Description

In this study, a low-cycle fatigue experiment was conducted on printed wiring boards (PWB). The Weibull regression model and computational Bayesian analysis method were applied to analyze failure time data

In this study, a low-cycle fatigue experiment was conducted on printed wiring boards (PWB). The Weibull regression model and computational Bayesian analysis method were applied to analyze failure time data and to identify important factors that influence the PWB lifetime. The analysis shows that both shape parameter and scale parameter of Weibull distribution are affected by the supplier factor and preconditioning methods Based on the energy equivalence approach, a 6-cycle reflow precondition can be replaced by a 5-cycle IST precondition, thus the total testing time can be greatly reduced. This conclusion was validated by the likelihood ratio test of two datasets collected under two different preconditioning methods Therefore, the Weibull regression modeling approach is an effective approach for accounting for the variation of experimental setting in the PWB lifetime prediction.

Reuse Permissions
  • Details

    Contributors
    Date Created
    • 2016-11-12
    Collections this item is in
    Identifier
    • Digital object identifier: 10.1016/j.csefa.2016.11.001
    • Identifier Type
      International standard serial number
      Identifier Value
      2213-2902

    Citation and reuse

    Cite this item

    This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.

    Pan, R., Xu, X., & Juarez, J. (2016). Bayesian analysis of low-cycle fatigue failure in printed wiring boards. Case Studies in Engineering Failure Analysis, 7, 65-70. doi:10.1016/j.csefa.2016.11.001

    Machine-readable links