Applying RCM in large scale systems: a case study with railway networks

Carretero, Jesús; Perez, J.M.; Garcı́a-Carballeira, Félix; Calderón, Alejandro; Fernández, Julia Martínez; García, Juan Carlos Figueroa; Lozano, Antonio; Cardona, Luis Felipe; Cotaina, N.; Prete, Pierre

doi:10.1016/s0951-8320(03)00167-4

Cited by 93 publications

(51 citation statements)

References 6 publications

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“…those elements whose p-value for the corresponding test is lower that lim 1 , with yellow (light grey in the print version) the possible warnings, i.e. those elements with p-value in the interval [lim 1 , lim 2 ] and with green (intermediate grey in the print version) those elements for which there is no warning as their p-value is higher than lim 2 .…”

Section: Warning Proceduresmentioning

confidence: 99%

“…The accumulated number of failures in October is too high for that estimated failure intensity, and therefore the procedure issues a warning. 1 and lim 2 , the procedure will only give a warning when the case is far beyond doubt (usually too far). In Figure 4(b) we have used lim 1 = 0.001 and lim 2 = 0.005.…”

Section: Warning Proceduresmentioning

confidence: 99%

“…Our industrial partners in this work have obviously been the staff of the electrical department at Spanish railways, where a lot of work is being done with the aim of improving the whole network performance using RCM techniques. Two interesting references in this field are Carretero et al 1 and García-Escudero et al 2 . The network has quite a large number of systems (about 50), and each of them has an enormous number of components spread over the whole Spanish territory.…”

Section: Introductionmentioning

confidence: 99%

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Warning procedures for systems that are improving

García-Escudero

Fernández

Duque

et al. 2007

Quality & Reliability Eng

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Nowadays it is quite usual that systems are correctly maintained. This leads to a decreasing number of failures for the system. In this paper we discuss how to establish warning procedures that take into account features giving the chance of detecting eventual changes of trend in the systems and allowing taking measures before too much damage has actually happened. The proposed procedure is applied to the study of the reliability and maintenance of the railway electric supply system. In this kind of systems, complex and extended, testing the performance of the system and effectiveness of the maintenance tasks has special interest.

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Section: Warning Proceduresmentioning

confidence: 99%

Section: Warning Proceduresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Warning procedures for systems that are improving

García-Escudero

Fernández

Duque

et al. 2007

Quality & Reliability Eng

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“…The objective must be to find the most critical use cases without evaluating criticality for every use case of the system. In such cases, having a structured use case model may help by allowing the application of the criticality inheritance concept [23].…”

Section: Use Case Levels and Criticality Analysismentioning

confidence: 99%

Specifying use case behavior with interaction models.

García

Carretero

Perez

et al. 2005

JOT

Self Cite

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Functional requirements for information systems can be modeled through use cases. Furthermore, use case models have been successfully used in broader contexts than software engineering, as systems engineering. Even if small systems may be modeled as a set of use cases, when large systems requirements are modeled with a plain use case model several difficulties arise. Traditionally, the behavior of use cases has been modeled through textual specifications. In this paper we present an alternate approach based on interaction modeling. The behavior modeling has two variants (one for UML 1.x and one for UML 2.0). We also integrate our behavior modeling with standard use case relationships.

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“…The Criticality Measures Carretero et al (2003) applied the Reliability Centered Maintenance (RCM) methodology in railway infrastructures through the project "RAIL: Reliability centered maintenance Approach for the Infrastructure and Logistics of railway operation". In this project, the criticality of a system was introduced as the measure of a system importance from a functional point of view.…”

Section: Introductionmentioning

confidence: 99%

Criticality-Based Model for Rehabilitating Subway Stations

Abouhamad¹,

Zayed²

2013

Proceedings of the 30th International Symposium on Automation and Robotics in Construction and Mining (ISARC 2013): Building Th

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According to the Canadian Urban Transit Association (CUTA), 140 Billion CAD is required to maintain, rehabilitate, and replace subway infrastructure between 2010 and 2014. The current practice adopted by transit authorities for prioritizing subway stations for rehabilitation is based on the station structural needs. While this classification is reflective of station condition, other factors, such as station size, location and passenger capacity, play an important role. The criticality of a station is an index that represents the functional importance of a station depending upon a set of identified factors. The system criticality is based on several attributes, such as station location, size, and nature of use. This paper presents a novel method of clustering subway stations for rehabilitation priority based on their criticality level. The different stations in a subway network are rated according to their relative importance against predefined attributes. The weights and scores of the attributes are computed with the help of experts and current subway network data. The analysis is done using the Fuzzy Analytic Network Process (FANP) to accommodate the subjectivity of human judgment as being expressed in natural language which entails 'fuzziness' in real-life problems and account for the interdependency between the selected attributes. The output of the model is a criticality based clustering of subway stations. The proposed framework helps authorities prioritize stations for rehabilitation and highlight stations with more criticality for a more robust asset analysis.

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Applying RCM in large scale systems: a case study with railway networks

Cited by 93 publications

References 6 publications

Warning procedures for systems that are improving

Warning procedures for systems that are improving

Specifying use case behavior with interaction models.

Criticality-Based Model for Rehabilitating Subway Stations

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