• Journal of Korean Society for Quality Management
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• v.22 no.4
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• pp.59-78
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• 1994

In some observational studies, we have often random censoring model. However, the data available may be partially observable censored data consisting of the observed failure times and only those nonfailure times which are subject to follow up. In this paper, we present an extension of the problem of partially parametric estimation of the survival function to such partially observable censored data. The proposed estimator treats the observed failure times nonparametrically and uses a parametric model only for those nonfailure times which are subject to follow-up. We discuss the motivation and construction of the proposed estimator and investigate the limiting properties of the proposed estimator such as asymptotic normality. Also, when the assumed parametric model is exponential, the asymptotic variance of the estimator is obtained. Furthermore, an example is given to compare the proposed estimator with the modified Kaplan Meier(MKM) estimator. From the results, it is shown that the relative efficiency of the proposed estimator is higher than that of the MKM estimator in the follow-up study with increasing time.

• International Journal of Reliability and Applications
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• v.15 no.1
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• pp.51-64
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• 2014

This paper develops a warranty cost model for complex systems with imperfect repair within a warranty period by addressing a practical case that the first inter-failure interval is longer than any other inter-failure intervals. The product is in its best condition before the first failure if repair is imperfect. After the imperfect repair, other inter-failure intervals which are explained by renewal processes, are stochastically smaller than the first inter-failure interval. Based on this idea, we suggest the failure-interval-failure-criterion model. In this model, we consider two random variables, X and Y where X represents failure intervals and Y represents failure criterion. We also obtain the distribution of the number of failures and conduct the warranty cost analysis. We investigate different types of warranty cost models, reliabilities and other measures for various systems including series-parallel configurations. Several numerical examples are discussed to demonstrate the applicability of the methodologies derived in the paper.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.351-358
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• 1999

The structural responses of underground structures are examined in probability by using the elasto-plastic stochastic finite element method in which the spatial distributions of material properties are assumed to be stochastic fields. In addition, the adaptive importance sampling method using the response surface technique is used to improve simulation efficiency. The method is found to provide appropriate information although the nonlinear Limit State involves a large number of basic random variables and the failure probability is small. The probability of plastic local failures around an excavated area is effectively evaluated and the reliability for the limit displacement of the ground is investigated. It is demonstrated that the adaptive importance sampling method can be very efficiently used to evaluate the reliability of a large scale stochastic finite element model, such as the underground structures located in the multi-layered ground.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.11a
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• pp.161-165
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• 2005

In this paper, we observed degradation characteristics of luminous flux for new light source. Because degradation tests can be a useful tool for assessing the reliability when few or even no failures are expected in a life tests. And we use a simple random coefficient degradation model to induce most suitable equation of degradation. As a result, exponential distribution and equation is best suitable model for new light source.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1482-1488
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• 2014

The reliability evaluation of the electrical distribution networks (EDN) requires sufficient consideration of the effects of planned outages. The planned outages of the EDN can be divided, by outage models and their effects on the reliability into two major categories: by equipment and by feeder. After studying the characteristics of different categories of planned outages, this paper expands the classification of load points by outage time from 4 types to 7 types and defines corresponding reliability parameters for the different types. By using the section algorithm, this paper proposes a reliability evaluation technique of EDN considering equipment random failures and two categories of planned outages. The proposed technique has been applied to the RBTS-BUS6 test system and some practical EDNs in China. The study results demonstrate that the proposed technique is of higher practical value and can be used for evaluating the reliability performance of EDN more efficiently considering the planned outages.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.146-154
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• 2019

An improved principal component analysis (PCA) method is applied for sensor fault detection and isolation (FDI) in a nuclear power plant (NPP) in this paper. Data pre-processing and false alarm reducing methods are combined with general PCA method to improve the model performance in practice. In data pre-processing, singular points and random fluctuations in the original data are eliminated with various techniques respectively. In fault detecting, a statistics-based method is proposed to reduce the false alarms of $T^2$ and Q statistics. Finally, the effects of the proposed data pre-processing and false alarm reducing techniques are evaluated with sensor measurements from a real NPP. They are proved to be greatly beneficial to the improvement on the reliability and stability of PCA model. Meanwhile various sensor faults are imposed to normal measurements to test the FDI ability of the PCA model. Simulation results show that the proposed PCA model presents favorable performance on the FDI of sensors no matter with major or small failures.

