• Journal of Applied Reliability
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• v.11 no.4
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• pp.343-356
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• 2011

This paper proposes an accelerated life evaluation of drive shaft. The life test of drive shaft for independent suspension type AWD vehicle should be performed by use of the least test sample because many number of samples can't be used for the test because of its mass capacity and high price. We calculated the no failure test time by application of no failure test concept, and the already performed test data for drive shaft are applied for some kinds of reliability coefficients which are needed for calculation of life test time. And, for analysis of real driving condition of vehicle, the load spectrum is prepared using the needed road condition and vehicle data. The inverse power model is used for accelerated life test. The equivalent torque of load spectrum is achieved by use of Miner's Rule, and then the final accelerating condition is determined by decision of the accelerated test torque. This paper shows that the accelerated life test results corresponds with the target life and the proposed life test method can be very well applied to no failure life test for mass capacity machinery components.

• Journal of Applied Reliability
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• v.16 no.1
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• pp.56-63
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• 2016

Purpose: The purpose of this study is to point out that the Kaplan-Meier method is not valid to calculate the survival probability or failure probability (risk) in the presence of competing risks and to introduce more valid method of cumulative incidence function. Methods: Survival analysis methods have been widely used in biostatistics division. However the same methods have not been utilized in reliability division. Especially competing risks cases, where several causes of failure occur and the occurrence of one event precludes the occurrence of the other events, are scattered in reliability field. But they are not noticed in the realm of reliability expertism or they are analysed in the wrong way. Specifically Kaplan-Meier method which assumes that the censoring times and failure times are independent is used to calculate the probability of failure in the presence of competing risks, thereby overestimating the real probability of failure. Hence, cumulative incidence function is introduced and sample competing risks data are analysed using cumulative incidence function and some graphs. Finally comparison of cumulative incidence functions and regression type analysis are mentioned briefly. Results: Cumulative incidence function is used to calculate the survival probability or failure probability (risk) in the presence of competing risks and some useful graphs depicting the failure trend over the lifetime are introduced. Conclusion: This paper shows that Kaplan-Meier method is not appropriate for the evaluation of survival or failure over the course of lifetime. In stead, cumulative incidence function is shown to be useful. Some graphs using the cumulative incidence functions are also shown to be informative.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.2
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• pp.164-176
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• 1991

This paper considers the model of a k-out-of-n :G system with non-identical components which are subject to both forced and planned outages. For the forced outages, it assumes that there are the independent and common-cause outage events causing component failures. Then, the objective is to derive the upper and lower bounds on the mean operating time between system failures in the ample-server model. In addtion, the mean system failure times are also considered.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.647-655
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• 2006

In this paper, we consider multiple comparisons for the ratio of the failure rates in two components system that the lifetimes of the components have independent exponential distributions. Also we suggest Bayesian multiple comparisons procedure based on fractional Bayes factor when noninformative priors are applied for the parameters. Finally, we give numerical examples to illustrate our procedure.

• Journal of Korean Society for Quality Management
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• v.42 no.1
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• pp.43-61
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• 2014

Purpose: This study identifies preventive measures for VOC management by analyzing the causes and effects of factors that contribute to high risk service failure using FMEA on KORAIL VOC data. Methods: Two research methods were used. First, a Risk Priority Number (RPN) was assigned to each KORAIL VOC based on Failure Mode and Effect Analysis (FMEA). Second, multiple regression analysis was run with RPN factors that include severity, occurrence, and detection as the independent variables and customer dissatisfaction as the dependent variable. Results: Multiple regression analysis showed that RPN factors including severity, occurrence, and detection had significantly positive relationship with customer dissatisfaction. Based on these results, an FMEA was performed on VOC categories with high RPN for railroad stations including platform, ticketing, ticket verification, parking, and escalator, and VOC categories with high RPN for trains including entrance doors, cafes, air quality, announcement, and ticket verification. Conclusion: This study has practical implications to service failure management. A priority order using FMEA was established for the list of customer dissatisfactions that should be addressed to actively manage service failure, and strategies for tackling this priority list are offered.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.981-988
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• 2023

