Modeling and detecting approach for the change point of electronic product infant failure rate

2019 ◽  
Vol 99 ◽  
pp. 222-231 ◽  
Author(s):  
Yihai He ◽  
Yixiao Zhao ◽  
Yi Wei ◽  
Anqi Zhang ◽  
Di Zhou
Keyword(s):  
Failure Rate ◽  
Change Point ◽  
Electronic Product

Estimation of change point in failure rate models

1991 ◽  
Vol 29 (1-2) ◽  
pp. 111-124 ◽  
Author(s):  
K.B. Kulasekera ◽  
K.M. Lal Saxena
Keyword(s):  
Failure Rate ◽  
Change Point

scholarly journals Failure rate of Birnbaum–Saunders distributions: Shape, change-point, estimation and robustness

2019 ◽  
Vol 33 (2) ◽  
pp. 301-328 ◽  
Author(s):  
Emilia Athayde ◽  
Assis Azevedo ◽  
Michelli Barros ◽  
Víctor Leiva
Keyword(s):  
Failure Rate ◽  
Change Point ◽  
Shape Change ◽  
Point Estimation ◽  
Change Point Estimation

On Estimating Change Point in a Failure Rate

1988 ◽  
pp. 239-252 ◽  
Author(s):  
A. P. Basu ◽  
J. K. Ghosh ◽  
S. N. Joshi
Keyword(s):  
Failure Rate ◽  
Change Point

ON THE BEHAVIORS OF THE PERCENTILE RESIDUAL LIFE FOR COMPONENTS AND FOR K-OUT-OF-N SYSTEMS

2015 ◽  
Vol 29 (2) ◽  
pp. 291-308
Author(s):  
Yan Shen ◽  
Zhisheng Ye
Keyword(s):  
Failure Rate ◽  
Change Point ◽  
Residual Life ◽  
Parallel Systems ◽  
Rate Function ◽  
Single Component ◽  
Failure Rate Function ◽  
Component Failure ◽  
Number Of Components ◽  
Intimate Relations

This paper investigates properties of the percentile residual life (PRL) function for a single component and for a k-out-of-n system. The shape of the component PRL function can be determined by the component failure rate function. The intimate relations between these two functions are studied first. Then we generalize the results to a k-out-of-n system by assuming independent and identical components. We show that the behavior of the PRL for a k-out-of-n system is quite different from the component PRL. We also find that for series and parallel systems, the location of the change point of the PRL is monotone in the number of components in a system.

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