• Journal of Applied Reliability
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• v.3 no.2
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• pp.93-101
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• 2003

Life time data analysis requires some time-to-failure data to an extent. Some life tests result in few or no failure. In such cases, it is difficult to access reliability with traditional life tests that record only time to failure. Furthermore, with short product development time, reliability tests must be conducted with severe time constraints. For some devices, it is possible to obtain degradation measurements over time, and these measurements may contain useful information about product reliability. This article describes degradation reliability analysis methods to do inferences and predictions about a failure-time distribution by using software. In addition, the possibility of extension to CBM (Condition Based Maintenance) is suggested as an example of applied degradation data analysis.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.1
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• pp.1-6
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• 1998

Our studies diagnose insulation degradation using the method of PD system. In analysis method of degradation, we make use of degradation information that analyzed the phase angle - PD pulse amplitude - degradation time( $\Phi$- PDA - t) pattern and phase angle- PD pulse number - degradation time( $\Phi$- PDN - t) pattern using statistical operators such as skewness(S), kurtosis(K). Secondly using statically operator such as the center of gravity (G), the gradient of the discharge distribution(C), we have analyzed for the prediction of life which we can be obtained the time, occurred of many pulse of small discharge amplitude.

• Journal of Applied Reliability
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• v.18 no.1
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• pp.80-86
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• 2018

Purpose: This article provides a mathematical model for the accelerated degradation test when the performance degradation characteristic follows the lognormal distribution. Method: For developing test plans, the total number of test units and the test time are determined based on the minimization of the asymptotic variance of the q-th quantile of the lifetime distribution at the use condition. Results: The mathematical model for the accelerated degradation test is provided. Conclusion: Accelerated degradation test method is widely used to evaluate the product lifetime within a resonable amount of cost and time. In this article. a mathematical model for the accelerated degradation test method is newly developed for this purposes.

• Journal of Applied Reliability
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• v.16 no.4
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• pp.356-363
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• 2016

Purpose: The purpose of this study is to propose efficiency of equipment testing the luminance degradation of OLED. Methods: The degradation model of Exponential model and Stretched exponential model is analyzed by goodness of fit test using calculated R-square. The degradation model having the higher R-square is finally selected. Scale parameter and Shape parameter using the selected degradation model is estimated. The activation energy and current density n using peck model among the accelerated model is estimated. the estimated parameters are analyzed by t-test. Results: The results of t-test show that the estimated parameters on chamber and hotplate are equal statistically. we can know the similarity of the luminance degradation rate and degradation pattern on chamber and hotplate. Conclusion: The result of the degradation test on chamber and hotplate is similar. when the accelerated degradation test on the panel of the OLED TV is performed, hotplate is requiring less samples, time and cost than chamber. so the accelerated degradation test on the panel of the OLED TV using the hoplate is efficient of time and cost.

• Journal of Applied Reliability
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• v.15 no.4
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• pp.270-275
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• 2015

Purpose : UHMWPE (Ultra-high-molecular-weight-polyethylene) is one of the most widely used material in knife protection clothes because of high strength, elasticity, and light weight. The purpose of this study is to develop the accelerated life test method and predict the lifetime for the knife protection fabric composed by UHMWPE. Methods : In this study, degradation characteristics of UHMWPE fibers and knife protection fabric for cut resistance were evaluated under the hydrolysis and photo-degradation conditions. It was found out that the degradation rate of retained tensile strength was more significant in the photo-degradation than hydrolysis. Therefore, the failure time was determined as the time that the retained tensile strength in photo-degradation is less than 50%. Considering an acceleration factor for irradiance and exposure time, the lifetime was predicted from the calculated failure time. Results : As a result of the accelerated life test, the $B_{10}$ lifetime of knife protection fabric composed by UHMWPE fibers is estimated as 2.8 years for a 90% statistical confidence level. Conclusion: Since the lifetime is predicted by the view-point of radiant exposure in this study, there is a possibility that the estimated lifetime may differ from the actual lifetime. However, it is considered as an useful methodology to estimate the long-term lifetime of knife protection fabrics.

