Volume 8 Number 12 (Dec. 2013)
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JCP 2013 Vol.8(12): 3210-3215 ISSN: 1796-203X
doi: 10.4304/jcp.8.12.3210-3215

Electronics Life Prediction based on Multiple Performance Parameters ADT using Multidimensional Time Series Model

Li Wang, Zaiwen Liu, Xuebo Jin, Yan Shi
School of Computer & Information Engineering, Beijing Technology & Business University, China
Abstract—This paper proposes a new Accelerated Degradation Testing (ADT) life prediction method utilizing a multidimensional composite time series modeling procedure to take into account the integrated effect of system’s multiple performance parameters along with the random effect of environmental variables for equivalent damage in ADT. In this paper, system performance parameter ADT data are treated as a multidimensional composite time series model to predict system failure time. First, this paper decomposes these multiple performance parameters useful for ADT into three classes as trend, cyclical or random components, and describes them with a combined multi-dependent variable regressive model, hidden periodic model and multivariate auto-regression model. Second, according to standard practice, this paper assumes that the failure of such a system obeys a competing failure rule, that is, for an individual unit there is one primary controlling variable that will indicate failure even though others degrade they do not meet any failure criterion. Failure time at each test-stress level is predicted by using the best linear unbiased prediction of the multidimensional composite time series model. Finally, the reliability at usestress level is estimated from a failure time distribution evaluation based on the failure time predictions at each teststress level providing a relationship between failure time and test-stress levels.

Index Terms—Electronics, Time Series, Life prediction, Model, ADT

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Cite: Li Wang, Zaiwen Liu, Xuebo Jin, Yan Shi, "Electronics Life Prediction based on Multiple Performance Parameters ADT using Multidimensional Time Series Model," Journal of Computers vol. 8, no. 11, pp. 3210-3215, 2013.

General Information

ISSN: 1796-203X
Frequency: Monthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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