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Optimization of reliability allocation strategies through use of genetic algorithms [electronic resource].

Published
Washington, D.C. : United States. Dept. of Energy, 1996.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
Physical Description
11 pages : digital, PDF file
Additional Creators
Sandia National Laboratories, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
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Summary
This paper examines a novel optimization technique called genetic algorithms and its application to the optimization of reliability allocation strategies. Reliability allocation should occur in the initial stages of design, when the objective is to determine an optimal breakdown or allocation of reliability to certain components or subassemblies in order to meet system specifications. The reliability allocation optimization is applied to the design of a cluster tool, a highly complex piece of equipment used in semiconductor manufacturing. The problem formulation is presented, including decision variables, performance measures and constraints, and genetic algorithm parameters. Piecewise ``effort curves`` specifying the amount of effort required to achieve a certain level of reliability for each component of subassembly are defined. The genetic algorithm evolves or picks those combinations of ``effort`` or reliability levels for each component which optimize the objective of maximizing Mean Time Between Failures while staying within a budget. The results show that the genetic algorithm is very efficient at finding a set of robust solutions. A time history of the optimization is presented, along with histograms or the solution space fitness, MTBF, and cost for comparative purposes.
Report Numbers
E 1.99:sand--96-1998c
E 1.99: conf-9609208--1
conf-9609208--1
sand--96-1998c
Subject(s)
Other Subject(s)
Note
Published through SciTech Connect.
08/01/1996.
"sand--96-1998c"
" conf-9609208--1"
"DE96013823"
6. American Institute of Aeronautics and Astronautics (AIAA)/USAF/NASA/ISSMO symposium on multidisciplinary analysis and optimization, Bellevue, WA (United States), 4-6 Sep 1996.
Campbell, J.E.; Painton, L.A.
Funding Information
AC04-94AL85000
View MARC record | catkey: 14351153