Template:WebNotes/RGACrow AMSAA Fleet: Difference between revisions
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Fleet analysis is similar to repairable systems analysis, except the fleet of systems is considered and the models are applied to the fleet failures rather than to the system failures. In other words, repairable systems analysis models the number of system failures versus system time, whereas fleet analysis models the number of fleet failures versus fleet time. The Crow-AMSAA model for fleet data can be used as an alternative to the power law model for repairable systems when | Fleet analysis is similar to repairable systems analysis, except the fleet of systems is considered, and the models are applied to the fleet failures rather than to the system failures. In other words, repairable systems analysis models the number of system failures versus system time, whereas fleet analysis models the number of fleet failures versus fleet time. The Crow-AMSAA model for fleet data can be used as an alternative to the power law model for repairable systems when the latter does not provide a good fit for the data. | ||
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| [http://help.synthesisplatform.net/rga9/repairable_systems_analysis.htm | | [http://help.synthesisplatform.net/rga9/index.htm#repairable_systems_analysis.htm V9 Help] or [http://help.synthesisplatform.net/rga10/index.htm#repairable_systems_analysis.htm V10 Help] | ||
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| [http://reliawiki.com/index.php/ | | [http://reliawiki.com/index.php/Fleet_Analysis_Articles related article(s)...] | ||
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Latest revision as of 23:09, 23 April 2015
Crow-AMSAA Model for Fleet Data
Fleet analysis is similar to repairable systems analysis, except the fleet of systems is considered, and the models are applied to the fleet failures rather than to the system failures. In other words, repairable systems analysis models the number of system failures versus system time, whereas fleet analysis models the number of fleet failures versus fleet time. The Crow-AMSAA model for fleet data can be used as an alternative to the power law model for repairable systems when the latter does not provide a good fit for the data. |
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