• International Journal of Reliability and Applications
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• 제10권2호
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• pp.101-107
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• 2009

In the accelerated tests, the importance of correct failure analysis must be strongly emphasized. Understanding the failure mechanisms is requisite for designing and conducting successful accelerated life test. Under this presumption, a rational method must be identified to relate the results of accelerated tests quantitatively to the reliability or failure rates in use conditions, using a scientific acceleration transform. Most widely used models for relating the results of accelerated tests quantitatively to the reliability or failure rates in use conditions are an accelerated failure time model and a proportional hazards model. The purpose of this research is to compare the usability of the accelerated failure time model and proportional hazards model in the accelerated life tests.

• Communications for Statistical Applications and Methods
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• 제23권6호
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• pp.467-478
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• 2016

The accelerated failure time model or accelerated life model relates the logarithm of the failure time linearly to the covariates. The parameters in the model provides a direct interpretation. In this paper, we review some newly developed practically useful estimation and inference methods for the model in the analysis of right censored data.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.268-275
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• 2003

We consider the Bayesian accelerated failure time model. The error distribution is assigned a skewed normal distribution which is including normal distribution. For noninformative priors of regression coefficients, we show the propriety of posterior distribution. A Markov Chain Monte Carlo algorithm(i.e., Gibbs Sampler) is used to obtain a predictive distribution for a future observation and Bayes estimates of regression coefficients.

• 전기학회논문지
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• 제57권2호
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• pp.208-213
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• 2008

In order to assess the reliability of the electronics control unit for vehicles, accelerated life test model and procedure are developed. By using this method, failure mechanism and life distribution are analyzed. The main results are as follows : i) the main failure mechanism is degradation failure that is, junction destruction of a semiconductor resin by high temperature. ii) the life distribution of the electronics control unit for vehicles is fitted well to Weibull life distribution and the accelerated life model of that is fitted well to Arrhenius model. iii) at the result of the life distribution, accelerated life test method is developed, and test time for life assessment will be shortened by 5,000 hours by this test method.

• 한국신뢰성학회지:신뢰성응용연구
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• 제11권3호
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• pp.281-291
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• 2011

This paper presents an accelerated life test of booster pump for home water purifier. The failure analysis shows that decreased flux due to the plastic deformation of bypass spring adjusting pressure is the predominant failure mechanism. An accelerated life test is designed and implemented to estimate the lifetime of the booster pump. Temperature, water pressure and voltage are selected as accelerating variables through the technical review about failure mechanism. It is assumed that the lifetimes of booster pumps follow lognormal distribution and the combination model of temperature and non-thermal stresses holds. The life-stress relationship, acceleration factor, and $B_{10}$ life at design condition are estimated by analyzing the accelerated life test data.

• 산업경영시스템학회지
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• 제23권61호
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• pp.75-87
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• 2000

This paper proposes a procedure for designing an accelerated test using SMAT(Stress, (failure) Mechanism and Test) model describing the relation among stress, failure mode/mechanism and test method. In SMAT model the stresses to be applied are derived from the environmental factor analysis, the relative importance of those stresses can be estimated using AHP(Analytic Hierarchy Process) and failure mode/mechanism and test method are derived from the fields failure information and FMEA(Failure Mode and Effect Analysis). By applying the procedure we can make a selection of major factors to cause the failure of assembly and design the accelerated test using DOE(Design of Experiments) The procedure is illustrated with an qualification test case study of washing machine shaft assembly in "A" electric appliance company.

• Journal of the Korean Data and Information Science Society
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• 제21권4호
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• pp.813-818
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• 2010

The least squares estimation method for model parameters under failure step-stress accelerated life tests is studied and a numerical example will be given to illustrate the proposed inferential procedures under the compound linear plans proposed as an alternative to the optimal quadratic plan, assuming that the exponential distribution with a quadratic relationship between stress and log-mean lifetime. The proposed compound linear plan for constant stress accelerated life tests and 4:2:1 plan are compared for various situations. Even though the compound linear plan was proposed under constant stress accelerated life tests, we found that this plan did well relatively in failure step-stress accelerated life tests.

• 대한기계학회논문집A
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• 제29권5호
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• pp.689-697
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• 2005

This paper presents the reliability estimation of door hinge for home appliances, which consists of bushing and shaft. The predominant failure mechanism of bushing made of polyoxymethylene(POM) is brittle fracture due to decrease of strength caused by voids existing, and that of shaft made of acrylonitrile-butadiene-styrene(ABS) is creep due to plastic deformation caused by excessive temperature and lowering of glass transition temperature by absorbed moisture. Since the brittle fracture of bushing is overstress failure mechanism, the load-strength interference model is used to estimate the failure rate of it along with failure analysis. By the way, the creep of shaft is wearout failure mechanism, and an accelerated life test is then planned and implemented to estimate its lifetime. Through the technical review about failure mechanism, temperature and humidity are selected as accelerating variables. Assuming Weibull lifetime distribution and Eyring model, the life-stress relationship and acceleration factor, $B_{10}$ life and its lower bound with $90\%$ confidence at worst case use condition are estimated by analyzing the accelerated life test data.

• 한국신뢰성학회:학술대회논문집
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• 한국신뢰성학회 2004년도 정기학술대회
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• pp.303-311
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• 2004

This paper presents the reliability estimation of door hinge for home appliances, which consists of bushing and shaft. The predominant failure mechanism of bushing made of polyoxymethylene(POM) is brittle fracture due to decrease of strength caused by voids existing, and that of shaft made of acrylonitrile-butadiene-styrene(ABS) is creep due to plastic deformation caused by excessive temperature and lowering of glass transition temperature by absorbed moisture. Since the brittle fracture of bushing is overstress failure mechanism, the load-strength interference model is used to estimate the failure rate of it along with failure analysis. By the way, the creep of shaft is wearout failure mechanism, and an accelerated life test is then planned and implemented to estimate its lifetime. Through the technical review about failure mechanism, temperature and humidity are selected as accelerating variables. Assuming Weibull lifetime distribution and Eyring model, the life-stress relationship and acceleration factor, B$_{10}$ life and its lower bound with 90% confidence at worst case use condition are estimated by analyzing the accelerated life test data.a.

• 한국전기전자재료학회논문지
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• 제28권12호
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• pp.843-846
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• 2015

In this paper, the failure mechanism of PTC heater were examined closely by failure analysis and based on it, accelerated life test were conducted. Finally, life distribution and acceleration model were established. The failure mechanism of PTC heater such as crack, increase of resistance due to heating were identified. Two acceleration factors such as temperature, humidity were chosen with two levels each and accelerated life test were done. Life distribution were identified as Weibull distribution with shape parameter 5.4 and Temperature-Humidity model was fitted as an acceleration model.