Failure modes, effects and criticality analysis (FMECA) of power electronic devices using fuzzy logic

Dialynas, EN; Zafiropoulos, EP

dc.contributor.author	Dialynas, EN	en
dc.contributor.author	Zafiropoulos, EP	en
dc.date.accessioned	2014-03-01T02:43:20Z
dc.date.available	2014-03-01T02:43:20Z
dc.date.issued	2005	en
dc.identifier.issn	1472-8915	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31335
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-23144451179&partnerID=40&md5=4bdac9801ac00b1446fe161cb9c1dc8b	en
dc.subject	Failure Modes Effects and Criticality Analysis	en
dc.subject	Fuzzy Inference	en
dc.subject	Fuzzy Sets	en
dc.subject	Knowledge Base	en
dc.subject	Power Electronic Devices	en
dc.subject	Reliability Assessment	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Electronic equipment	en
dc.subject.other	Fuzzy sets	en
dc.subject.other	Membership functions	en
dc.subject.other	Power electronics	en
dc.subject.other	Probability	en
dc.subject.other	Problem solving	en
dc.subject.other	Reliability	en
dc.subject.other	Spreadsheets	en
dc.subject.other	Failure modes effects and criticality analysis (FMECA)	en
dc.subject.other	Fuzzy inference	en
dc.subject.other	Knowledge base	en
dc.subject.other	Power electronic devices	en
dc.subject.other	Reliability assessment	en
dc.subject.other	Failure analysis	en
dc.title	Failure modes, effects and criticality analysis (FMECA) of power electronic devices using fuzzy logic	en
heal.type	conferenceItem	en
heal.language	English	en
heal.publicationDate	2005	en
heal.abstract	The objective of this paper is to present an efficient methodology for the Failure Modes Effects and Criticality Analysis (FMECA) of power electronic devices. The methodology uses fuzzy sets to represent the parameters being used in the conventional FMECA and a knowledge base is developed to identify the rules governing the fuzzy inputs and output. A fuzzy failure mode risk index is introduced to prioritise the criticality of the components for the system operation. The fuzzy inference module is Mamdani type and uses the min-max implication-aggregation method while it was developed in Matlab 6.1. The developed methodology was applied to a typical power electronic device such as a switched-mode-power-supply. The required data of the component failure modes were estimated using a reliability prediction procedure and a failure mode database. The crisp values of the conventional FMECA were used as inputs to the fuzzy FMECA and the fuzzy failure mode risk indices were calculated and compared with the respective indices calculated by the conventional FMECA. © 2005 CRL Publishing Ltd.	en
heal.publisher	C R L PUBLISHING LTD	en
heal.journalName	Engineering Intelligent Systems	en
dc.identifier.isi	ISI:000230629300008	en
dc.identifier.volume	13	en
dc.identifier.issue	2	en
dc.identifier.spage	119	en
dc.identifier.epage	125	en