• Journal of Korean Society for Quality Management
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• v.32 no.1
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• pp.113-129
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• 2004

The reliability of the product can be improved by making the product less sensitive to noises. Especially, it Is important to make products robust against various noise factors encountered in production and field environments. In this paper, the phenomenon of degradation assumes a simple random coefficient degradation model to present analysis procedures of degradation data for robust experimental design. To alleviate weak points of previous studies, such as Taguchi's, Wasserman's, and pseudo failure time methods, novel techniques for analysis of degradation data using the cross array that regards amount of degradation as a dynamic characteristic for time are proposed. Analysis approach for degradation data using robust experimental design are classified by assumptions on parametric or nonparametric degradation rate(or slope). Also, a simulation study demonstrates the superiority of proposed methods over some previous works.

• Structural Engineering and Mechanics
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• v.9 no.6
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• pp.601-613
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• 2000

Existing models for the shear strength degradation of reinforced concrete members present varied conceptual approaches to interpreting test data. The relative superiority of one approach over the others is difficult to determine, particularly given the sparseness of ideal test data. Nevertheless, existing models are compared using a suite of test data that were used for the development of one such model, and significant differences emerge. Rather than relying purely on column test data, the body of knowledge concerning degradation of concrete as a material is considered. Confined concrete relations are examined to infer details of the degradation process, and to establish a framework for developing phenomenologically-based models for shear strength degradation in reinforced concrete members. The possibility of linking column shear strength degradation with material degradation phenomena is explored with a simple model. The model is applied to the results of 7 column tests, and it is found that such a link is sustainable. It is expected that models founded on material degradation phenomena will be more reliable and more broadly applicable than the current generation of empirical shear strength degradation models.

• Journal of Applied Reliability
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• v.18 no.1
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• pp.33-39
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• 2018

Purpose: Accelerated degradation tests can be effective in assessing product reliability when degradation leading to failure can be observed. This article proposes an accelerated degradation test model for highly reliable solid state drives (SSDs). Methods: We suggest a nonlinear mixed-effects (NLME) model to degradation data for SSDs. A Monte Carlo simulation is used to estimate lifetime distribution in accelerated degradation testing data. This simulation is performed by generating random samples from the assumed NLME model. Conclusion: We apply the proposed method to degradation data collected from SSDs. The derived power model is shown to be much better at fitting the degradation data than other existing models. Finally, the Monte Carlo simulation based on the NLME model provides reasonable results in lifetime estimation.

• Journal of Applied Reliability
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• v.2 no.2
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• pp.63-83
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• 2002

Degradation data can provide more reliability information than traditional failure-time data, especially products with few or no failures. This paper is concerned with a method of estimating lifetime distribution from field data with supplementary information on degradation data and covariates. When a distribution of degradation rate obtained by follow-up study for a portion of products that survive after-warranty follows a reciprocal-Weibull or lognormal distribution. A time-to-failure distribution of the product follows Weibull or lognormal distribution, respectively. A method of estimating lifetime parameters for this kind of data and their asymptotic properties are studied. Effects of after-warranty report probability, follow-up rate, and proportion of degradation data on pseudo maximum likelihood estimators of these parameters are investigated.

• Korean Journal of Computational Design and Engineering
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• v.18 no.1
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• pp.36-48
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• 2013

In general, the product is used under several circumstances including environmental and usage conditions. According to the circumstances, the product has various performance degradation processes. In order to optimize the lifecycle of product usage, it is important to observe the degradation process and make suitable decisions on product operations. However, there are not much research works in evaluating the degree of product degradation based on product usage data. Recently, due to emerging ICT (Information and Communication Technology) technologies, it becomes possible to get the product usage data. Based on the gathered data, it is possible to analyze the degree of product degradation. The analysis of product usage data can improve product use and product design with advanced decisions. To this end, this study addresses one approach based on FMEA/FMECA method, called PDMCA (Performance, Degradation Modes and Criticality Analysis) for evaluating product degradation status and making suitable decisions.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.9
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• pp.2271-2279
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• 1993

In the case of life prediction on the structures and machines after long service, it is natural to consider a degradation problems. Most of degradation data form practical structures are isolated data obtained at the time of periodical inspection or repair. From such data, it may be difficult to obtain the degradation curve available and necessary for life prediction. In this paper, for the purpose of obtaining a degradation curves, developed the simulate degradation method and fatigue test and Charpy impact test were conducted on the degraded, simulate degraded and recovered materials. Fatigue life prediction were conducted by using the relationship between fracture transition temperature (DBTT : vTrs) obtained from the Charpy impact test through the degradation process and fatigue crack growth constants of m and C obtained from the fatigue test.

• Journal of Applied Reliability
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• v.9 no.1
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• pp.59-69
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• 2009

LEDs have rapidly replaced old light devices such as incandescent or fluorescent lamps, and have been widely applied in general lighting, signals, automobile, signs and others. Since LEDs are for both indoor and outdoor use, temperature and humidity inevitably affect its reliability. We explain the result of the degradation life test on LEDs, and guide to reliability analysis procedure. Analysis on reliability measures are performed by Weibull++6 program, and a common shape parameter of Weibull distribution on the LED is suggested. Also, we make a description of reliability analysis procedures for the degradation data using collected test data from degradation tests. Reliability analysis procedures are consisted of estimating degradation models and failure time, verifying of distribution and parameters of the distribution, and estimating of reliability measures. Finally, this paper suggests reliability analysis method for light characteristics on LEDs.

• Journal of Applied Reliability
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• v.17 no.3
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• pp.181-187
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• 2017

Purpose: The purpose of this study is to estimate the lifetime of commercial passenger vehicles shock absorber using degradation test and data. Method: The degradation factor of shock absorber was determined to be a damping force using FMEA. Degradation test was performed on damping force under real world usage condition and analysed the degradation data. Results: To estimate the lifetime of shock absorber, a degradation model was developed and a numerical example was provided. Conclusion: Evaluation of the lifetime of commercial and military vehicles shock absorber will be possible by using the proposed degradation analysis method.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.154-156
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• 2017

Constant variance of degradation data over time has been generally assumed to estimate storage lifetime using destructive, accelerated degradation data over time. However, performance data of ammunitions deteriorate over time, and the standard deviation would tend to increase over time. This paper shows storage lifetime comparison results for constant variance and time-variant variance assumptions of degradation data over time, and proposes that time-variant variance assumption should be considered to increase accuracy in lifetime estimation.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.2
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• pp.173-179
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• 2018

Estimating reliability of a non-repairable system using the degradation data, variance assumption such as homogeneity (constant) or heteroscedasticity (time-variant) could affect accuracy of reliability estimation. This paper showed reliability estimation and comparison results under normal conditions using accelerated degradation data obtained from destructive measurements, according to variance assumption of the data at each measurement time. Degradation data from three accelerated conditions with stress factors of temperature and humidity were used to estimate reliability. The $B_{10}$ lifetime was estimated as 1243.8 years by constant variance assumption, and 18.9 years by time-variant variance. And variance assumption provided different analysis results of important stresses to reliability. Thus, accurate assumption of variance at each measurement time is required when estimating reliability using degradation data of a non-repairable system.