• Journal of Korean Society for Quality Management
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• v.38 no.4
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• pp.504-511
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• 2010

A fuze detonator comprising star shells is an important device so that its failure usually leads to failure of the shells. In this paper, accelerated degradation tests of RD1333 (lead azide) using temperature stress were performed, and then degradation data of explosive power for the detonator were analyzed to predict the storage lifetime of detonator. Degradation data analysis to estimate the storage lifetime is based on a distribution-based degradation process. Statistical distribution parameters of explosive power degradation measures at each time were estimated for each temperature level, and then reliability of the detonator for each accelerated temperature level was estimated using both time-varying distribution parameters and critical level of explosive power. Arrhenius model was applied to estimate storage lifetime of the detonator under the field temperature condition. Accelerated distribution-based degradation analysis to estimate storage lifetime is explained in detail, and estimation results are compared to field data of storage lifetime in this paper.

• IE interfaces
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• v.12 no.3
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• pp.448-457
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• 1999

Accelerated degradation is concerned with models and data analyses for degradation of product performance over time at overstress and design conditions. Although there have been numerous studies with accelerated degradation theory in reliability, very few actually apply to parametric statistical analyses. This paper shows how to analyze degradation data, provides tests for how well the assumptions hold. Reel sensors, a sort of photointerrupters in home VCR, hive been tested, and least-square analyses are used to illustrate our approach. Tests for linearity of the performance-time relationship, dependence of the lognormal distribution, and the standard deviation on time are performed. The mean life of tested sensors is assessed at about 414,000 hours, and the Arrhenius activation energy of this reaction is concluded to be 0.39 eV as results.

• Journal of Applied Reliability
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• v.5 no.4
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• pp.413-425
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• 2005

As an alternative to traditional life testing, degradation tests can be effective in assessing product reliability when measurements of degradation leading to failure can be observed. This article presents an accelerated degradation testing for vacuum fluorescent displays (VFDs). The accelerated degradation model is based on Arrhenius-lifetime relationship for cathode temperatures. We compare the results between accelerated degradation test and test at normal use condition. Accelerated degradation test for display devices is observed as an efficient method to warrantee product reliability to customers, as well as a tool to save time and costs.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1686-1693
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• 2014

In this paper, oil-paper samples composed of transformer windings were used to investigate the insulation degradation process subjected to partial discharge (PD), with artificial defects inside to simulate the PD induced insulation degradation. To determine appropriate test voltages, the breakdown time obtained through a group of accelerated electrical degradation tests under high voltages was firstly fitted by two-parameter Weibull model to acquire the average breakdown time, which was then applied to establish the inverse power law life model to choose advisable test voltages. During the electrical degradation process, PD signals were synchronously detected by an ultra-high frequency (UHF) sensor from inception to breakdown. For PD analysis, the whole degradation process was divided into ten stages, and chaos theory was introduced to analyze the variation of three chaotic parameters with the development of electrical degradation, namely the largest Lyapunov exponent, correlation dimension and Komogorov entropy of PD amplitude time series. It is shown that deterministic chaos of PD is confirmed during the oil-paper degradation process, and the obtained results provide a new effective tool for the diagnosis of degradation of oil-paper insulation subjected to PD.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.45-51
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• 2000

This study proposes that analysis and evaluation method of time series ultrasonic signal using the chaotic feature extrac-tion for degradation extent. Features extracted from time series data using the chaotic time series signal analyze quantitatively material degradation extent. For this purpose analysis objective in this study if fractal dimension lyapunov exponent and strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical syste, In experiment fractal(correlation) dimensions and lyapunov experiments showed values of mean 3.837-4.211 and 0.054-0.078 in case of degradation material The proposed chaotic feature extraction in this study can enhances ultrasonic pattern recognition results from degrada-tion signals.