• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.645-646
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• 2008

In order to evaluate a solenoid actuator's reliability, the following three-step approach was used: (1) we analyzed the cause and effect of major failures through FMEA and FTA, decided the main test items through 2-stage QFD; (2) after a performance test was carried out, five-sampled data were collected from the it; finally, we decided the reliability parameters for the industrial solenoid actuator. The reliability parameters, such as the shape parameter(${\beta}$), the scale parameter(${\theta}$), etc., were analyzed inductively by the use of MINITAP and the Weibull probability model which has been used practically in the study of the reliability.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.274-283
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• 2016

The study of maintenance planning is important in military weapon systems because it can improve their availability and reduce the operational and maintenance cost during the total life cycle. In maintenance planning, it is important to determine the preventive maintenance task and its optimal interval. This paper focuses on the hard time task, which is one of the preventive maintenance tasks. A hard time task removes an item or restorative action before some specified maximum age limit to prevent functional failure. The Monte-Carlo simulation model was proposed to help understand the cost effectiveness of a hard time task. In the simulation, various shape parameters of the Weibull distribution and cost ratio of corrective maintenance to preventive maintenance were assumed. Using a Monte-Carlo simulation, a quantified cost saving effect and optimal preventive maintenance interval were suggested.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.1
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• pp.31-36
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• 2010

Collecting all failures during life cycle of vehicle is not easy way because its life cycle is normally over 10 years. Warranty period can help gathering failures data because most customers try to repair its failures during warranty period even though small failures. This warranty data, which means failures during warranty period, can be a good resource to predict initial reliability and permanence reliability. However uncertainty regarding reliability prediction remains because this data is censored. University of Wuppertal and major auto supplier developed the reliability prognosis model considering censored data and this model introduce to predict reliability estimate further "failure candidate". This paper predicts reliability of telecommunications system in vehicle using the model and describes data structure for reliability prediction.

• Convergence Security Journal
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• v.8 no.2
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• pp.35-40
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• 2008

Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. The used software failure time data for forecasting failure time is random number of Weibull distribution(shaper parameter 1, scale parameter 0.5), Using this data, we are proposed to ARIMA(AR(1)) and simulation method for forecasting failure time. The practical ARIMA method is presented.

• Korean journal of applied entomology
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• v.43 no.2
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• pp.111-116
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• 2004

The development of Aphis gossypii was studied at various constant temperatures ranging from 15 to 35$^{\circ}C$, with 60-70％ RH, and photoperiod of 16：8 (L：D h). Mortality of A. gossypii was high in the early developmental stages, and at high temperatures. The total immature developmental period ranged from 4.6 to 11.5 days. The lower developmental threshold temperature and effective cumulated temperature for all immature stages were 5.0$^{\circ}C$ and 106.8 degree-day, respective. The nonlinear shape of temperature-dependent development was well described by the modified Sharpe and DeMichele model. The normalized cumulative frequency distributions of developmental period for each life stage were fitted to the three-parameter Weibull function.

• Korean journal of applied entomology
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• v.55 no.1
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• pp.35-43
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• 2016

The temperature-dependent development of Metcalfa pruinosa overwintering eggs was investigated at ten constant temperatures (12.5, 15, 17.5, 20, 22.5, 25, 27.5, 30, 32.5, and $35{\pm}1^{\circ}C$, Relative Humidity 20~30%). All individuals collected before April 13, 2012 failed to develop into first instar larvae. In contrast, some individuals that were collected on April 11, 2013 successfully developed when reared under $20{\sim}32.5^{\circ}C$ temperature regimes. The developmental duration was shortest at $30^{\circ}C$ (13.3 days) and longest at $15^{\circ}C$ (49.6 days) in the fourth collected colony (April 26 2013). Developmental duration decreased with increasing temperature up to $30^{\circ}C$ and development was retarded at high-temperature regimes ($32.5^{\circ}C$). The lower developmental threshold was $10.1^{\circ}C$ and the thermal constant required to complete egg overwintering was 252DD. The Lactin 2 model provided the best statistical description of the relationship between temperature and the developmental rate of M. pruinosa overwintering eggs ($r^2=0.99$). The distribution of the developmental completion of overwintering eggs was well described by the 2-parameter Weibull function ($r^2=0.92$) based on the standardized development duration. However, the estimated cumulative 50% spring emergence dates of overwintering eggs were best predicted by poikilotherm rate model combined with the 2-parameter Weibull model (average difference of 1.7days between observed and estimated dates).

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.9-18
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• 2006

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the exponentiated exponential distribution reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001) Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using NTDS data set for the sake of proposing shape parameter of the exponentiated exponential distribution was employed. This analysis of failure data compared with the exponentiated exponential distribution model and the existing model (using arithmetic and Laplace trend tests, bias tests) is presented.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.3
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• pp.523-534
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• 1994

The purpose of this study is to develop computer simulation model that produce precipitation patterns from stochastic model. In the paper(I) of this study, the alternate renewal process(ARP) is used for the daily precipitation series. In this paper(Il), stochastic simulation models for the daily precipitation series are developed by combining Markov chain for the precipitation occurrence process and continuous probability distribution for the precipitation amounts on the wet days. The precipitation occurrence is determined by first order Markov chain with two states(dry and wet). The amounts of precipitation, given that precipitation has occurred, are described by a Gamma, Pearson Type-III, Extremal Type-III, and 3 parameter Weibull distribution. Since the daily precipitation series shows seasonal variation, models are identified for each month of the year separately. To illustrate the application of the simulation models, daily precipitation data were taken from records at the seven locations of the Nakdong and Seomjin river basin. Simulated data were similar to actual data in terms of distribution for wet and dry spells, seasonal variability, and precipitation amounts.

• Advanced Composite Materials
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• v.18 no.1
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• pp.77-93
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• 2009

This paper investigated the damage transition mechanism between the fiber-breaking mode and the fiber-avoiding crack mode when the fiber-length is reduced in the unidirectional discontinuous carbon fiber-reinforced-plastics (CFRP) composites. The critical fiber-length for the transition is a key parameter for the manufacturing of flexible and high-strength CFRP composites with thermoset resin, because below this limit, we cannot take full advantage of the superior strength properties of fibers. For this discussion, we presented a numerical model for the microscopic damage and fracture of unidirectional discontinuous fiber-reinforced plastics. The model addressed the microscopic damage generated in these composites; the matrix crack with continuum damage mechanics model and the fiber breakage with the Weibull model for fiber strengths. With this numerical model, the damage transition behavior was discussed when the fiber length was varied. The comparison revealed that the length of discontinuous fibers in composites influences the formation and growth of the cluster of fiber-end damage, which causes the damage mode transition. Since the composite strength is significantly reduced below the critical fiber-length for the transition to fiber-avoiding crack mode, we should understand the damage mode transition appropriately with the analysis on the cluster growth of fiber-end damage.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.7
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• pp.2159-2166
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• 1996

The stochastic properties of variation in fatigue crack growth are important in reliability and stability of structures. In this study,the stochastic model for the variation of fatigue crack growth rate was proposed in consideration of nonhomogeneity of materials. For this model, experiments were ocnducted on 7075-T6 aluminum alloy under the constant stress intensity factor range. The variation of fatigue crack growth rate was expressed by random variables Z and r based on the variation of material coefficients C and m in the paris-Erodogan's equation. The distribution of fatigue life with respect to the stress intensity factor range was evaluated by the stochastic Markov chain model based on the Paris-Erdogan's equation. The merit of proposed model is that only a small number of test are required to determine this this function, and fatigue crack growth life is easily predicted at the given stress intensity factor range.