DocumentCode
3332812
Title
A method for parameter estimation of Mixed Weibull distribution
Author
Ling, Dan ; Huang, Hong-Zhong ; Liu, Yu
Author_Institution
Sch. of Mechatron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu
fYear
2009
fDate
26-29 Jan. 2009
Firstpage
129
Lastpage
133
Abstract
Many mechanical components exhibit more than one failure mode; and not all components under study have been exposed to similar operating conditions. For example, components may have been used in different operating environments or there may be differences in design and/or material. In these cases, life time data of components would not fall on a straight line on a Weibull probability paper (WPP), that is, the standard 2-parameter Weibull distribution is not an appropriate model. It has been recognized that Mixed Weibull distribution can be used to fit such data properly. However, a mixed Weibull distribution involves more unknown parameters; and due to the difficulty of estimation of these parameters, mixed models have not been widely used. In this paper, a mixed model involving two Weibull distributions is considered. We establish parameter estimation methods for the mixed Weibull model using nonlinear least squares (NLS) theory; and quasi-Newton method is used to solve the optimization problem. A numerical example is given to compare the proposed method with the conventional graphical method.
Keywords
Weibull distribution; failure analysis; least mean squares methods; parameter estimation; mixed Weibull distribution; nonlinear least squares theory; parameter estimation; quasi-Newton method; Failure analysis; Least squares approximation; Manufacturing processes; Maximum likelihood estimation; Optimization methods; Parameter estimation; Production planning; Reliability engineering; Shape; Weibull distribution; mixed Weibull distribution; nonlinear least squares; parameter estimation; quasi-Newton method;
fLanguage
English
Publisher
ieee
Conference_Titel
Reliability and Maintainability Symposium, 2009. RAMS 2009. Annual
Conference_Location
Fort Worth, TX
ISSN
0149-144X
Print_ISBN
978-1-4244-2508-2
Electronic_ISBN
0149-144X
Type
conf
DOI
10.1109/RAMS.2009.4914663
Filename
4914663
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