@inproceedings{atamuradov_failure_2009,
	title = {Failure diagnostics for railway point machines using expert systems},
	doi = {10.1109/DEMPED.2009.5292755},
	abstract = {Maintenance is an inevitable reality in industry. Maintenance of a system usually involves maintenance of multiple components with multiple failure modes, each of which may require different maintenance policy (i.e., corrective (CM), preventive (PM), or condition based maintenance (CBM)). A maintenance policy may be best for one component and the worst for the other (CM may be best for a very cheap and non-critical component and the worst for a critical one). This paper presents an economical analysis method that identifies the best maintenance policy for a failure mode and/or component of a system.},
	booktitle = {2009 {IEEE} {International} {Symposium} on {Diagnostics} for {Electric} {Machines}, {Power} {Electronics} and {Drives}},
	author = {Atamuradov, V. and Camci, F. and Baskan, S. and Sevkli, M.},
	month = aug,
	year = {2009},
	keywords = {Clustering algorithms, Control systems, Diagnostic expert systems, Diagnostics, Expert Systems, Fault diagnosis, Phase measurement, Rail transportation, Railway Turnouts, Remote monitoring, Signal analysis, Smoothing methods, Time Series Analysis, Time series analysis},
	pages = {1--5},
}

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