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dc.contributor.authorMillar, Richard C.
dc.contributor.authorMazzuchi, Thomas Andrew
dc.contributor.authorSarkani, Shahram
dc.date.accessioned2014-10-08T23:14:51Z
dc.date.available2014-10-08T23:14:51Z
dc.date.issued2009
dc.identifier.citationNaval Engineers Journal
dc.identifier.urihttps://hdl.handle.net/10945/43486
dc.descriptionThe article of record as published may be located at http://dx.doi.org/10.1111/j.1559-3584.2009.00195.xen_US
dc.description.abstractThis paper reports the results of applying lifetime (or reliability database) statistical analysis methods to engine removal data recorded over the initial 8 years’ service of the General Electric F414-GE-400 turbofan engines propelling the F/A-18 E/F Super Hornet in service with the US Navy, with the intent of better understanding the reasons for engine removal and their impact on engine time on wing (TOW), and to gain an insight into the reliability of the modules and components from which the engine is assembled. It was found that ‘‘coloring’’ the engine removals into three classes of reasons for removal enabled lifetime data analysis revealing interesting and useful features of in-service engine reliability. Nonparametric statistical analysis provided actionable information on engine removal probability as a function of TOW and removal cause that should be applicable to planning flight operations, line maintenance, and support logistics. The analysis of engine removals due to hot section distress appears to disconfirm the presumption of independence between the three classes of removal. Opportunistic maintenance of modules made accessible due to engine removals to service other modules may significantly affect the observed engine removal distribution of the module of interest, i.e., competing risk masks the underlying module hazard functions.en_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleNonparametric Statistical Analysis of the Reliability of a Naval Aviation Propulsion Systemen_US
dc.typeArticleen_US
dc.contributor.departmentSystems Engineering


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