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A study on warning/detection degree of warranty claims data using natural network learning
Citation
Lee, SH and Seo, SC and Yeom, SJ and Moon, K and Kang, MS and Kim, BG, A study on warning/detection degree of warranty claims data using natural network learning, Proceedings from the Sixth International Conference on Advanced Language Processing and Web Information Technology, 22-24 August, Henan, China, pp. 492-497. ISBN 9780769529301 (2007) [Refereed Conference Paper]
Copyright Statement
Copyright 2007 IEEE
DOI: doi:10.1109/ALPIT.2007.82
Abstract
Warranty service is getting important since it is an
agreement between manufacturers and consumers. An
issue is to find out a lower level of agreement from the
perspective of manufacturers and consumers. Thus, it
is very important to determine early warning/detection
degree of defected parts through warranty claims data.
However, there are qualitative factors more than
quantitative ones in the determination. The study thus
provides a part-significance knowledge extraction
method based on analytic hierarchy process analysis
which is appropriate to analyze those qualitative
factors as well as a process to extract a list of defected
parts using neural network learning.
Item Details
| Item Type: | Refereed Conference Paper |
|---|---|
| Keywords: | warranty claims data, reliability, neural network |
| Research Division: | Information and Computing Sciences |
| Research Group: | Machine learning |
| Research Field: | Neural networks |
| Objective Division: | Information and Communication Services |
| Objective Group: | Information systems, technologies and services |
| Objective Field: | Application software packages |
| UTAS Author: | Yeom, SJ (Dr Soonja Yeom) |
| ID Code: | 123784 |
| Year Published: | 2007 |
| Web of Science® Times Cited: | 3 |
| Deposited By: | Information and Communication Technology |
| Deposited On: | 2018-01-29 |
| Last Modified: | 2018-03-29 |
| Downloads: | 0 |
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