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
收藏
页码:492 / +
页数:2
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