• 품질경영학회지
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• 제25권3호
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• pp.96-107
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• 1997

The recent stream to reliability prediction is that it is totally inclusive in depth to consider even the operating and environmental condition at the level of finished goods as well as component itselves. In this study, firstly we present the reliability prediction methods by entire failure rate model which failure rate at the system level is added to the failure rate model at the component level. Secondly we build up the improved bases of reliability demonstration through a, pp.ication of Kaplan-Meier, Cumulative hazard, Johnson's methods as non-parametric and Maximum Likelihood Estimator under exponential & Weibull distribution as parametric. And also present the methods of curve fitting to piecewise failure rate under Weibull distribution, PRST (Probability Ratio Sequential Test), curve fitting to S-shaped reliability growth curve, computer programs of each methods. Lastly we show the practical for determination of optimal burn-in time as a method of reliability enhancement, and also verify the practical usefulness of the above study through the a, pp.ication of failure and test data during 1 year.

• 전기학회논문지P
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• 제63권4호
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• pp.345-350
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• 2014

DC electrolytic capacitor is widely used in the power converter including PWM inverter, switching power supply and PFC Boost converter system because of its large capacitance, small size and low cost. In this paper, basic characteristics of DC electrolytic capacitor vs. frequency is presented and the real-time estimation scheme of ESR and capacitance based on the bandpass filtering is adopted to the single phase boost converter of uninterruptible power supply to diagnose its split dc-link capacitors. The feasibility of this real-time failure prediction monitoring system is verified by the computer simulation of the 5[kW] singe phase PFC half-bridge boost converter.

• 산업경영시스템학회지
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• 제28권1호
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• pp.49-54
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• 2005

Recently, the reliability are applied for many industrial products, and many products are required to guarantee in quality and in performance. The purpose of this paper is to present some of reliability prediction methodologies using failure rate database for machinery parts that are applicable to machine tools. VDI Turret, which is core component of the NC Lathe, was chosen as the target of the reliability prediction. The results of reliability prediction has shown the failure rate, MTBF(Mean Time Between Failure), and reliability of the VDI Turret. It is expected that proposed methodologies will be applicable to prediction of reliability for other components of machine tools.

• Journal of the Korean Data and Information Science Society
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• 제8권1호
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• pp.21-30
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• 1997

가속수명시험에서 강한충격수준에서 부품들의 고장시간이 관측되고 가속화된 고장시간을 토대로 정상충격수준에서 부품들의 성능을 조사한다. 본 논문은 지수수명분포에서 중도절단된 가속수명자료를 이용하여 고장률의 사전분포의 평균을 알 때, 정상조건하에서 하나의 미래 관찰치의 예측문제를 사전분포의 모수에 대하여 적률추정량을 이용하는 경험적 베이즈 접근방법을 적용시켜 경험적 베이즈 예측분포와 예측구간에 대하여 연구하였다.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2004년도 추계학술발표대회 논문집
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• pp.73-77
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• 2004

Failure predictions of composite single-lap bonded joints were performed considering both of composite adherend failure and bondline failure. An elastic-perfectly plastic model of adhesive and a delamination failure criterion are used. The failure prediction results such as failure mode and strength have very good agreements with the test results of joint specimens with various bonding methods and parameters. The influence of variations in the effective strength (that is, adhesion performance) and plastic behavior of adhesive on the failure characteristics of composite bonded joints are investigated numerically. The numerical results show that optimal joint strength is archived when adhesive and delamination failure occur in the same time.

• 한국가시화정보학회지
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• 제19권1호
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• pp.62-67
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• 2021

Selective catalytic reduction(SCR) is an exhaust gas reduction device to remove nitro oxides (NOx). SCR operation of ship can be controlled through valves for minimizing economic loss from SCR. Valve in SCR-high pressure (HP) system is directly connected to engine exhaust and operates in high temperature and high pressure. Long-term thermal deformation induced by engine heat weakens the sealing of the valve, which can lead to unexpected failures during ship sailing. In order to prevent the unexpected failures due to long-term valve thermal deformation, a failure prediction system using autoregressive integrated moving average (ARIMA) was proposed. Based on the heating experiment, virtual data mimicking temperature range around the SCR-HP valve were produced. By detecting abnormal temperature rise and fall based on the short-term ARIMA prediction, an algorithm determines whether present temperature data is required for failure prediction. The signal processed by the data collection algorithm was interpolated for the failure prediction. By comparing mean average error (MAE) and root mean square error (RMSE), ARIMA model and suitable prediction instant were determined.

