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Optimisation of Maintenance Policies Based on Right-Censored Failure Data Using a Semi-Markovian Approach
This paper exposes the existing problems for optimal industrial preventive maintenance intervals when decisions are made with right-censored data obtained from a network of sensors or other sources. A methodology based on the use of the z transform and a semi-Markovian approach is presented to solve...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8875710/ https://www.ncbi.nlm.nih.gov/pubmed/35214334 http://dx.doi.org/10.3390/s22041432 |
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author | Sánchez-Herguedas, Antonio Mena-Nieto, Angel Rodrigo-Muñoz, Francisco Villalba-Díez, Javier Ordieres-Meré, Joaquín |
author_facet | Sánchez-Herguedas, Antonio Mena-Nieto, Angel Rodrigo-Muñoz, Francisco Villalba-Díez, Javier Ordieres-Meré, Joaquín |
author_sort | Sánchez-Herguedas, Antonio |
collection | PubMed |
description | This paper exposes the existing problems for optimal industrial preventive maintenance intervals when decisions are made with right-censored data obtained from a network of sensors or other sources. A methodology based on the use of the z transform and a semi-Markovian approach is presented to solve these problems and obtain a much more consistent mathematical solution. This methodology is applied to a real case study of the maintenance of large marine engines of vessels dedicated to coastal surveillance in Spain to illustrate its usefulness. It is shown that the use of right-censored failure data significantly decreases the value of the optimal preventive interval calculated by the model. In addition, that optimal preventive interval increases as we consider older failure data. In sum, applying the proposed methodology, the maintenance manager can modify the preventive maintenance interval, obtaining a noticeable economic improvement. The results obtained are relevant, regardless of the number of data considered, provided that data are available with a duration of at least 75% of the value of the preventive interval. |
format | Online Article Text |
id | pubmed-8875710 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88757102022-02-26 Optimisation of Maintenance Policies Based on Right-Censored Failure Data Using a Semi-Markovian Approach Sánchez-Herguedas, Antonio Mena-Nieto, Angel Rodrigo-Muñoz, Francisco Villalba-Díez, Javier Ordieres-Meré, Joaquín Sensors (Basel) Article This paper exposes the existing problems for optimal industrial preventive maintenance intervals when decisions are made with right-censored data obtained from a network of sensors or other sources. A methodology based on the use of the z transform and a semi-Markovian approach is presented to solve these problems and obtain a much more consistent mathematical solution. This methodology is applied to a real case study of the maintenance of large marine engines of vessels dedicated to coastal surveillance in Spain to illustrate its usefulness. It is shown that the use of right-censored failure data significantly decreases the value of the optimal preventive interval calculated by the model. In addition, that optimal preventive interval increases as we consider older failure data. In sum, applying the proposed methodology, the maintenance manager can modify the preventive maintenance interval, obtaining a noticeable economic improvement. The results obtained are relevant, regardless of the number of data considered, provided that data are available with a duration of at least 75% of the value of the preventive interval. MDPI 2022-02-13 /pmc/articles/PMC8875710/ /pubmed/35214334 http://dx.doi.org/10.3390/s22041432 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Sánchez-Herguedas, Antonio Mena-Nieto, Angel Rodrigo-Muñoz, Francisco Villalba-Díez, Javier Ordieres-Meré, Joaquín Optimisation of Maintenance Policies Based on Right-Censored Failure Data Using a Semi-Markovian Approach |
title | Optimisation of Maintenance Policies Based on Right-Censored Failure Data Using a Semi-Markovian Approach |
title_full | Optimisation of Maintenance Policies Based on Right-Censored Failure Data Using a Semi-Markovian Approach |
title_fullStr | Optimisation of Maintenance Policies Based on Right-Censored Failure Data Using a Semi-Markovian Approach |
title_full_unstemmed | Optimisation of Maintenance Policies Based on Right-Censored Failure Data Using a Semi-Markovian Approach |
title_short | Optimisation of Maintenance Policies Based on Right-Censored Failure Data Using a Semi-Markovian Approach |
title_sort | optimisation of maintenance policies based on right-censored failure data using a semi-markovian approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8875710/ https://www.ncbi.nlm.nih.gov/pubmed/35214334 http://dx.doi.org/10.3390/s22041432 |
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