Rationale for a modified Duane model

1985 ◽  
Vol 25 (6) ◽  
pp. 1163
Keyword(s):  
2017 ◽  
Vol 73 (5) ◽  
Author(s):  
G. Krishna Mohan ◽  
R. Satyaprasad ◽  
N. V. K. Stanley Raju

1984 ◽  
Vol R-33 (2) ◽  
pp. 157-159 ◽  
Author(s):  
Bev Littlewood
Keyword(s):  

2013 ◽  
Vol 13 (22) ◽  
pp. 5265-5269
Author(s):  
Wang Xiaohong ◽  
Zhang Shengpeng ◽  
Li Xiaogang

2010 ◽  
Vol 118-120 ◽  
pp. 536-540 ◽  
Author(s):  
Zhi Li Sun ◽  
Yu Guo ◽  
Shi Ji

As everyone knows, reliability growth technology is an essential part in the mechanical reliability theory as well as an insurance of the products capability in usage. It exists throughout the entire lifespan of development, manufacturing and application. Concerning the reliability characters of mechanical products, that product life obeys Weibull distribution, which is mostly resulted from the test on the small sample, three parameters of life distribution are estimated by the grey estimation in this paper. Then according to the data acquired in the test, Duane growth model is surely developed to assess the situation of reliability growth. Furthermore, the following example ascertains that the developed model is in accordance with mechanical characters. From the result, Duane model is reasonable to evaluate the reliability growth level of mechanical products. It is obvious that the improved measure is effective to enhance the reliability and the value of MTBF can be calculated with the model.


Author(s):  
Ming Zhao

One of the widely used NHPP models in reliability is the so-called power-law model, also known as the Duane model. A power-law model can be applied in analyzing failure data of both software and hardware systems. Nevertheless, the power-law model is no longer applicable to describe the failure behavior when a hardware/software embedded system is concerned since the failures can come from both hardware and software. How to analyze the failure data of this type is still a problem to study and a new type of model is needed to develop. In this paper, we consider the superposition of the power-law models (SPLM) as one candidate to describe the failure behaviors of hardware/software systems. The characteristics of SPLMs are thoroughly studied. It is shown that an SPLM has the intensity function that can be increasing, decreasing, increasing-then-decreasing or decreasing-then-increasing. Specifically, the identification method of the superposition of power-law processes is provided by using the TTT-plot technique. The TTT-transform of a superposition of power-law processes is DFR-like. Therefore, the conditional TTT-plot should present a convex pattern if the system failures follow a superposition process by a few power-law processes. This provides us an easy way to identify the model when the testing data is available.


Sign in / Sign up

Export Citation Format

Share Document