Design and degradation modelling through artificial neural networks

Lin, Hungyen and Kong, L. X. and Hsu, Hung-Yao (2007) Design and degradation modelling through artificial neural networks. International Journal of Manufacturing Research, 2 (1). pp. 97-113. ISSN 1750-0591

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Abstract

Automotive 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.

Item Type:
Journal Article
Journal or Publication Title:
International Journal of Manufacturing Research
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1706
Subjects:
ID Code:
76844
Deposited By:
Deposited On:
24 Nov 2015 11:12
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Jan 2020 09:29