Bivariate Constant Stress Degradation Model: LED Lighting System Reliability Estimation with Two-stage Modelling

被引:83
作者
Sari, J. K. [1 ,2 ,3 ]
Newby, M. J. [3 ]
Brombacher, A. C. [3 ]
Tang, L. C. [2 ]
机构
[1] Knowledge Ctr Wind Turbine Mat & Construct, NL-1770 AA Wieringerwerf, Netherlands
[2] Natl Univ Singapore, Dept Ind & Syst Engn, Singapore 117548, Singapore
[3] Tech Univ Eindhoven, Fac Technol Management, Qual & Reliab Grp, Eindhoven, Netherlands
关键词
generalized linear model; bivariate CSDT; copula function; LED lighting system; ACCELERATED-DEGRADATION; LINEAR DEGRADATION; TESTS;
D O I
10.1002/qre.1022
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Light-emitting diode (LED) lamp has received great attention as a potential replacement for the more commercially available lighting technology, such as incandescence and fluorescence lamps. LED which is the main component of LED lamp has a very long lifetime. This means that no or very few failures are expected during LED lamp, testing. Therefore, degradation testing and modelling are needed. Because the complexity of modern lighting system is increasing, it is possible that more than one degradation failures dominate the system reliability. If degradation paths of the systems performance characteristics (PCs) tend to be comonotone there is a likely dependence between the PCs because of the system v common usage history. lit this paper, a bivariate constant stress degradation data model is proposed. The model accommodates assumptions of dependency between PCs and allows the use of different marginal degradation distribution functions. Consequently, a better system reliability estimation can be expected front this model than from a model with independent PCs assumption. The proposed model is applied to art actual LED lamps experiment data. Copyright (C) 2009 John Wiley & Sons, Ltd.
引用
收藏
页码:1067 / 1084
页数:18
相关论文
共 32 条
[1]   Two-stage estimation in copula models used in family studies [J].
Andersen, EW .
LIFETIME DATA ANALYSIS, 2005, 11 (03) :333-350
[2]  
[Anonymous], 1996, ESTIMATION METHOD IN
[3]  
[Anonymous], 2001, Classical competing risks
[4]  
[Anonymous], 2018, Generalized linear models
[5]   Statistical analysis of linear degradation and failure time data with multiple failure modes [J].
Bagdonavicius, V ;
Bikelis, A ;
Kazakevicius, V .
LIFETIME DATA ANALYSIS, 2004, 10 (01) :65-81
[6]  
BULLOUGH JD, 2006, ASSIST RECOMMENDS LE
[7]   Lifetime distribution based degradation analysis [J].
Chen, ZH ;
Zheng, SR .
IEEE TRANSACTIONS ON RELIABILITY, 2005, 54 (01) :3-10
[8]   Reliability assessment from degradation data [J].
Crk, V .
ANNUAL RELIABILITY AND MAINTAINABILITY SYMPOSIUM - 2000 PROCEEDINGS, 2000, :155-161
[9]   Comparison of methods to estimate the time-to-failure distribution in degradation tests [J].
de Oliveira, VRB ;
Colosimo, EA .
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2004, 20 (04) :363-373
[10]  
Energy Information Administration, 2007, DOEEIA04842007