Applying association rules in the maintenance and reliability of physical systems: A review

Author:

Paiva Rafael G.N.ORCID,Cavalcante Cristiano A.V.,Do Phuc

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Coordination of Higher Education Personnel Improvement

Publisher

Elsevier BV

Reference71 articles.

1. Agrawal, R., & Srikant, R. (1994). Fast Algorithms for Mining Association Rules. Proc. of 20th International Conference on Very Large Data Bases, {VLDB’94}, 487–499. citeseer.ist.psu.edu/agrawal94fast.html.

2. Prediction of maintenance activities using generalized sequential pattern and association rules in data mining;Al-Refaie;Buildings,2023

3. A data mining framework for maintenance prediction of faulty products under warranty;Al-Refaie;Journal of Advanced Manufacturing Systems,2024

4. Defining a data-driven maintenance policy: An application to an oil refinery plant;Antomarioni;International Journal of Quality and Reliability Management,2019

5. Antomarioni, S., Bellinello, M. M., Bevilacqua, M., Ciarapica, F. E., Da Silva, R. F., & De Souza, G. F. M. (2020). A data-driven approach to extend failure analysis: A framework development and a case study on a hydroelectric power plant. Energies 13(23). https://doi.org/10.3390/en13236400.

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