Neural Networks and Genetic Algorithms applied to the Maintenance Process in an ATM Network

L. Calle-Sarmiento; J. Bermeo-Moyano; Jose Ignacio Castillo-Velazquez; Germania Vayas

doi:10.1109/ETCM56276.2022.9935754

Neural Networks and Genetic Algorithms applied to the Maintenance Process in an ATM Network

L. Calle-Sarmiento, J. Bermeo-Moyano, Jose Ignacio Castillo-Velazquez, Germania Vayas

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The optimization of infrastructure maintenance costs in Automated Teller Machine networks of financial institutions is a huge problem faced through business intelligence as artificial intelligence for decision-making. This paper addresses the issue to optimize costs through the application of systems with artificial intelligence. So, neural networks were applied to predict ATM failures based on the historical information of specified errors, number and amounts of transactions. Then forecasting was used to determinate failures, after, the optimal maintenance route that the technical personnel must travel was determined by means of a genetic algorithm. Finally, it was estimated that the reduction of maintenance costs when applying the proposed predictive maintenance methodology is around 200,000 USD for an ATM network of 500 devices of a financial institution in Ecuador.

Original language	English
Title of host publication	6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022
Editors	David Rivas Lalaleo, Monica Karel Huerta
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665487443
DOIs	https://doi.org/10.1109/ETCM56276.2022.9935754
State	Published - 2022
Event	6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022 - Quito, Ecuador Duration: 11 Oct 2022 → 14 Oct 2022

Publication series

Name	6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022

Conference

Conference	6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022
Country/Territory	Ecuador
City	Quito
Period	11/10/22 → 14/10/22

Bibliographical note

Funding Information:
This research was funded by projects CYTED 788 [REDTPI4.0-320RT0006], PLAGRI project by Telecommunications and Telematics Research Group (GITEL) from Uni-versidad Politécnica Salesiana, Cuenca, Ecuador.

Publisher Copyright:
© 2022 IEEE.

Keywords

ATM
Business Intelligence
Genetic Algorithm
Neural Networks
Predictive Maintenance

Access to Document

10.1109/ETCM56276.2022.9935754

Cite this

Calle-Sarmiento, L., Bermeo-Moyano, J., Castillo-Velazquez, J. I., & Vayas, G. (2022). Neural Networks and Genetic Algorithms applied to the Maintenance Process in an ATM Network. In D. R. Lalaleo, & M. K. Huerta (Eds.), 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022 (6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ETCM56276.2022.9935754

Calle-Sarmiento, L. ; Bermeo-Moyano, J. ; Castillo-Velazquez, Jose Ignacio et al. / Neural Networks and Genetic Algorithms applied to the Maintenance Process in an ATM Network. 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022. editor / David Rivas Lalaleo ; Monica Karel Huerta. Institute of Electrical and Electronics Engineers Inc., 2022. (6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022).

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title = "Neural Networks and Genetic Algorithms applied to the Maintenance Process in an ATM Network",

abstract = "The optimization of infrastructure maintenance costs in Automated Teller Machine networks of financial institutions is a huge problem faced through business intelligence as artificial intelligence for decision-making. This paper addresses the issue to optimize costs through the application of systems with artificial intelligence. So, neural networks were applied to predict ATM failures based on the historical information of specified errors, number and amounts of transactions. Then forecasting was used to determinate failures, after, the optimal maintenance route that the technical personnel must travel was determined by means of a genetic algorithm. Finally, it was estimated that the reduction of maintenance costs when applying the proposed predictive maintenance methodology is around 200,000 USD for an ATM network of 500 devices of a financial institution in Ecuador.",

keywords = "ATM, Business Intelligence, Genetic Algorithm, Neural Networks, Predictive Maintenance",

author = "L. Calle-Sarmiento and J. Bermeo-Moyano and Castillo-Velazquez, {Jose Ignacio} and Germania Vayas",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022 ; Conference date: 11-10-2022 Through 14-10-2022",

year = "2022",

doi = "10.1109/ETCM56276.2022.9935754",

language = "English",

series = "6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022",

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Calle-Sarmiento, L, Bermeo-Moyano, J, Castillo-Velazquez, JI & Vayas, G 2022, Neural Networks and Genetic Algorithms applied to the Maintenance Process in an ATM Network. in DR Lalaleo & MK Huerta (eds), 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022. 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022, Institute of Electrical and Electronics Engineers Inc., 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022, Quito, Ecuador, 11/10/22. https://doi.org/10.1109/ETCM56276.2022.9935754

Neural Networks and Genetic Algorithms applied to the Maintenance Process in an ATM Network. / Calle-Sarmiento, L.; Bermeo-Moyano, J.; Castillo-Velazquez, Jose Ignacio et al.
6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022. ed. / David Rivas Lalaleo; Monica Karel Huerta. Institute of Electrical and Electronics Engineers Inc., 2022. (6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - The optimization of infrastructure maintenance costs in Automated Teller Machine networks of financial institutions is a huge problem faced through business intelligence as artificial intelligence for decision-making. This paper addresses the issue to optimize costs through the application of systems with artificial intelligence. So, neural networks were applied to predict ATM failures based on the historical information of specified errors, number and amounts of transactions. Then forecasting was used to determinate failures, after, the optimal maintenance route that the technical personnel must travel was determined by means of a genetic algorithm. Finally, it was estimated that the reduction of maintenance costs when applying the proposed predictive maintenance methodology is around 200,000 USD for an ATM network of 500 devices of a financial institution in Ecuador.

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Calle-Sarmiento L, Bermeo-Moyano J, Castillo-Velazquez JI, Vayas G. Neural Networks and Genetic Algorithms applied to the Maintenance Process in an ATM Network. In Lalaleo DR, Huerta MK, editors, 6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022. Institute of Electrical and Electronics Engineers Inc. 2022. (6th IEEE Ecuador Technical Chapters Meeting, ETCM 2022). doi: 10.1109/ETCM56276.2022.9935754

Neural Networks and Genetic Algorithms applied to the Maintenance Process in an ATM Network

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