System-level health assessment of complex engineered processes

Condition-Based Maintenance (CBM) and Prognostics and Health Management (PHM) technologies aim at improving the availability, reliability, maintainability, and safety of systems through the development of fault diagnostic and failure prognostic algorithms. In complex engineering systems, such as air...

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Main Author: Abbas, Manzar
Published: Georgia Institute of Technology 2011
Subjects:
Online Access:http://hdl.handle.net/1853/37260
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spelling ndltd-GATECH-oai-smartech.gatech.edu-1853-372602015-06-10T03:38:05ZSystem-level health assessment of complex engineered processesAbbas, ManzarFault diagnosticsFailure prognosticsResponse surface metamodelsCondition-based maintenance (CBM)Design of experiments (DOE)Prognostics and health management (PHM)System-levelSystems engineeringCondition-Based Maintenance (CBM) and Prognostics and Health Management (PHM) technologies aim at improving the availability, reliability, maintainability, and safety of systems through the development of fault diagnostic and failure prognostic algorithms. In complex engineering systems, such as aircraft, power plants, etc., the prognostic activities have been limited to the component-level, primarily due to the complexity of large-scale engineering systems. However, the output of these prognostic algorithms can be practically useful for the system managers, operators, or maintenance personnel, only if it helps them in making decisions, which are based on system-level parameters. Therefore, there is an emerging need to build health assessment methodologies at the system-level. This research employs techniques from the field of design-of-experiments to build response surface metamodels at the system-level that are built on the foundations provided by component-level damage models.Georgia Institute of Technology2011-03-04T21:02:14Z2011-03-04T21:02:14Z2010-11-18Dissertationhttp://hdl.handle.net/1853/37260
collection NDLTD
sources NDLTD
topic Fault diagnostics
Failure prognostics
Response surface metamodels
Condition-based maintenance (CBM)
Design of experiments (DOE)
Prognostics and health management (PHM)
System-level
Systems engineering
spellingShingle Fault diagnostics
Failure prognostics
Response surface metamodels
Condition-based maintenance (CBM)
Design of experiments (DOE)
Prognostics and health management (PHM)
System-level
Systems engineering
Abbas, Manzar
System-level health assessment of complex engineered processes
description Condition-Based Maintenance (CBM) and Prognostics and Health Management (PHM) technologies aim at improving the availability, reliability, maintainability, and safety of systems through the development of fault diagnostic and failure prognostic algorithms. In complex engineering systems, such as aircraft, power plants, etc., the prognostic activities have been limited to the component-level, primarily due to the complexity of large-scale engineering systems. However, the output of these prognostic algorithms can be practically useful for the system managers, operators, or maintenance personnel, only if it helps them in making decisions, which are based on system-level parameters. Therefore, there is an emerging need to build health assessment methodologies at the system-level. This research employs techniques from the field of design-of-experiments to build response surface metamodels at the system-level that are built on the foundations provided by component-level damage models.
author Abbas, Manzar
author_facet Abbas, Manzar
author_sort Abbas, Manzar
title System-level health assessment of complex engineered processes
title_short System-level health assessment of complex engineered processes
title_full System-level health assessment of complex engineered processes
title_fullStr System-level health assessment of complex engineered processes
title_full_unstemmed System-level health assessment of complex engineered processes
title_sort system-level health assessment of complex engineered processes
publisher Georgia Institute of Technology
publishDate 2011
url http://hdl.handle.net/1853/37260
work_keys_str_mv AT abbasmanzar systemlevelhealthassessmentofcomplexengineeredprocesses
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