Title :
Warranty Cost Forecast Based on Car Failure Data
Author :
Hrycej, Tomas ; Grabert, Matthias
Author_Institution :
DaimlerChrysler Res. Center, Ulm
Abstract :
A failure and warranty cost model is gained from a failure database. The model is a combination of statistical components with a multi-layer perceptron and a cross-entropy based learning rule. The model is used for forecasting warranty costs in alternative warranty condition scenarios. The estimate of forecast variance considers both the individual vehicle risk and the overall manufacturing quality fluctuation risk.
Keywords :
automobiles; costing; failure analysis; multilayer perceptrons; reliability; alternative warranty condition scenarios; car failure data; cross-entropy based learning rule; manufacturing quality fluctuation risk; multilayer perceptron; warranty cost forecast; Costs; Data mining; Databases; Fluctuations; Manufacturing; Neural networks; Predictive models; Roads; Vehicles; Warranties;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4370939
