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Experiment Design and Reliability Analysis of Accelerated Degradation Test

Zhang, Xiao
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378197282

Abstract Details

2013, PhD, University of Cincinnati, Arts and Sciences: Mathematical Sciences.
The traditional MLE method for analyzing Accelerated Degradation Test often en- counters convergence problem because no closed form is available for most integrals. In this thesis, our target is to develop a Bayesian model to avoid the integral problem and effectively analyze the Accelerated Degradation Test data. Then we validated the model with simulation ADT data and compared with traditional and approximated MLE method's result. In comparison, the Bayesian model showed a significant advantage, as it doesn't need too much prior information, and convergences better than the MLE methods. We then further expanded the Bayesian model, combined more than one Accelerated Factors and Non-accelerated Factors. For these complex models, Bayesian method performs even better compared with MLE methods, suggestings that the Bayesian method has the ability of dealing with more complex models. An R function is developed for this model, which enables the automation of this procedure in the future. In the last part, we developed a method to find the best experimental design for a given ADT plan. This method is based on the Bayesian Network random walk model, the node with highest through frequency will be considered as the best plan, several alternative plans can also be selected from the network path based on the frequency. This model is first tested on a simple one Accelerated Factor case, and com- pared that design with current available software's result. It provided reasonable experimental plans similar to the traditional method's result for the simple case. We then applied our design method on a more practical example, and provided a detailed plan result for the example. This method has shown better accuracy than traditional balanced design in the simulated example.
Paul Horn, Ph.D. (Committee Chair)
Siva Sivaganesan, Ph.D. (Committee Member)
Xia Wang, Ph.D. (Committee Member)
95 p.
Statistics
Reliability; Design of Experiment; Bayesian Network

Recommended Citations

Citations

  • Zhang, X. (2013). Experiment Design and Reliability Analysis of Accelerated Degradation Test [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378197282

    APA Style (7th edition)

  • Zhang, Xiao. Experiment Design and Reliability Analysis of Accelerated Degradation Test. 2013. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378197282.

    MLA Style (8th edition)

  • Zhang, Xiao. "Experiment Design and Reliability Analysis of Accelerated Degradation Test." Doctoral dissertation, University of Cincinnati, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378197282

    Chicago Manual of Style (17th edition)

ucin1378197282
542
© 2013, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.