• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.62-68
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• 2016

The feeder cable assembly is an automotive part used for telecommunication. If it malfunctions, the control and safety of the automobile can be put at risk. ALT (Accelerated Life Testing) is a testing process for products in which they are subjected to conditions (stress, strain, temperatures, etc.) in excess of their normal service parameters in an attempt to uncover faults and potential modes of failure in a short amount of time. Failure is caused by defects in the design, process, quality, or application of the part, and these defects are the underlying causes of failure or which initiate a process leading to failure. Thermal shock occurs when a thermal gradient causes different parts of an object to expand by different amounts. Thermal shock testing is performed to determine the ability of parts and components to withstand sudden changes in temperature. In this research, the main causes of failure of the feeder cable assembly were snapping, shorting and electro-pressure resistance failure. Using the Coffin-Manson model for ALT, the normal conditions were from Tmax = $80^{\circ}C$ to Tmin = $-40^{\circ}C$, the accelerated testing conditions were from Tmax = $120^{\circ}C$ to Tmin = $-60^{\circ}C$, the AF (Acceleration Factor) was 2.25 and the testing time was reduced from 1,000 cycles to 444 cycles. Using the Bxlife test, the number of samples was 5, the required life was B0.04%.10years, in the acceleration condition, 747 cycles were obtained. After the thermal shock test under different conditions, the feeder cable assembly was examined by a network analyzer and compared with the Weibull distribution modulus parameter. The results obtained showed good results in acceleration life test mode. For the same reliability rate, the testing time was decreased by a quarter using ALT.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.797-810
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• 2017

The Korean peninsula is exposed to typhoons every year. Typhoons cause huge socioeconomic damage because tropical cyclones tend to occur with strong winds and heavy precipitation. In order to understand the complex dependence structure between strong winds and heavy precipitation, the copula links a set of univariate distributions to a multivariate distribution and has been actively studied in the field of hydrology. In this study, we carried out analysis using data of wind speed and precipitation collected from the weather stations in Busan and Jeju. Log-Normal, Gamma, and Weibull distributions were considered to explain marginal distributions of the copula. Kolmogorov-Smirnov, Cramer-von-Mises, and Anderson-Darling test statistics were employed for testing the goodness-of-fit of marginal distribution. Observed pseudo data were calculated through inverse transformation method for establishing the copula. Elliptical, archimedean, and extreme copula were considered to explain the dependence structure between strong winds and heavy precipitation. In selecting the best copula, we employed the Cramer-von-Mises test and cross-validation. In Busan, precipitation according to average wind speed followed t copula and precipitation just as maximum wind speed adopted Clayton copula. In Jeju, precipitation according to maximum wind speed complied Normal copula and average wind speed as stated in precipitation followed Frank copula and maximum wind speed according to precipitation observed Husler-Reiss copula.