Integrated Diagnostics and Time to Maintenance Estimation for Complex Engineering Systems
Authors
Azam, Mohammad
Ghoshal, Sudipto
Deb, Somnath
Pattipati, Krishna
Haste, Deepak
Mandal, Suvasri
Kleinman, David
Advisors
Second Readers
Subjects
Date of Issue
2014
Date
Publisher
IEEE
Language
Abstract
Prognostics and Health Management (PHM) [1] is a
key enabler of Condition Based Maintenance Plus (CBM+) [2].
In essence, it refers to the “Plus” by providing the ability to
predict future health status of a system or component, as well
as providing the ability to anticipate faults, problems, potential
failures, and required maintenance actions. From the
perspective of operation and maintenance (O&M) world, the
vital knowledge requirements from PHM are indicators of
degraded health condition (alarm, warnings, call for
inspection, etc.), estimates of time to onset of such indicators,
estimate of time to maintenance, and ahead-of-time diagnostics
for identification of the root causes (or sources) that will likely
cause these maintenance calls. Such knowledge provides lead
time to the operators and system maintainers to prepare for
inspection and schedule maintenance opportunistically, so as to
minimize downtime and optimize maintenance cost.
Type
Article
Description
Proceedings IEEE Aerospace Conference, Big Sky, MT (2014). This paper was also presented at the conference by D. Kleinman.
Series/Report No
Department
Information Sciences (IS)
Organization
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NPS Report Number
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Citation
Azam, M., Ghoshal, S., Deb, S., Pattitpatti, K., Haste, D., Mandal, S. and Kleinman, D., "Integrated Diagnostics and Time to Maintenance for Complex Engineering Systems," Proceedings IEEE Aerospace Conference, Big Sky, MT (2014). This paper was also presented at the conference by D. Kleinman.
Distribution Statement
Rights
This 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.
