Reliability Assessment for Weibull and Normal Distributions with Incomplete Data
Reliability assessment methods for two-parameter Weibull and normal distributions with type-Ⅱ censored data are proposed,enabling high-confidence inference of the one-sided confidence limit for reliable life and reliability.Moreover,a method that can make full use of past test data and integrate it with current test data for reliability assessment is presented,which can significantly improve the accuracy of current product reliability assessments due to the increased information.Based on this,the above methods are further extended to the reli-ability assessment of two-parameter Weibull and normal distributions with type-Ⅰ censored data,zero-failure data,and general incomplete data.This extension achieves a high-precision and small-sample reliability assessment of electromechanical products under incomplete data conditions.Compared to the traditional methods such as BLUE and BLIE,which require complex table querying,the proposed method is not only more theoretically rigorous but also offers higher assessment accuracy and simpler calculation steps.
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