Identification and impact assessment of high-priority field failures in passenger vehicles using evolutionary optimization

0Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.
Get full text

Abstract

This paper presents a method for prioritizing field failures in passenger vehicles based on their potential for improvement in the Customer Satisfaction Index (CSIQSR). CSIQSR refers to Customer Satisfaction Index pertaining to quality, service and reliability of the vehicle and is referred to as simply 'CSI' in this paper. A novel method for quantitative modeling of the CSI function using an evolutionary approach was presented in [3]. Such a CSI function can be used to capture individual customer's perception of a vehicle model as well as to compare overall CSI of multiple vehicle models. This work is firstly aimed at improving the previous modeling technique and validating it against Consumer Reports reliability ratings. More importantly, it presents a procedure for identifying high impact field failures based on their CSI Improvement Potential (CIP). These high priority field failures can then be further studied for root cause analysis. © 2013 Springer.

Cite

CITATION STYLE

APA

Gaur, A., Bandaru, S., Khare, V., Chougule, R., & Deb, K. (2013). Identification and impact assessment of high-priority field failures in passenger vehicles using evolutionary optimization. In Advances in Intelligent Systems and Computing (Vol. 201 AISC, pp. 111–122). Springer Verlag. https://doi.org/10.1007/978-81-322-1038-2_10

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free