ASSESSMENT OF EXTERNAL RELIABILITY DATA SOURCES AND RELIABILITY PREDICTIONS OF COMPLEX SYSTEMS IN EARLY SYSTEM DESIGN
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Authors
Kosempel, John W.
Subjects
reliability
external data sources
systems engineering
reliability prediction methods
reliability modeling
complex systems
design for reliability
early system design
physics of failure
reliability decision framework
preliminary design
external data sources
systems engineering
reliability prediction methods
reliability modeling
complex systems
design for reliability
early system design
physics of failure
reliability decision framework
preliminary design
Advisors
O'Halloran, Bryan M.
Date of Issue
2018-09
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
Two common reliability prediction methods are the traditional method and physics of failure method. Each method requires accurate failure data in order to fully assess a system’s durability. This is particularly important in early system design when historical design and relative failure rates are non-existent. Consequently, practitioners rely on the use of external reliability data sources such as MIL-HDBK-217F, especially when using the traditional reliability approach. Several other external reliability data sources are available to the practitioner, each with its own strengths and limitations. This thesis surveys the various external data sources industries use in reliability predictions and assesses the completeness of the reliability data sources. The thesis presents the inherent limitations of all external data sources along with further considerations on using the traditional reliability approach. Early system design offers practitioners a significant amount of decision-making flexibility. This thesis further analyzes both reliability approaches and addresses when it is appropriate for a practitioner to use either approach or a combination of the two approaches. The author develops a reliability decision framework to aid practitioners in selecting the reliability prediction approach appropriate for the system.
Type
Thesis
Description
Series/Report No
Department
Systems Engineering (SE)
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NPS Report Number
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Citation
Distribution Statement
Approved for public release; distribution is unlimited.
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Copyright is reserved by the copyright owner.