal of Manufacturing Science and Engineering, [s.l.], v. 139, n. 7, p. 071018, 1º jul. 2017. Disponível em: https://asmedigitalcollection.asme.org/manufacturingscience/article/139/7/071018/454654/A-Comparative-Study-on-Machine-Learning-Algorithms. Acesso em: 20 jun. 2023.

WIENKER, M.; HENDERSON, K.; VOLKERTS, J. The Computerized Maintenance Management System an Essential Tool for World Class Maintenance. Procedia Engineering, [s.l.], v. 138, p. 413-420, 2016. Disponível em: https://www.sciencedirect.com/science/article/pii/S1877705816004641?via%3Dihub. Acesso em: 25 jun. 2023.

YAM, R. C. M. et al. Intelligent Predictive Decision Support System for Condition-Based Maintenance. The International Journal of Advanced Manufacturing Technology, [s.l.], v. 17, n. 5, p. 383-391, 1º fev. 2001. Disponível em: https://link.springer.com/article/10.1007/s001700170173. Acesso em: 27 jul. 2023.

ZAMPOLLI, M. Gestão de Ativos: Guia para aplicação da norma ABNT NBR 55001 considerando as diretrizes da ISO 55002:2018. 2. ed. [S.l.]: International Copper Association Brazil, 2019. Disponível em: http://abcobre.org.br/wp-content/uploads/2021/06/gestao-de-ativos-guia-para-a-aplicacao-da-iso-55001.pdf. Acesso em: 9 jul. 2023.

Published

2024-07-01

How to Cite

Lisboa, O. M. de, Costa, J. M. da, & Lima, Ângela M. F. (2024). Bibliometric Analysis of Maintenance Management: from corrective to asset management. Cadernos De Prospecção, 17(3), 1025–1040. https://doi.org/10.9771/cp.v17i3.56602

Issue

Section

Prospecções Tecnológicas de Assuntos Específicos