A study on warning/detection degree of warranty claims data using neural network learning

被引：3

作者：

Lee, SangHyun ^{[1
]}

Seo, SeongChae ^{[1
]}

Yeom, SoonJa ^{[2
]}

Moon, KyungIl ^{[3
]}

Kang, MoonSeol ^{[4
]}

Kim, ByungGi ^{[1
]}

机构：

[1] Chonnam Natl Univ, Sch Elect & Comp Engn, Kwangju 500757, South Korea

[2] Univ Tasmania, Sch Comp, Lecturer & Coordinator Int Affairs, Hobart, Tas 7000, Australia

[3] Honam Univ, Dept Comp Engn, Seoul 506714, South Korea

[4] Gwangju Univ, Dept Comp Sci & Engn, Seoul 503703, South Korea

来源：

ALPIT 2007: PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON ADVANCED LANGUAGE PROCESSING AND WEB INFORMATION TECHNOLOGY | 2007年

关键词：

warranty claims data; reliability; neural network;

D O I：

10.1109/ALPIT.2007.82

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：492 / +

页数：2

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