Planning of step-stress accelerated degradation test based on the inverse Gaussian process

The step-stress accelerated degradation test (SSADT) is a useful tool for assessing the lifetime distribution of highly reliable or expensive product. Some efficient SSADT plans have been proposed when the underlying degradation follows the Wiener process or Gamma process. However, how to design an efficient SSADT plan for the inverse Gaussian (IG) process is still a problem to be solved. The aim of this paper is to provide an optimal SSADT plan for the IG degradation process. A cumulative exposure model for the SSADT is adopted, in which the product degradation path depends only on the current stress level and the degradation accumulated, and has nothing to do with the way of accumulation. Under the constraint of the total experimental budget, some design variables are optimized by minimizing the asymptotic variance of the estimated p-quantile of the lifetime distribution of the product. Finally, we use the proposed method to deal with the optimal SSADT design for a type of electrical connector based on a set of stress relaxation data. The sensitivity and stability of the SSADT plan are studied, and we find that the optimal test plan is quite robust for a moderate departure from the values of the parameters.

[1]  Ewan Macarthur,et al.  Accelerated Testing: Statistical Models, Test Plans, and Data Analysis , 1990 .

[2]  Xiao Wang,et al.  Wiener processes with random effects for degradation data , 2010, J. Multivar. Anal..

[3]  Tongmin Jiang,et al.  A Bayesian reliability evaluation method with integrated accelerated degradation testing and field information , 2013, Reliab. Eng. Syst. Saf..

[4]  Yu Fan,et al.  Bayesian Optimal Design for Step-Stress Accelerated Degradation Testing Based on Gamma Process and Relative Entropy , 2015 .

[5]  Sheng-Tsaing Tseng,et al.  Optimal design for step-stress accelerated degradation tests , 2006, IEEE Trans. Reliab..

[6]  Michael S. Hamada,et al.  Bayesian Analysis of Step-Stress Accelerated Life Tests and Its Use in Planning , 2015 .

[7]  Zhengqiang Pan,et al.  Multiple-Steps Step-Stress Accelerated Degradation Modeling Based on Wiener and Gamma Processes , 2010, Commun. Stat. Simul. Comput..

[8]  Luis A. Escobar,et al.  Accelerated degradation tests: modeling and analysis , 1998 .

[9]  Jen Tang,et al.  Optimum step-stress accelerated degradation test for Wiener degradation process under constraints , 2015, Eur. J. Oper. Res..

[10]  Xiao Wang,et al.  An Inverse Gaussian Process Model for Degradation Data , 2010, Technometrics.

[11]  Enrico Zio,et al.  Smart electricity meter reliability prediction based on accelerated degradation testing and modeling , 2014 .

[12]  Loon Ching Tang,et al.  Accelerated Degradation Test Planning Using the Inverse Gaussian Process , 2014, IEEE Transactions on Reliability.

[13]  Maya R. Gupta,et al.  Functional Bregman Divergence and Bayesian Estimation of Distributions , 2006, IEEE Transactions on Information Theory.

[14]  G A Whitmore,et al.  Modelling Accelerated Degradation Data Using Wiener Diffusion With A Time Scale Transformation , 1997, Lifetime data analysis.

[15]  Xiang Lu,et al.  Reliability demonstration methodology for products with Gamma Process by optimal accelerated degradation testing , 2015, Reliab. Eng. Syst. Saf..

[16]  Kush R. Varshney,et al.  Bayes Risk Error is a Bregman Divergence , 2011, IEEE Transactions on Signal Processing.

[17]  Naijun Sha,et al.  Bayesian analysis for step-stress accelerated life testing using weibull proportional hazard model , 2014 .

[18]  Zhengqiang Pan,et al.  Optimal Design for Step-Stress Accelerated Degradation Test with Multiple Performance Characteristics Based on Gamma Processes , 2014, Commun. Stat. Simul. Comput..

[19]  Hao Qin,et al.  Inverse Gaussian process-based corrosion growth model for energy pipelines considering the sizing error in inspection data , 2013 .

[20]  Tao Yuan,et al.  Bayesian planning of optimal step-stress accelerated life test , 2011, 2011 Proceedings - Annual Reliability and Maintainability Symposium.

[21]  Zhuoming Xu,et al.  An Improved Particle Swarm Optimization Algorithm Based on Centroid and Exponential Inertia Weight , 2014 .

[22]  Guangbin Yang Life cycle reliability engineering , 2007 .

[23]  Weiwen Peng,et al.  A Bayesian optimal design for degradation tests based on the inverse Gaussian process , 2014 .

[24]  Chien-Yu Peng,et al.  Inverse Gaussian Processes With Random Effects and Explanatory Variables for Degradation Data , 2015, Technometrics.

[25]  Narayanaswamy Balakrishnan,et al.  Optimal Step-Stress Accelerated Degradation Test Plan for Gamma Degradation Processes , 2009, IEEE Transactions on Reliability.

[26]  William Q. Meeker,et al.  Bayesian Methods for Accelerated Destructive Degradation Test Planning , 2012, IEEE Transactions on Reliability.

[27]  M. Crowder,et al.  Covariates and Random Effects in a Gamma Process Model with Application to Degradation and Failure , 2004, Lifetime data analysis.

[28]  Nan Chen,et al.  The Inverse Gaussian Process as a Degradation Model , 2014, Technometrics.

[29]  M. Xie,et al.  Planning of step-stress accelerated degradation test , 2004, Annual Symposium Reliability and Maintainability, 2004 - RAMS.

[30]  Wayne Nelson,et al.  Analysis of Performance-Degradation Data from Accelerated Tests , 1981, IEEE Transactions on Reliability.

[31]  Haijian Xue,et al.  Accelerated Degradation Tests Modeling Based on the Nonlinear Wiener Process with Random Effects , 2014 .

[32]  Mohamed AbuAli,et al.  Bayesian optimal design of step stress accelerated degradation testing , 2015 .

[33]  Nan Chen,et al.  A new class of Wiener process models for degradation analysis , 2015, Reliab. Eng. Syst. Saf..

[34]  Dipak K. Dey,et al.  Bayesian model diagnostics using functional Bregman divergence , 2014, J. Multivar. Anal..

[35]  Weiwen Peng,et al.  Inverse Gaussian process models for degradation analysis: A Bayesian perspective , 2014, Reliab. Eng. Syst. Saf..

[36]  W. Nelson Statistical Methods for Reliability Data , 1998 .

[37]  S. Tseng,et al.  Step-Stress Accelerated Degradation Analysis for Highly Reliable Products , 2000 .

[38]  Suk Joo Bae,et al.  Degradation models and implied lifetime distributions , 2007, Reliab. Eng. Syst. Saf..

[39]  Zhengqiang Pan,et al.  Reliability modeling of degradation of products with multiple performance characteristics based on gamma processes , 2011, Reliab. Eng. Syst. Saf..

[40]  W. Meeker Accelerated Testing: Statistical Models, Test Plans, and Data Analyses , 1991 .

[41]  J. Bert Keats,et al.  Statistical Methods for Reliability Data , 1999 .