Title :
Study on Statistical Model of Reparable System Failure Data
Author :
Han, Qingtian ; Gao, Xiaoyan
Author_Institution :
Control Eng. Dept., Naval Aeronaut. & Astronaut. Univ., Yantai
Abstract :
Either for hardware or software repairable system, reliability analysis is very important. However, failure data analysis for repairable system is not an easy task. The widely used AMSAA model (power law process) is a kind of NHPP, corresponding to minimal repair. According to the variety of the reliability of repairable systems, accounting for the influences of the modification and repair, the repair effectiveness index is introduced, and a reliability growth model based on virtual age is developed. The model can be applied to various situations, such as perfect repair, imperfect repair, minimal repair, worse repair and worst repair. The failure rate function and the expression of the cumulate failure numbers are developed, and the MLE of the model parameters are also presented. Finally, the results of the analysis of the example show that the model is practical, and the parameters of the model have more exact engineering meaning.
Keywords :
data analysis; failure analysis; program diagnostics; software reliability; statistical analysis; system recovery; cumulate failure number; failure data analysis; failure rate function; hardware repairable system; imperfect repair; minimal repair; power law process; reliability analysis; reliability growth model; repair effectiveness index; reparable system failure data; software repairable system; statistical model; worse repair; worst repair; Control engineering; Data analysis; Data mining; Failure analysis; Hardware; Power system modeling; Power system reliability; Reliability engineering; Software systems; Weibull distribution; model; reliability growth; repairable system;
Conference_Titel :
Knowledge Discovery and Data Mining, 2009. WKDD 2009. Second International Workshop on
Conference_Location :
Moscow
Print_ISBN :
978-0-7695-3543-2
DOI :
10.1109/WKDD.2009.94