Planning for System Reliability Demonstration Tests under Zero Component Failures (基于零组件失效的系统可靠性验证试验计划)

Tongdan Jin
Dr. Tongdan Jin is a tenure-track Assistant Professor in the Ingram School of Engineering at Texas State University. Prior to the academia, he held a reliability engineer position for five years at Teradyne Inc., Boston. He obtained the Ph.D. in Industrial & Systems Engineering from Rutgers University. He has published more than 50 technical papers in various journals and conference proceeding...read more



Details

It is difficult to estimate the confidence interval of a systems reliability with zero failures experienced. We approach this problem by proposing a hybrid model that integrates the Bayesian model with the variance propagation technique. The Bayesian model will compute the moments of component reliability estimates, and the variance propagation technique is used to estimate the system reliability variance. The confidence interval for the system reliability is then derived by matching the moments with a beta distribution. As a major contribution, the distribution for reliability estimates with zero failures is explicitly derived. The performance of the new model is compared with existing methods, and further validated by simulation data. The results show that the hybrid model generally outperforms existing methods in terms of estimation accuracy. Because the new model does not require multiple integral calculations, it can be applied to design complex systems configured in mixed series-parallel or networked components.

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