• Communications for Statistical Applications and Methods
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• v.24 no.1
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• pp.43-65
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• 2017

We propose a flexible cure rate survival model by assuming that the number of competing causes of the event of interest has the Poisson distribution and the time for the event follows the gamma-G family of distributions. The extended family of gamma-G failure-time models with long-term survivors is flexible enough to include many commonly used failure-time distributions as special cases. We consider a frequentist analysis for parameter estimation and derive appropriate matrices to assess local influence on the parameters. Further, various simulations are performed for different parameter settings, sample sizes and censoring percentages. We illustrate the performance of the proposed regression model by means of a data set from the medical area (gastric cancer).

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.11
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• pp.94-101
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• 2020

In the age of industry 4.0, artificial intelligence is being widely used to realize machinery condition monitoring. Due to their excellent performance and the ability to handle large volumes of data, machine learning techniques have been applied to realize the fault diagnosis of different equipment. In this study, we performed the failure mode effect analysis (FMEA) of an aluminum electrolytic capacitor by using deep learning and big data. Several tests were performed to identify the main failure mode of the aluminum electrolytic capacitor, and it was noted that the capacitance reduced significantly over time due to overheating. To reflect the capacitance degradation behavior over time, we employed the Vanilla long short-term memory (LSTM) neural network architecture. The LSTM neural network has been demonstrated to achieve excellent long-term predictions. The prediction results and metrics of the LSTM and Vanilla LSTM models were examined and compared. The Vanilla LSTM outperformed the conventional LSTM in terms of the computational resources and time required to predict the capacitance degradation.

• Tunnel and Underground Space
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• v.27 no.3
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• pp.121-131
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• 2017

We studied the time-dependent behaviors of rock and concrete materials by conducting the static and dynamic long-term strength tests. In particular, acoustic emission(AE) signals generated while the tests were analyzed and used for the long-term stability evaluation. In the static subcritical crack growth test, the long-term behavior and AE characteristics of Mode I and Mode II were investigated. In the dynamic long-term strength test, the fatigue limit and characteristics of generation of AE were analyzed through cyclic four points bending test. The graph of the cumulative AE hits versus time showed a shape similar to that of the creep curve with the first, second and third stages. The possibility for evaluating the static and dynamic long-term stability of rock and concrete is presented from the log - log relationship between the slope of the secondary stage of cumulative AE hits curve and the delayed failure time.

• Journal of the Korean GEO-environmental Society
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• v.23 no.12
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• pp.25-31
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• 2022

Unlike structures installed on land, the structures installed on the offshore ground must consider long-term cyclic loads such as wave loads, wind loads and tidal loads at sea. Therefore, it is important to analyze the behavior of the ground subjected to long-term cyclic loads in order to design a structure installed on the ocean ground. In this paper, cyclic simple shear tests were performed to analyze the ground behavior for long-term cyclic loads according to the confining pressure, and a three-dimensional design failure curve was prepared that can easily check the failure characteristics according to the confining pressure. As a result of the analysis, it was confirmed that the position of the design failure curve is different depending on the confining pressure even under the same conditions of the cyclic shear stress ratio and the average shear stress ratio, and the number of cyclic loads reaching failure is affected by the confining pressure. From the created 3-D design failure curve under different confining pressure, the tendency and approximate value of the design failure curve according to the confining pressure can be estimated.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.1
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• pp.1-7
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• 2020

In general, an inspection schedule is established based on the long-term fatigue life during the design stage. However, in the design stage, it is difficult to clearly identify the uncertainty factors affecting long-term fatigue life. In this study, the probabilistic fatigue life assessment was conducted in accordance with the methodology of DNV-GL. Firstly, The initial crack distribution estimated through the initial crack propagation analysis was updated by reflecting the results of crack inspection. Secondly, the updated crack distribution was compared with the initial crack distribution, and the probability of failure was updated with the effect of crack inspection.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1391-1393
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• 2008

In this paper, the long-term reliability for 1.25G transceiver in use of high speed optical access network is investigated. High temperature storage tests and accelerated life tests are used to long-term reliability. Accelerated aging test have been during 3,000 hour of the three accelerated aging conditions by caused high temperature stress. Mean life is assumed to follow the Arrhenius relationship and analysis from the failure data obtained in the accelerated aging conditions.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.12
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• pp.85-91
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• 2021

In our daily life, artificial intelligence performs simple and complicated tasks like us, including operating mobile phones and working at homes and workplaces. Artificial intelligence is used in industrial technology for diagnosing various types of equipment using the machine learning technology. This study presents a fault mode effect analysis (FMEA) of start motors using machine learning and big data. Through multiple data collection, we observed that the primary failure of the start motor was caused by the melting of the magnetic switch inside the start motor causing it to fail. Long-short-term memory (LSTM) was used to diagnose the condition of the magnetic locations, and synthetic data were generated using the synthetic minority oversampling technique (SMOTE). This technique has the advantage of increasing the data accuracy. LSTM can also predict a start motor failure.

• Journal of the Korean Institute of Gas
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• v.27 no.2
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• pp.71-78
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• 2023

In general, electric submersible pumps (ESPs), which have an average life of 1.0 to 1.5 years, experience a decrease in performance and a reduction in life of the pump depending on oil and gas reservoir characteristics and operating conditions in wells. As the result, the failure of ESP causes high well workover costs due to retrieval and installation, and additional costs due to shut down. In this study, a flow loop system was designed and established to predict the life of ESP in long­term operation of oil and gas wells, and the life cycle data of ESP from the time of installation to the time of failure was acquired and analyzed. Among the data acquired from the system, flow rate, inlet and outlet temperature and pressure, and the data of the vibrator installed on the outside of ESP were analyzed, and then the performance status according to long-term operation was classified into five stages: normal, advice I, advice II, maintenance, and failed. Through the experiments, it was found that there was a difference in the data trend by stage during the long­term operation of the ESP, and then the condition of the ESP was diagnosed and the failure of the pump was predicted according to the operating time. The results derived from this study can be used to develop a failure prediction program and data analysis algorithm for monitoring the condition of ESPs operated in oil and gas wells.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.16 no.1
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• pp.56-64
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• 2020

The safety related heat exchangers have been evaluated for their performance during the operation of the nuclear power plant. The evaluation program for the safety related heat exchanger was developed in 2010 and used by KHNP based on EPRI TR-10739 algorithms. The spend fuel pool heat exchanger is one of the safety related heat exchanger in the nuclear power plant and also evaluated for their performance. Recently the performance evaluation for the spend fuel pool heat exchanger was not available because of the decreased heat in the spend fuel pool due to the long term overhaul. This paper analyzes the main cause of evaluation failure in the evaluation process and suggests the criteria for the heat exchanger performance evaluation during the long term overhaul.

• Journal of the Korean Academy of Esthetic Dentistry
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• v.10 no.1
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• pp.56-70
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• 2001

The use of resin-bonded fixed partial dentures described in the early 1980s caused an conservative way to preserve tooth structure in the restorative dental community. The treatment of patients with requires long term analysis of clinical application and basic research. Failure rates of these prosthesis ranged from 3% to 55%. These varieties were orginated by different techniques, materials, tooth preparation methods and diverse clinical situations. This article review was focused on the standard long term results and in vitro studies on bond strength between metal and teeth. From this, many useful clinical guidelines to RBFPD could be adopted to clinical dentistry. For successful results, careful case selection and good clinical skills are needed. And appropriate techniques for each situations should be adopted. Also, RBFPD using new materials like all-ceramics, FRC/Ceromer was introduced.