• Applied Biological Chemistry
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• 제38권4호
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• pp.325-329
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• 1995

응고제 양, 두유 가열 온도, 성형 압력과 같은 두부 제조 공정에 따른 두부의 조직 강도를 파손강도와 초음파의 지연시간 측정을 이용하여 측정하였다. 응고제 양은 0.3%에서 두유 가열 온도는 $95^{\circ}C$에서 최대 파손강도를 나타내었고 성형압력은 압력이 증가할수록 파손강도가 증가하였으며 그에 상응하는 초음파의 잔존시간은 파손강도와 반비례하여 감소하는 경향을 나타내었다. 각 제조공정을 변수로 하여 중회귀 분석을 한 결과 초음파의 잔존시간으로 예측된 예측 파손강도와 실측정한 파손강도 값들 사이에는 유사함을 나타내어 초음파를 이용한 초음파 잔존시간의 변화는 식품조직의 변화에 따라 민감한 변화를 나타내므로 식품 제조 공정중 품질관리 측면에서 초음파의 사용이 기대되어진다.

• Composites Research
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• 제18권1호
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• pp.1-9
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• 2005

본 논문에서는 복합재료 접합 조인트의 다양한 파손 모드를 고려하여 파손 강도를 예측할 수 있는 방법을 제시하였다. 제시된 방법에서는 접착제의 탄성-완전 소성 재료 모델과 층간분리 파손 식을 이용해 접착제 파손 하중과 복합재료 부재의 층간분리 파손 하중을 동시에 계산하였다. 제시된 방법을 유한요소해석에 도입하여 복합재료 Single-Lap 접합조인트의 파손 예측을 수행하였으며 시험결과와 비교하였다 이를 통해 본 방법이 다양한 접합 방법에 따른 실제적인 파손모드 및 파손 하중을 정확하게 예측할 수 있음을 확인하였다. 또한 접착제의 유효강도(또는 접착 성능) 및 소성거동이 복합재료 접합 조인트의 파손 특성에 미치는 영향을 수치적으로 평가하였다. 이를 통해, 복합재료 접합조인트의 파손 강도는 접착제의 접착 성능과 항상 비례하지 않으며 층간분리 파손과 접착제 파손이 동시에 발생하도록 하는 것이 접합 조인트의 강도를 최대로 향상시킬 수 있음을 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권8호
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• pp.2016-2029
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• 2023

Accurate prediction of critical illness is significant for ensuring the lives and health of patients. The selection of indicators affects the real-time capability and accuracy of the prediction for critical illness. However, the diversity and complexity of these indicators make it difficult to find potential connections between them and critical illnesses. For the first time, this study proposes an indicator analysis model to extract key indicators from the preoperative and intraoperative clinical indicators and laboratory results of critical illnesses. In this study, preoperative and intraoperative data of heart failure and respiratory failure are used to verify the model. The proposed model processes the datum and extracts key indicators through four parts. To test the effectiveness of the proposed model, the key indicators are used to predict the two critical illnesses. The classifiers used in the prediction are light gradient boosting machine (LightGBM) and eXtreme Gradient Boosting (XGBoost). The predictive performance using key indicators is better than that using all indicators. In the prediction of heart failure, LightGBM and XGBoost have sensitivities of 0.889 and 0.892, and specificities of 0.939 and 0.937, respectively. For respiratory failure, LightGBM and XGBoost have sensitivities of 0.709 and 0.689, and specificity of 0.936 and 0.940, respectively. The proposed model can effectively analyze the correlation between indicators and postoperative critical illness. The analytical results make it possible to find the key indicators for postoperative critical illnesses. This model is meaningful to assist doctors in extracting key indicators in time and improving the reliability and efficiency of prediction.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권2호
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• pp.103-111
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• 2017

Purpose: Accelerated degradation tests can speed time to market and reduce the test time and costs associated with long term reliability tests to verify the required service life of a product or material. This paper proposes a service life prediction method for components or materials using an accelerated degradation tests based on the relationships between temperature and the rate of failure-causing chemical reaction. Methods: The relationship between performance degradation and the rate of a failure-causing chemical reaction is assumed and least square estimation is used to estimate model parameters from the degradation model. Results: Methods of obtaining acceleration factors and predicting service life using the degradation model are presented and a numerical example is provided. Conclusion: Service life prediction of a component or material is possible at an early stage of the degradation test by using the proposed method.