Title :
Reliability prediction using an unequal interval grey model
Author :
Wang, Yuhong ; Pohl, Edward A. ; Dang, Yaoguo
Author_Institution :
Coll. of Econ. & Manage., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
Abstract :
An unequal interval grey model is constructed to predict component reliability using meantime between failure data. The initial grey model developed focuses on predicting failure tendencies using equal time intervals or an equally spaced interval sequence for small sample sizes. Using this approach, the grey model does a poor job of predicting component reliabilities. To better predict component reliability at a random failure time an unequal time interval grey model is constructed. An improved formula expression for the first-order accumulated generation operator is developed. Using this formula and the whitened equation for the grey differential model, yields a higher prediction precision for the improved unequal interval grey model. A numerical example is used to illustrate the method mentioned above. These results are compared with parametric estimates found using the maximum likelihood method as well as with Kaplan-Meier nonparametric estimates of reliability. The results indicate that the unequal time interval grey model is capable of predicting component reliabilities better than maximum likelihood estimation approach and the Kaplan-Meier nonparametric methods.
Keywords :
grey systems; maximum likelihood estimation; reliability theory; Kaplan-Meier nonparametric estimation; component reliability; first-order accumulated generation operator; maximum likelihood estimation; meantime between failure data; reliability prediction; unequal interval grey model; Costs; Differential equations; Failure analysis; Maintenance; Manufacturing; Maximum likelihood estimation; Prediction methods; Predictive models; Reliability engineering; Reliability theory; Kaplan-Meier method; maximum likelihood estimation; reliability prediction; unequal interval grey model;
Conference_Titel :
Reliability and Maintainability Symposium (RAMS), 2010 Proceedings - Annual
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-5102-9
Electronic_ISBN :
0149-144X
DOI :
10.1109/RAMS.2010.5448063