Using operational data for decision making a feasibility study in rail maintenance

Date

2016-05-01

Author

Marsh, William
Nur, Khalid
Yet, Barbaros
Majumdar, Arnab

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

99
views

0
downloads

In many organisations, large databases are created as part of the business operation: the promise of ‘big data’ is to extract information from these databases to make smarter decisions. We explore the feasibility of this approach for better decision-making for maintenance, specifically for rail infrastructure. We argue that the data should be used within a Bayesian framework with the aim of inferring the underlying state of the system so we can predict future failures and improve decision-making. Within this framework, some data is diagnostic of this underlying state and other data have a causal influence. The framework can be realised as a Bayesian network and the probabilistic relationships in this network can be learnt from data. However, the network cannot be created just from data; instead experts’ knowledge is vital for the model’s structure as some variables representing the underlying state of the system may not be present in the data. We outline an architecture for a smart decision tool and show that the GB railway industry has the data needed. The challenges of developing such a tool are also discussed. For example, the required data are distributed across multiple databases and both within and between these databases important relationships, such as physical proximity, may not be represented explicitly.

Subject Keywords

Railway maintenance, Bayesian networks, Decision making

URI

https://hdl.handle.net/11511/58044

Journal

Safety and Reliability

DOI

https://doi.org/10.1080/09617353.2016.1148923

Collections

Graduate School of Informatics, Article

Suggestions

OpenMETU
Core

A Decision Support System for Optimal Selection of Enterprise Information Security Preventative Actions Sonmez, Ferda Ozdemir; Günel Kılıç, Banu (2021-09-01) Types and complexity of information security related vulnerabilities are growing rapidly and present numerous challenges to the enterprises. One of the key challenges is to identify the optimal set of precautions with limited budget. Despite the fact that majority of enterprises have a budget constraint for installing and maintaining the protection systems, the majority of the previous work only focus on prioritization of security targets and do not consider the preventative actions and budget constraints. ...
Building Bayesian networks based on DEMATEL for multiple criteria decision problems: A supplier selection case study Kaya, Rukiye; Yet, Barbaros (2019-11-01) Bayesian Networks (BNs) are effective tools for providing decision support based on expert knowledge in uncertain and complex environments. However, building knowledge-based BNs is still a difficult task that lacks systematic and widely accepted methodologies, especially when knowledge is elicited from multiple experts. We propose a novel method that systematically integrates a widely used Multi Criteria Decision Making (MCDM) approach called Decision Making Trial and Evaluation Laboratory (DEMATEL) in BN c...
Secure logical schema and decomposition algorithm for proactive context dependent attribute based inference control Turan, Ugur; Toroslu, İsmail Hakkı; Kantarcioglu, Murat (2017-09-01) Inference problem has always been an important and challenging topic of data privacy in databases. In relational databases, the traditional solution to this problem was to define views on relational schemas to restrict the subset of attributes and operations available to the users in order to prevent unwanted inferences. This method is a form of decomposition strategy, which mainly concentrates on the granularity of the accessible fields to the users, to prevent sensitive information inference. Nowadays, du...
Optimization of an online course with web usage mining Akman, LE; Akkan, B; Baykal, Nazife (2004-02-18) The huge amount of information existing in the World Wide Web constitutes an ideal environment to implement data mining techniques. Web mining is the mining of web data. There are different applications of web mining: web content mining, web structure mining and web usage mining. In our study we analyzed an online course by web usage mining techniques in order to optimize the navigation paths, the duration of the time spend on each page and the number of visits throughout the semester of the course. Moreove...
Utilisation of Decision Support Systems in Construction Management: A Literature Survey Günay, Göksu ; Pekeriçli, Mehmet Koray (2020-11-12) Today, computers are widely used in all industries for data collection and analysis, interpretation of data and decision making processes. Especially Decision Support Systems, which are computer-based Information Systems providing tools for assisting managers in making semi-structured decisions, have gained stronger ground parallel to the latest developments in information technologies including artificial intelligence applications like fuzzy logic, machine learning, natural langu...

Citation Formats

W. Marsh, K. Nur, B. Yet, and A. Majumdar, “Using operational data for decision making a feasibility study in rail maintenance,” Safety and Reliability, pp. 35–47, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/58044.