• Ocean Systems Engineering
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• v.9 no.2
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• pp.135-155
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• 2019

One of the safest and the most economical methods to transfer oil and gas is pipeline system. Prediction and prevention of pipeline failures during its assessed lifecycle has considerable importance. The dropped object is one of the accidental scenarios in the failure of the submarine pipelines. In this paper, using Monte Carlo Sampling, the probability of damage to a submarine pipeline due to a box-shaped dropped object has been calculated in terms of dropped object impact frequency and energy transfer according to the DNV-RP-F107. Finally, Reliability sensitivity analysis considering random variables is carried out to determine the effect intensity of each parameter on damage probability. It is concluded that impact area and drag coefficient have the highest sensitivity and mass and add mass coefficient have the lowest sensitivity on probability of failure.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.56-61
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• 2021

Neighbor path selection is to pre-select alternate routes in case geographically correlated failures occur simultaneously on the communication network. Conventional heuristic-based algorithms no longer improve solutions because they cannot sufficiently utilize historical failure information. We present a novel solution model for neighbor path selection by using machine learning technique. Our proposed machine learning neighbor path selection (ML-NPS) model is composed of five modules- random graph generation, data set creation, machine learning modeling, neighbor path prediction, and path information acquisition. It is implemented by Python with Keras on Tensorflow and executed on the tiny computer, Raspberry PI 4B. Performance evaluations via numerical simulation show that the neighbor path communication success probability of our model is better than that of the conventional heuristic by 26% on the average.

• Journal of the Korea Safety Management & Science
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• v.15 no.4
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• pp.161-169
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• 2013

Due to the recent advances in technology, the systems are becoming more demanding in terms of functionality and implementation complexity. Therefore, when system failures are involved in such complex systems, the effects of the related safety issues can also be more serious, thereby causing in the worst case irrecoverable hazards on both human being and properties. This fact can be witnessed in the recent rail systems accidents. In general, the accidents can be attributed to the systematic failure or the random failure. The latter is due to the aging or unsatisfied quality of the parts used in implementation or some unexpected external cause that would otherwise result in accidents whereas the former is usually related to incomplete systems design. As the systems are becoming more complex, so are the systematic failures. The objective of the paper is to study an approach to solving the systematic failure. To do so, at first the system design process is augmented by the functional safety activities that are suggested in the standard IEC 61508. Analyzing the artifacts of the integrated process yields the traceability, which satisfies the requirements for reduction of systematic failure as provided in ISO 26262. In order to reduce systematic failure, the results are utilized in the conceptual design stage of systems development in which systems requirements are generated and functional architecture is developed.

• Geomechanics and Engineering
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• v.14 no.3
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• pp.271-281
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• 2018

A jointed rock slope stability evaluation was simulated by a discontinuous deformation analysis numerical method to investigate the process and safety factors for different crack distributions and different overloading situations. An optimized method using Discontinuous Deformation Analysis for Rock Failure (DDARF) is presented to perform numerical investigations on the jointed rock slope stability evaluation of the Dagangshan hydropower station. During the pre-processing of establishing the numerical model, an integrated software system including AutoCAD, Screen Capture, and Excel is adopted to facilitate the implementation of the numerical model with random joint network. These optimizations during the pre-processing stage of DDARF can remarkably improve the simulation efficiency, making it possible for complex model calculation. In the numerical investigations on the jointed rock slope stability evaluations using the optimized DDARF, three calculation schemes have been taken into account in the numerical model: (I) no joint; (II) two sets of regular parallel joints; and (III) multiple sets of random joints. This model is capable of replicating the entire processes including crack initiation, propagation, formation of shear zones, and local failures, and thus is able to provide constructive suggestions to supporting schemes for the slope. Meanwhile, the overloading numerical simulations under the same three schemes have also been performed. Overloading safety factors of the three schemes are 5.68, 2.42 and 1.39, respectively, which are obtained by analyzing the displacement evolutions of key monitoring points during overloading.