Block Truncation Life Test Data System Of Successive Statistical Analysis

In the reliability analysis, we often estimate the unknownparameters of life distribution for each component unit of the systembased on the lifetime data. System life test data consists of two aspects,the time of failure and the cause of failure which means the failure ofthe system is caused by a failure of which unit. In practice, a researchinto the cause of the failure of system often needs to spend more timeand money which limits us from performing the further experiment toreveal the real cause of the failure. Masking occurs for various reasons,such as inadequate funding, time limit, record errors, lack of diagnostictools and some of the destructive consequences brought about by thefailure of some units. Statistical analysis of the masked data hasbecome one of the hot issues in recent years.The article focuses on the statistical analysis of the masked data ina simple series and parallel system with multiple successive censoredsample data and gives the maximum likelihood estimate of theparameters and approximate interval estimation under different failurerates. Afterwards the precision of the estimates of the parameters isgiven by MATLAB simulation.