DocumentCode :
1949479
Title :
System Self Diagnosis for industrial devices
Author :
Rentschler, Markus ; Kehrer, Stephan ; Zangl, Clemens Pirmin
Author_Institution :
Hirschmann Autom. & Control GmbH, Neckartenzlingen, Germany
fYear :
2013
fDate :
10-13 Sept. 2013
Firstpage :
1
Lastpage :
8
Abstract :
Downtimes of failed devices in an industrial plant must be kept to a minimum to achieve high system availability. Since failures are often caused by transient hardware- or software faults, a well-defined System Self Diagnosis (SSD) functionality is an important feature for the effective long-term operation of industrial plants. To achieve effective SSD techniques for network infrastructure devices, a root cause analysis of past failures was conducted and a fault model derived. A set of error detection methods was derived based on the checked root cause indicators. For productive deployment, an extensible SSD framework in form of a rule based system was designed and implemented to be used as an embedded software tool throughout the whole product lifecycle of an industrial device, achieving a highly efficient “Design for Testability” approach.
Keywords :
condition monitoring; design for testability; fault diagnosis; knowledge based systems; product life cycle management; production engineering computing; SSD functionality; checked root cause indicator; design for testability approach; embedded software tool; error detection method; extensible SSD framework; industrial device; industrial plant; network infrastructure device; product lifecycle; productive deployment; root cause analysis; rule based system; software fault; system self diagnosis; transient hardware fault; Decision support systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Emerging Technologies & Factory Automation (ETFA), 2013 IEEE 18th Conference on
Conference_Location :
Cagliari
ISSN :
1946-0740
Print_ISBN :
978-1-4799-0862-2
Type :
conf
DOI :
10.1109/ETFA.2013.6648019
Filename :
6648019
Link To Document :
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