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Prediction of Automobile Warranty Reclaims using ANFIS Approach SCOPUS

Choi Kwang-Wook, Lee Sang-Hyun, Kim Cheol-sung, Moon Kyung-Il

보안공학연구지원센터(IJSEIA) International Journal of Software Engineering and Its Applications Vol.8 No.2 2014.02 pp.243-254

※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

Basically, there are six types of warranty that can be offered either by manufacturer or dealers of a product or services which are basic warranty, extended warranty, warranty for used, repair limit warranty, service warranty and lifetime warranty. The different types of warranty policy have been established in order to fulfill the demand of manufacturers and the requirement of buyers so that a win-win situation could be acquired. However, when considering these warranty policies, an important concept to keep in mind is warranty reclaims. Warranty reclaims extend the scope of warranty activities beyond the walls of a single company to encompass suppliers, manufacturers, OEMs, distributors, dealers, repair centers, policy carriers, and customers. This paper presents a methodology to adapt historical maintenance warranty reclaims data with Adaptive Neuro Fuzzy Inference System (ANFIS) approach. The main motivations for conducting this paper are simplicity and less computational mass of the ANFIS based on linear generating functions with regard to warranty reclaims prediction.

 
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