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標題: 使用大量遮蔽系統存活資料來漸近估計個體可靠度
Asymptotic Estimation of Component Reliability Using Large Number of Masked System Life Data
作者: 鄭百志
關鍵字: Exponential distribution;指數分配;masked data;maximum likelihood estimation;mixture;unsupervised learning;遮蔽資料;最大概似估計量;混合;沒有監督的學習
出版社: 應用數學系

Life data from multi-component systems (or masked system life data) are used to estimate the reliability of each component in a system. Due to cost and diagnostic constraints, the component reliability may not be known or it is impossible to know the component reliability in the systems such as living organisms. In this paper, we consider a system where if one of components fails, the whole system fails. Suppose that the lifetimes of components have exponential distributions. The traditional approach to finding such reliability is the method of maximum likelihood (ML), which is a complicated multi-parameter optimization problem. We propose a simple likelihood function and a simple algorithm to find the unknown failure rate (reliability) of each component using a large number of masked system life data. The results of a Monte Carlo study are presented to demonstrate the convergence of estimates to the unknown reliability of each component using large masked system life test data.
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