Reliability and cost optimization of electronic devices considering the component failure rate uncertainty

Zafiropoulos, EP; Dialynas, EN

dc.contributor.author	Zafiropoulos, EP	en
dc.contributor.author	Dialynas, EN	en
dc.date.accessioned	2014-03-01T01:21:18Z
dc.date.available	2014-03-01T01:21:18Z
dc.date.issued	2004	en
dc.identifier.issn	0951-8320	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/16192
dc.subject	Failure rate uncertainty	en
dc.subject	Latin hypercube sampling method	en
dc.subject	Monte Carlo simulation	en
dc.subject	Simulated annealing algorithm	en
dc.subject	Single objective and multiobjective optimization	en
dc.subject	System reliability	en
dc.subject.classification	Engineering, Industrial	en
dc.subject.classification	Operations Research & Management Science	en
dc.subject.other	Algorithms	en
dc.subject.other	Computational methods	en
dc.subject.other	Computer simulation	en
dc.subject.other	Costs	en
dc.subject.other	Electronic equipment	en
dc.subject.other	Estimation	en
dc.subject.other	Monte Carlo methods	en
dc.subject.other	Optimal systems	en
dc.subject.other	Optimization	en
dc.subject.other	Probability distributions	en
dc.subject.other	Sampling	en
dc.subject.other	Simulated annealing	en
dc.subject.other	Failure rate uncertainty	en
dc.subject.other	Latin hypercube sampling methods	en
dc.subject.other	Simulated annealing algorithms	en
dc.subject.other	Single objective and multiobjective optimization	en
dc.subject.other	System reliability	en
dc.subject.other	Reliability	en
dc.title	Reliability and cost optimization of electronic devices considering the component failure rate uncertainty	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.ress.2003.11.012	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.ress.2003.11.012	en
heal.language	English	en
heal.publicationDate	2004	en
heal.abstract	The objective of this paper is to present an efficient computational methodology to obtain the optimal system structure of electronic devices by using either a single or a multiobjective optimization approach, while considering the constraints on reliability and cost. The component failure rate uncertainty is taken under consideration and it is modeled with two alternative probability distribution functions. The Latin hypercube sampling method is used to simulate the probability distributions. An optimization approach was developed using the simulated annealing algorithm because of its flexibility to be applied in various system types with several constraints and its efficiency in computational time. This optimization approach can handle efficiently either the single or the multiobjective optimization modeling of the system design. The developed methodology was applied to a power electronic device and the results were compared with the results of the complete enumeration of the solution space. The stochastic nature of the best solutions for the single objective optimization modeling of the system design was sampled extensively and the robustness of the developed optimization approach was demonstrated. (C) 2004 Elsevier Ltd. All rights reserved.	en
heal.publisher	ELSEVIER SCI LTD	en
heal.journalName	Reliability Engineering and System Safety	en
dc.identifier.doi	10.1016/j.ress.2003.11.012	en
dc.identifier.isi	ISI:000221899000005	en
dc.identifier.volume	84	en
dc.identifier.issue	3	en
dc.identifier.spage	271	en
dc.identifier.epage	284	en