Exponential-Dispersion Degradation Process Models With Random Effects and Covariates

2018 ◽  
Vol 67 (3) ◽  
pp. 1128-1142 ◽  
Author(s):  
Fengjun Duan ◽  
Guanjun Wang
Keyword(s):  
Random Effects ◽  
Degradation Process ◽  
Process Models

Degradation modeling based on gamma process models with random effects

2017 ◽  
pp. 0-0 ◽  
Author(s):  
Luis Alberto Rodríguez-Picón ◽  
Anna Patricia Rodríguez-Picón ◽  
Luis Carlos Méndez-González ◽  
Manuel I. Rodríguez-Borbón ◽  
Alejandro Alvarado-Iniesta
Keyword(s):  
Random Effects ◽  
Process Models ◽  
Gamma Process ◽  
Degradation Modeling

scholarly journals Accelerated Degradation Tests Modeling Based on the Nonlinear Wiener Process with Random Effects

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Shengjin Tang ◽  
Xiaosong Guo ◽  
Chuanqiang Yu ◽  
Haijian Xue ◽  
Zhijie Zhou
Keyword(s):  
Wiener Process ◽  
Random Effects ◽  
Process Modeling ◽  
High Reliability ◽  
Random Variable ◽  
Degradation Process ◽  
Unknown Parameters ◽  
Accelerated Degradation ◽  
Degradation Tests ◽  
Product Variation

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.

scholarly journals Accelerated Degradation Process Analysis Based on the Nonlinear Wiener Process with Covariates and Random Effects

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Li Sun ◽  
Xiaohui Gu ◽  
Pu Song
Keyword(s):  
Diffusion Coefficient ◽  
Wiener Process ◽  
Random Effects ◽  
Process Analysis ◽  
Likelihood Estimation ◽  
Degradation Process ◽  
Unknown Parameters ◽  
Accelerated Degradation ◽  
Degradation Data ◽  
Drift Parameter

It is assumed that the drift parameter is dependent on the acceleration variables and the diffusion coefficient remains the same across the whole accelerated degradation test (ADT) in most of the literature based on Wiener process. However, the diffusion coefficient variation would also become obvious in some applications with the stress increasing. Aiming at the phenomenon, the paper concludes that both the drift parameter and the diffusion parameter depend on stress variables based on the invariance principle of failure mechanism and Nelson assumption. Accordingly, constant stress accelerated degradation process (CSADP) and step stress accelerated degradation process (SSADP) with random effects are modeled. The unknown parameters in the established model are estimated based on the property of degradation and degradation increment, separately for CASDT and SSADT, by the maximum likelihood estimation approach with measurement error. In addition, the simulation steps of accelerated degradation data are provided and simulated step stress accelerated degradation data is designed to validate the proposed model compared to other models. Finally, a case study of CSADT is conducted to demonstrate the benefits of our model in the practical engineering.

Stochastic degradation process modeling and remaining useful life estimation with flexible random-effects

2017 ◽  
Vol 354 (6) ◽  
pp. 2477-2499 ◽  
Author(s):  
Zhengxin Zhang ◽  
Changhua Hu ◽  
Xiaosheng Si ◽  
Jianxun Zhang ◽  
Jianfei Zheng
Keyword(s):  
Random Effects ◽  
Process Modeling ◽  
Degradation Process ◽  
Remaining Useful Life ◽  
Life Estimation ◽  
Useful Life

The Scepter Waste Package Subsystem Computer Model for Performance Assessment

1982 ◽  
Vol 15 ◽  
Author(s):  
Aviva Brecher ◽  
F. J. Pearson
Keyword(s):  
Performance Assessment ◽  
Degradation Process ◽  
Process Models ◽  
System Level ◽  
Time Step ◽  
Package Design ◽  
Waste Package ◽  
Design Concepts ◽  
Systems Model ◽  
Coupling Variables

ABSTRACTThe Waste Package Performance Assessment (WAPPA) code has recently been completed, verified, and documented within the SCEPTER program for ONWI. This is a systems model of the gradual degradation of physical and retardation barriers comprising a nuclear waste package, under repository isolation conditions, in various geologic media. The model describes and predicts the temporal and spatial extent of the loss of containment capability for each barrier and for the entire waste package, on timescales of hundreds of thousands of years. The output quantifies the residual state of integrity of waste package components as a function of time and calculates heat, and radionuclide fluxes to the repository.The model includes five distinct degradation process models (Radiation, Thermal, Mechanical, Corrosion, and Leaching), which are driven both internally by waste decay and externally by repository stress and fluids. The process models are coupled at system level via state and coupling variables. The approach to degradation modeling adopted is barrier-integrated and process-sequential, allowing modification of the entire waste package sequentially by the five process models within each time step.The code is intended to serve as a tool for evaluating both the relative and the absolute performance of waste package design concepts, for guiding or selecting a preliminary design among conceptual designs, and for support of licensing activities.

Identifying suboptimalities with factorial model comparison

2018 ◽  
Vol 41 ◽  
Author(s):  
Wei Ji Ma
Keyword(s):  
Experimental Design ◽  
Model Comparison ◽  
Process Models ◽  
Multiple Forms ◽  
Factorial Experimental Design ◽  
Factorial Model ◽  
Multiple Components ◽  
The Many

AbstractGiven the many types of suboptimality in perception, I ask how one should test for multiple forms of suboptimality at the same time – or, more generally, how one should compare process models that can differ in any or all of the multiple components. In analogy to factorial experimental design, I advocate for factorial model comparison.

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