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Design and degradation modelling through artificial neural networks
journal contribution
posted on 2007-01-01, 00:00 authored by H Lin, Lingxue KongLingxue Kong, H Y HsuAutomotive is one of the major manufacturing industries in Australia that requires extensive reliability test for the components used in vehicles. To achieve a shorter time-to-market and a highly reliable product while reducing the amount of physical prototyping, there is a growing need for better understanding on the effect that the design parameters have on the degradation of the product. This paper presents comprehensive descriptions of applying Artificial Neural Network (ANN) to capture the relationships between design and degradation. Consequently, two models of different practical significance are created as the result of the work. The vision of the models is to be used by the testers and designers as a guideline in design evaluation, so that time-consuming and expensive iterations of the product developmental cycle can be reduced substantially. The degradation of the folding force of a mechanical system is used to illustrate our approach.
History
Journal
International journal of manufacturing researchVolume
2Issue
1Pagination
97 - 113Publisher
InderscienceLocation
Olney, EnglandISSN
1750-0591eISSN
1750-0605Language
engPublication classification
C1.1 Refereed article in a scholarly journalCopyright notice
2007, Inderscience Enterprises Ltd.Usage metrics
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