• Korean Journal of Computational Design and Engineering
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• v.18 no.4
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• pp.250-257
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• 2013

This paper introduces a failure analysis procedure that underpins real-time fault prognosis. In the previous study, we developed a systematic eventization procedure which makes it possible to reduce the original data size into a manageable one in the form of event logs and eventually to extract failure patterns efficiently from the reduced data. Failure patterns are then extracted in the form of event sequences by sequence-mining algorithms, (e.g. FP-Tree algorithm). Extracted patterns are stored in a failure pattern library, and eventually, we use the stored failure pattern information to predict potential failures. The two practical case studies (marine diesel engine and SIRIUS-II car engine) provide empirical support for the performance of the proposed failure analysis procedure. This procedure can be easily extended for wide application fields of failure analysis such as vehicle and machine diagnostics. Furthermore, it can be applied to human health monitoring & prognosis, so that human body signals could be efficiently analyzed.

• Korean Circulation Journal
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• v.54 no.7
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• pp.363-381
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• 2024

With global aging, the number of patients with heart failure has increased markedly. Heart failure is a complex condition intricately associated with aging, organ damage, frailty, and cognitive decline, resulting in a poor prognosis. The relationship among frailty, sarcopenia, cachexia, malnutrition, and heart failure has recently received considerable attention. Although these conditions are distinct, they often exhibit a remarkably close relationship. Overlapping diagnostic criteria have been observed in the recently proposed guidelines and position statements, suggesting that several of these conditions may coexist in patients with heart failure. Therefore, a comprehensive understanding of these conditions is essential, and interventions must not only target these conditions individually, but also provide comprehensive management strategies. This review article provides an overview of the epidemiology, diagnostic methods, overlap, and prognosis of frailty, sarcopenia, cachexia, and malnutrition in patients with heart failure, incorporating insights from the FRAGILEHF study data. Additionally, based on existing literature, this article discusses the impact of these conditions on the effectiveness of guideline-directed medical therapy for patients with heart failure. While recognizing these conditions early and promptly implementing interventions may be advantageous, further data, particularly from well-powered, large-scale, randomized controlled trials, are necessary to refine personalized treatment strategies for patients with heart failure.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.326-327
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• 2011

Failure rate serves as a pivotal role in reliability study. When the system operates, failure datum of the system reflects the actual operating environment. Therefore, when we estimate the system's with the component failure data, we can find the more exact failure rate that reflected the system's operating environment. In this paper, we use the components' fault data and find out failure rate.

• Journal of the Korean Society of Safety
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• v.33 no.3
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• pp.83-91
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• 2018

This paper suggests a weibull time delay model to evaluate failure risks in FMEA(failure modes and effects analysis). Assuming three types of loss functions for delayed time in failure cause detection, the risk of each failure cause is evaluated as its occurring frequency and expected loss. Since the closed form solution of the risk metric cannot be obtained, a statistical computer software R program is used for numerical calculation. When the occurrence and detection times have a common shape parameter, though, some simple results of mathematical derivation are also available. As an enormous quantity of field data becomes available under recent progress of data acquisition system, the proposed risk metric will provide a more practical and reasonable tool for evaluating the risks of failure causes in FMEA.

• Journal of Applied Reliability
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• v.10 no.1
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• pp.1-9
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• 2010

In general, the performance of a component degrades as time goes by and failure of a component occurs when the performance degradation reaches a pre-specified level. It is difficult to obtain the failure time distribution data or the necessary number of failure data especially for the metal or machine part. Thus, a design of reliability qualification test based on performance distribution is more effective than failure time distribution. In this study, a performance-based reliability qualification test is developed and a numerical example is provided to illustrate the use of the developed reliability qualification test. This approach could be applied to many kinds of metal or machine part whose magnitude of strength could not be evaluated during at any random points but judgement can be made by only failure of the part. Besides, it is also possible that any parts which have a similar failure characteristics could be applicable to the developed reliability qualification test.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.3
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• pp.43-59
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• 1995

This paper presents a method for estimating the population variability distribution of the failure parameter (failure rate or failure probability) for each failure mode considered in PSA (Probabilistic Safety Assessment). We focus on the utilization of generic estimates from various industry compendia for the estimation. The estimates are complicated statistics of failure data from plants. When the failure data referred in two or more sources are overlapped, dependency occurs among the estimates provided by the sources. This type of problem is first addressed in this paper. We propose methods based on ML-II estimation in Bayesian framework and discuss the characteristics of the proposed estimators. The proposed methods are easy to apply in real field. Numerical examples are also provided.

• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.366-374
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• 2014

This study assessed and analysed a result of a product design experiment through Product Data Analytics (PDA), to find reasons for failure of some projects in the experiment. PDA is a computer-based data analysis that uses Product Data Management (PDM) databases as its operational databases. The study examines 20 product design projects in the experiment, which are prepared to follow same product development process by using an identical PDM system. The design result in the PDM database is assessed and analysed by On-Line Analytical Processing (OLAP) and data mining tools in PDA. The assesment and analysis reveals the lateness in creation of 3D CAD models as the main reason of the failure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.30-39
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• 2024

This study introduces a novel approach for identifying potential failure risks in missile manufacturing by leveraging Quality Inspection Management (QIM) data to address the challenges presented by a dataset comprising 666 variables and data imbalances. The utilization of the SMOTE for data augmentation and Lasso Regression for dimensionality reduction, followed by the application of a Random Forest model, results in a 99.40% accuracy rate in classifying missiles with a high likelihood of failure. Such measures enable the preemptive identification of missiles at a heightened risk of failure, thereby mitigating the risk of field failures and enhancing missile life. The integration of Lasso Regression and Random Forest is employed to pinpoint critical variables and test items that significantly impact failure, with a particular emphasis on variables related to performance and connection resistance. Moreover, the research highlights the potential for broadening the scope of data-driven decision-making within quality control systems, including the refinement of maintenance strategies and the adjustment of control limits for essential test items.

• Geotechnical Engineering
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• v.12 no.6
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• pp.37-50
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• 1996

In this study, we collected data through the investigation of rock slopes of highway. By analyzing the collected data, the main factors of rock slope failure were studied. We studied on the failure types and scales according to rock types and geological structures in many rock slopes of highway. As a result, it was shown that many failed slopes were distributed in the areas of Cretaceous sedimentary rocks of south-eastern part in the Korean Peninsula and the Gneiss Complex in both Kyonggi-Do and Kangwon-Do. According to rock types, the following slope failure types were shown : that igneous rocks had the types of rock fall, plane failure, soil erosion and circular failure but had low failure frequency, and sedimentary rocks had predominantly the type of plane failure. Metamorphic rock showed the types of circular failure, wedge failure and plane failure due to poor rock qualities . According to geological structures, the following slope failure types were shown slope failure in igneous rocks was caused by joints, and in sedimentary rocks by bedding plane, and in metamorphic rocks by faults and poor rock qualities.