• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.3
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• pp.403-412
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• 2018

Medium-scale tests were conducted to measure and observe the strength and failure behavior of freshwater ice rubble. A custom box measuring $3.05m{\times}0.94m{\times}0.94m$, with Plexiglas walls was built so that failure mechanisms could be observed. Ice rubble beams of nominal thickness 50 cm were produced by placing randomly sized ice pieces into the box filled with water at its freezing temperature. After the specified consolidation time, ranging between 0.2 and 70.5 h, the ice rubble beam was deformed by pushing a platen vertically downwards though the center of the beam until failure. For consolidation times less than 4 h, the ice beam failed progressively and tended to fail by shearing on macroscopic scale. At times greater than 4 h the beam failed by bending. The change in failure behaviour has been attributed to the degree of bonding between ice blocks.

• Journal of the Korea Society for Simulation
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• v.14 no.1
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• pp.1-8
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• 2005

In the semiconductor manufacturing, yield enhancement is an urgent issue. It is ideal to prevent all the failures. However, when a failure occurs, it is important to quickly specify the cause stage and take countermeasure. Reviewing wafer level and composite lot level yield patterns has always been an effective way of identifying yield inhibitors and driving process improvement. This process is very time consuming and as such generally occurs only when the overall yield of a device has dropped significantly enough to warrant investigation. The automatic method of failure pattern extraction from fail bit map provides reduced time to analysis and facilitates yield enhancement. The automatic method of failure pattern extraction from fail bit map provides reduced time to analysis and facilitates yield enhancement. This paper describes the techniques to automatically classifies a failure pattern using a fail bit map.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.2
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• pp.154-157
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• 2010

In this paper, the Time-varying Failure Rates(TFR) of power distribution system components are extracted from the recorded failure data of KEPCO(Korea Electric Power Corporation) and the reliability of power distribution system is evaluated using Mean Failure Rate(MFR) and TFR. The TFR is approximated to bathtub curve using the exponential and Weibull distribution function. In addition, Kaplan-Meier estimation is applied to TFR extraction because of incomplete failure data of KEPCO. Also the reliability of the real power distribution system of Korea is evaluated using the MFR and TFR extracted from real failure data, respectively and the results of each case are compared with each other. As a result, it is proved that the reliability evaluation using the TFR is more realistic than MFR. In addition, it is presented that the application method at power distribution system maintenance and repair using the result of TFR.

• Journal of the Korean Society of Safety
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• v.20 no.3 s.71
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• pp.1-8
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• 2005

The industrial induction motor is widely used in the rotating electrical machine for the transmission of power. It is very reliable equipment, but it could lead to the loss of production and lift when failure occurs. Therefore, the failure data is acquired and analyzed by attaching an exclusive instrument to existing induction motor. However, these instruments could lead to side effects, increasing the production costs, because they are very expensive. The purpose of this study is the development of an induction motor bearing failure diagnosis system constructed using LabVIEW which can be supplied the kernelled function, process monitoring and current signature analysis. In addition, the availability and reasonability of the constructed system was examined for an induction motor with failure defects in outer raceway and ball bearing. From the results, it shows that failure diagnosis system constructed is useful for real-time monitoring with detection of bearing defects over the web.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.55-66
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• 2019

Storage system often applies erasure codes to protect against disk failure and ensure system reliability and availability. Liberation code that is a type of coding scheme has been widely used in many storage systems because its encoding and modifying operations are efficient. However, it cannot effectively achieve fast recovery from single disk failure in storage systems, and has great influence on recovery performance as well as response time of client requests. To solve this problem, in this paper, we present HRSF, a Hybrid Recovery method for solving Single disk Failure. We present the optimal algorithm to accelerate failure recovery process. Theoretical analysis proves that our scheme consumes approximately 25% less amount of data read than the conventional method. In the evaluation, we perform extensive experiments by setting different number of disks and chunk sizes. The results show that HRSF outperforms conventional method in terms of the amount of data read and failure recovery time.

• Journal of the Korean Statistical Society
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• v.11 no.2
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• pp.77-87
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• 1982

The choice if constants that define a life testing procedure is considered in terms of the test termination time (censoring time) and the number of items to be tested subject to a given range of variance of the expected life time, where the failure time of life testing is exponentially distributed.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.79-86
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• 2020

Failure data that has systematically managed for a long time has high reliability to an estimated volume. But since much cost and effort are needed to secure reliability data, data from overseas country is used in quantitative risk analysis in many workplaces. Reliability of the data that can be collected in workplaces can be dropped because of insufficient sample or lack of observation time. Therefore, estimated data is difficult to use as it is and environment and characteristic of the workplace cannot be reflected by using data from overseas country. So this study used Bayesian method that can be used reflecting both reliability data from overseas country and workplace failure data that has less samples. As a setting toward difficult situation that securing sufficient failure data cannot be achieved, we composed workplace failure data equivalent to mass observation time 20%(t=17000), 40%(t=24000), 60%(t=31000), 80%(t=38000) and IEEE data by using Bayesian method.

• Journal of Biosystems Engineering
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• v.28 no.6
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• pp.537-544
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• 2003

The objectives of this study were to investigate the failure characteristics of a total of 90 parts of tractor driveline, and to predict their average annual demands required to perform the after-sales service. The failure characteristics such as failure mode, mean time between failures, characteristic life and reliability were analyzed using the data collected through the experienced mechanics at the part centers of the tractor manufacturers. The analysis was based on the assumption that the failure distribution follows the Weibull distribution. The average annual demands were also predicted for the replacement parts using the mean time between failures and the renewal theory based on the Weibull distribution. The results of the study revealed that the driveline parts failure was mostly from wearout and their average characteristic life is about 1.760 hours. The estimated mean time between failures was in a range of 670∼3,740 hours and reliability in a range of 40∼60％. The annual replacement demands were in a range of 4∼45 for a service of 100 tractors.

• Convergence Security Journal
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• v.8 no.3
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• pp.33-39
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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 exponentially weighted moving average chart, in measuring failure time. In control, exponentially weighted moving average chart's uses are efficiency case of analysis with knowing information, Using real software failure time, we are proposed to use exponentially weighted moving average chart and comparative analysis of software failure time.

• Bulletin of the Korean Mathematical Society
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• v.39 no.1
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• pp.23-31
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• 2002

A scale parameter is the principal parameter to be estimated, since it corresponds to one of the main reliability characteristics, namely the average time to failure. To provide robustness of scale estimators to gross errors in the data, we apply the Huber minimax approach in time to failure models of the statistical reliability theory. The minimax valiance estimator of scale is obtained in the important particular case of the exponential distribution.