Reliability Analysis for Electronic Devices Using Generalized Exponential Distribution

Electronic devices are integral part of our life and modeling their lifetime is the most challenging and interesting field in reliability analysis. To investigate the failure behavior of electronic devices reliability analysis is commonly used. In the literature, however, it is reported that one in five electronic device failure is a result of corrosion and to save electricity and predict future failures, it is important to summarize the data by some flexible probability models. This will not only help the electronic companies, but also the users by providing them information about the maximum voltage level that a particular device can bear. This article deals with the reliability analysis of electronic devices under different voltages assuming modified generalized exponential distribution and beta generalized exponential distribution using the inverse power law rule. The parameters of the modified distribution are estimated assuming Bayesian inference to include prior information. Sensitivity of hyperparameters and selection of an appropriate probability model is also a part of this study.

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

[2]  Weiyong Ding,et al.  Reliability analysis of k-out-of-n systems based on a grouping of components , 2019, Advances in Applied Probability.

[3]  Luis Carlos Méndez González,et al.  Reliability Analysis for Laptop Computer Under Electrical Harmonics , 2016, Qual. Reliab. Eng. Int..

[4]  John K. Kruschke,et al.  Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan , 2014 .

[5]  Luis Alberto Rodríguez-Picón,et al.  Reliability Estimation for Products Subjected to Two‐Stage Degradation Tests Based on a Gamma Convolution , 2016, Qual. Reliab. Eng. Int..

[6]  D. Kundu,et al.  Theory & Methods: Generalized exponential distributions , 1999 .

[7]  Lev V. Utkin,et al.  Reliability analysis of load-sharing m-out-of-n systems with arbitrary load and different probability distributions of time to failure , 2015 .

[8]  Two-Parameter Stochastic Weibull Diffusion Model: Statistical Inference and Application to Real Modeling Example , 2020 .

[9]  Luis Alberto Rodríguez-Picón,et al.  Reliability analysis for electronic devices using beta-Weibull distribution , 2017, Qual. Reliab. Eng. Int..

[10]  Frede Blaabjerg,et al.  Lifetime Estimation and Failure Risk Analysis in a Power Stage Used in Wind-Fuel Cell Hybrid Energy Systems , 2019, Electronics.

[11]  Rui Peng,et al.  Reliability modeling for a discrete time multi-state system with random and dependent transition probabilities , 2019 .

[12]  Ehsan Ullah,et al.  Beta Exponentiated Modified Weibull Distribution: Properties and Application , 2019, Symmetry.

[13]  Yili Hong,et al.  Copula-based reliability analysis of degrading systems with dependent failures , 2020, Reliab. Eng. Syst. Saf..

[14]  Lei Zhang,et al.  Reliability analysis of structures based on a probability‐uncertainty hybrid model , 2018, Qual. Reliab. Eng. Int..

[15]  Liudong Xing,et al.  Copula-based reliability and safety analysis of safety-critical systems with dependent failures , 2018, Qual. Reliab. Eng. Int..

[16]  Debasis Kundu,et al.  Generalized exponential distribution: Existing results and some recent developments , 2007 .

[17]  Xianzhen Huang,et al.  A probability estimation method for reliability analysis using mapped Gegenbauer polynomials , 2014 .

[18]  Debasis Kundu,et al.  Generalized exponential distribution: different method of estimations , 2001 .

[19]  Sofiène Tahar,et al.  An approach for lifetime reliability analysis using theorem proving , 2014, J. Comput. Syst. Sci..

[20]  Gauss M. Cordeiro,et al.  The beta generalized exponential distribution , 2008, 0809.1889.

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

[22]  K. Phoon,et al.  Copula-based approaches for evaluating slope reliability under incomplete probability information , 2015 .

[23]  Sun Youchao,et al.  Copula-based reliability analysis for a parallel system with a cold standby , 2018 .

[24]  Lulu Zhang,et al.  Reliability Assessment for Very Few Failure Data and Weibull Distribution , 2019, Mathematical Problems in Engineering.

[25]  Junho Song,et al.  Reliability growth analysis of k-out-of-N systems using matrix-based system reliability method , 2017, Reliab. Eng. Syst. Saf..

[26]  G. S. Mudholkar,et al.  Exponentiated Weibull family for analyzing bathtub failure-rate data , 1993 .

[27]  Sajid Ali,et al.  Reliability Analysis for Electronic Devices Using Beta Generalized Weibull Distribution , 2019 .

[28]  Hon Keung Tony Ng,et al.  Life Cycle Reliability Engineering , 2008, Technometrics.