Accelerated Degradation Analysis for the Quality of a System Based on the Gamma Process

可靠性(半导体) 可靠性工程 蒙特卡罗方法 计算机科学 公制(单位) 推论 数学 统计 功率(物理) 工程类 人工智能 物理 量子力学 运营管理
作者
Man Ho Ling,Kwok‐Leung Tsui,N. Balakrishnan
出处
期刊:IEEE Transactions on Reliability [Institute of Electrical and Electronics Engineers]
卷期号:64 (1): 463-472 被引量:108
标识
DOI:10.1109/tr.2014.2337071
摘要

As most systems these days are highly reliable with long lifetimes, failures of systems become rare; consequently, traditional failure time analysis may not be able to provide a precise assessment of the system reliability. In this regard, a degradation measure, as a percentage of the initial value, is an alternate way of describing the system health. This paper presents accelerated degradation analysis that characterizes the health and quality of systems with monotonic and bounded degradation. The maximum likelihood estimates (MLEs) of the model parameters are derived, based on a gamma process, time-scale transformation, and a power link function for associating the covariates. Then, methods of estimating the reliability, the mean and median lifetime, the conditional reliability, and the remaining useful life of systems under normal use conditions are all described. Moreover, approximate confidence intervals for the parameters of interest are developed based on the observed Fisher information matrix. A model validation metric with exact power is introduced. A Monte Carlo simulation study is carried out for evaluating the performance of the proposed methods. For an illustration of the proposed model, and the methods of inference developed here, a numerical example involving light intensity of light emitting diodes (LED) is analyzed.
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