A seismic event caused an accident at the Fukushima Nuclear Power Plant, which further resulted in simultaneous accidents at several units. Consequently, this incident has aroused great interest in the safety of nuclear power plants worldwide. A reasonable safety evaluation of such an external event should appropriately consider the correlation between SSCs (structures, systems, and components) and the probability of failure. However, a probabilistic safety assessment in current nuclear industries is performed conservatively, assuming that the failure correlation between SSCs is independent or completely dependent. This is an extreme assumption; a reasonable risk can be calculated, or risk-based decision-making can be conducted only when the appropriate failure correlation between SSCs is considered. Thus, this study analyzed the effect of the failure correlation of SSCs on the safety of the system to realize rational safety assessment and decision-making. Consequently, the impact on the system differs according to the size of the failure probability of the SSCs and the AND and OR conditions.

• Geomechanics and Engineering
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• v.15 no.6
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• pp.1183-1191
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• 2018

Reliability analysis is generally regarded as the most appropriate method when uncertainties are taken into account in slope designs. With the help of limit analysis, probability evaluation for three-dimensional rock slope stability was conducted based upon the Mote Carlo method. The nonlinear Hoek-Brown failure criterion was employed to reflect the practical strength characteristics of rock mass. A form of stability factor is used to perform reliability analysis for rock slopes. Results show that the variation of strength uncertainties has significant influence on probability of failure for rock slopes, as well as strength constants. It is found that the relationship between probability of failure and mean safety factor is independent of the magnitudes of input parameters but relative to the variability of variables. Due to the phenomenon, curves displaying this relationship can provide guidance for designers to obtain factor of safety according to required failure probability.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.151-160
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• 2022

The total system is composed of the main system (MS) and the failure detection equipment (FDE) which detects failures of MS. The analysis of system reliability is performed when the failure of FDE is possible. Several repair policies are considered to determine the order of repair of failed systems, which are sequential repair (SQ), priority repair (PR), independent repair (ID), and simultaneous repair (SM). The states of MS-FDE systems are represented by Markov models according to repair policies and the main purpose of this paper is to derive the system availabilities of the Markov models. Analytical solutions of the stationary equations are derived for the Markov models and the system availabilities are immediately determined using the stationary solutions. A simple illustrative example is discussed for the comparison of availability values of the repair policies considered in this paper.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.7
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• pp.401-406
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• 2003

Electric power industries in several countries are currently undergoing major changes, mainly represented by the privatizations of the power plants and distribution systems. Reliable operations of the power plants directly contribute to the revenue increases of the generation companies in such competitive environments. Strategic optimizations should be performed between the levels of the reliabilities to be maintained and the various preventive maintenance costs, which require the accurate estimations of the power plant reliabilities. However, accurate estimations of the power plant reliabilities are often limited by the lack of accurate power plant failure data. A power plant is not supposed to be failed that often. And if it fails, its impact upon the power system stability is quite substantial in most cases, setting aside the significant revenue losses and lowered company images. Reliability assessment is also important for Independent System Operators(ISO) or Market Operators to properly assess the level of needed compensations for the installed capacity based on the availability of the generation plants. In this paper, we present a power plant reliability estimation technique that can be applied when the failure data is insufficient. Median rank and Weibull distribution are used to accommodate such insufficiency. The Median rank is utilized to derive the cumulative failure probability for each ordered failure. The Weibull distribution is used because of its flexibility of accommodating several different distribution types based on the shape parameter values. The proposed method is applied to small size failure data and its application potential is demonstrated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2457-2464
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• 2013

In this paper, we design and analyze a mutual exclusion algorithm, based on the Token and Failure detector, in asynchronous distributed systems. A Failure Detector is an independent module that detects and reports crashes of other processes. There are some of advantages in rewriting the Token-based ME algorithm using a Failure Detector. We show that the Token-based ME algorithm, when using Failure Detector, is more effectively implemented than the classic Token-based ME algorithm for synchronous distributed systems.