DocumentCode :
3234881
Title :
Intelligent Diagnostic Reasoning System deployment process and results
Author :
Cosgriff, Pat ; Harris, Michelle ; Helton, Alicia
Author_Institution :
Ogden Air Logistics Center, Ogden, UT
fYear :
2008
fDate :
8-11 Sept. 2008
Firstpage :
154
Lastpage :
158
Abstract :
Lockheed Martin Simulation, Training & Support (LM STS) has developed an Intelligent Diagnostic Reasoning System (IDRS) that can reduce the time and cost to diagnose a failure by isolating to the fault more quickly and reducing callout ambiguity. IDRS uses engineering knowledge and historical test and maintenance data to develop diagnostic models enabling intelligent decision support. IDRS models and services are based on the IEEE 1232trade Artificial Intelligence Exchange and Service Tie to All Test Environment (AI-ESTATE) standard. IDRS is deployed at Ogden Air Logistics Center (OO-ALC) through a partnership between LM STS and OO-ALC 309th Maintenance Wing (309 MXW) Software Maintenance Group and Electronics Maintenance Group at Hill Air Force Base. This paper will outline the selection of the Line Replaceable Unit (LRU), the deployment of IDRS, the results obtained, and the benefits of IDRS.
Keywords :
automatic test equipment; decision support systems; fault diagnosis; military computing; 309 MXW Software Maintenance Group; AI-ESTATE standard; Electronics Maintenance Group; Hill Air Force Base; IDRS models; IDRS services; IEEE 1232 Artificial Intelligence Exchange and Service Tie to All Test Environment; LM STS; Lockheed Martin Simulation Training & Support; OO-ALC 309th Maintenance Wing; Ogden Air Logistics Center; callout ambiguity; diagnostic models; engineering knowledge; failure diagnosis; historical test; intelligent decision support; intelligent diagnostic reasoning system deployment process; line replaceable unit; maintenance data; Artificial intelligence; Automatic testing; Bayesian methods; Costs; Electronic equipment testing; Intelligent systems; Logistics; Sociotechnical systems; Software maintenance; System testing; AI-ESTATE; Bayesian;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
AUTOTESTCON, 2008 IEEE
Conference_Location :
Salt Lake Cirty, UT
ISSN :
1088-7725
Print_ISBN :
978-1-4244-2225-8
Electronic_ISBN :
1088-7725
Type :
conf
DOI :
10.1109/AUTEST.2008.4662603
Filename :
4662603
Link To Document :
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