RUcore Resource Object
RUcore Resource Object
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TitleFlexible modeling and simulating mission availability within the operational framework for Canadian Naval platforms
NameKoshman, Scott (author), Coit, David (chair), Elsayed, Elsayed (internal member), Luxhoj, James (internal member), Rutgers University, Graduate School - New Brunswick,
Degree Date2011-05
Date Created2011
SubjectIndustrial and Systems Engineering,
Preparedness,
Canada. Royal Canadian Navy
DescriptionAvailability and reliability metrics have become key in-service performance measures in Canadian defence contracting. Previous implementations have evolved due to challenges in application, and were focused on the Air Force operational environment. With ongoing capital procurement and in-service support contracting, the Navy requires a definition and method of assessing availability appropriate to Naval platforms. Naval ships are multi-role multi-function platforms. Traditional single function availability metrics are ambiguous for multiple functions / capabilities. Critical systems (e.g. propulsion, power) have an obvious effect on availability, while the loss of other functions (e.g. radar) do not. Non-critical system and capability impact is a function of the requirements of the current mission, thus mission availability must be evaluated. Mission availability for a multi-function platform was defined as the interval average evaluation of critical system availability, mean capability availability, and mean weighted performance availability. The latter linked engineering performance to expected operational performance. Mission Capability Configuration Reliability Model was introduced to link system performance to capability performance. Using this model, an availability simulation, incorporating failure, maintenance, and logistical models was developed to assess mission availability. The simulation was applied to the project management functions of ship design and specification prototyping, availability assessment for contract management, and in-service performance prediction.
NoteM.S.
NoteIncludes bibliographical references
Noteby Scott Cameron Daniel Koshman
Genretheses
Persistent URLhttp://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061320
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.