scholarly journals Bayesian planning of step‐stress accelerated degradation tests under various optimality criteria

2018 ◽  
Vol 35 (3) ◽  
pp. 537-551 ◽  
Author(s):  
Xiujie Zhao ◽  
Rong Pan ◽  
Min Xie
Author(s):  
J M Francis ◽  
D W Moss ◽  
Elisabeth Colinet ◽  
D H Calam ◽  
D G Bullock

Acid phosphatase has been prepared in an apparently pure state by affinity chromatography from human prostatic tissue. When dissolved in an acidic albumin solution, lyophilized and stored at −20°C for up to 2 years, no time-dependent loss of catalytic activity was detectable in the reconstituted material. Accelerated degradation tests also predicted complete stability. A preliminary distribution of the lyophilized preparation to 143 laboratories confirmed its robustness and demonstrated its potential usefulness as a calibrant to unify the results of different methods of measuring acid phosphatase activity.


Technometrics ◽  
1994 ◽  
Vol 36 (3) ◽  
pp. 260-272 ◽  
Author(s):  
Michéle Boulanger ◽  
Luis A. Escobar

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Shengjin Tang ◽  
Xiaosong Guo ◽  
Chuanqiang Yu ◽  
Haijian Xue ◽  
Zhijie Zhou

Accelerated degradation tests (ADT) modeling is an important issue in lifetime assessment to the products with high reliability and long lifetime. Among the literature about the accelerated nonlinear degradation process modeling, the current methods did not consider the product-to-product variation of the products with the same type. Therefore, this paper proposes an accelerated degradation process modeling method with random effects for the nonlinear Wiener process. Firstly, we derive the lifetime distribution of the nonlinear Wiener process with random effects. Secondly, the nonlinear Wiener process is used to model the degradation process of a single stress, and the drift coefficient is considered as a random variable to describe the product-to-product variation. Using the random acceleration model, the random effects are incorporated into the constant stress ADT models and the step stress ADT models. Then, a two-step maximum likelihood estimation (MLE) method is presented to estimate the unknown parameters in the degradation models. Finally, a simulation study and a case study are provided to demonstrate the application and superiority of the proposed model.


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