• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.49-59
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• 2016

Naval combat system developed in-country is progressing at an alarming rate since 2000. ROK navy will be achieved all vessels that have combat system in the near future. The importance of System Engineering and Integrated Logistics Support based on reliability analysis is increasing. However, reliability analysis that everyone trusted and recognized is not enough and applied practically for development of Defense Acquisition Program. In particular, Existing Reliability Analysis is focusing on reliability index (Mean Time Between Failure (MTBF) etc.) for policy decision of defense improvement project. Most of the weapon system acquisition process applying in the exponential distribution simply persist unreality due to memoryless property. Critical failures are more important than simple faults to ship's operator. There are no confirmed cases of reliability analysis involved with critical failure that naval ship scheduler and operator concerned sensitively. Therefore, this study is focusing on Mean Time To Critical Failure (MTTCF), reliability on specific time and Operational Readiness Float (ORF) requirements related to critical failure of Patrol Killer Guided missile (PKG) combat system that is beginning of naval combat system developed in-country. Methods of analysis is applied parametric and non-parametric statistical techniques. It is compared to the estimates and proposed applications. The result of study shows that parametric and non-parametric estimators should be applied differently depending on purpose of utilization based on test of normality. For the first time, this study is offering Reliability of ROK Naval combat system to stakeholders involved with defense improvement project. Decision makers of defense improvement project have to active support and effort in this area for improvement of System Engineering.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.18
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• pp.8387-8390
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• 2016

Background: Treatment of biochemical failure after radical prostatectomy for prostate cancer is largely empirically based. The use of PSA kinetics has been used as a guide to determine local or systemic treatment of biochemical failure. We here compared PSA kinetics with detection of bone marrow micrometastasis as methods to determine local or systemic relapse. Materials and Methods: A transversal study was conducted of men with biochemical failure, defined as a serum PSA >0.2ng/ml after radical prostatectomy. Consecutive patients having undergone radical prostatectomy and with biochemical failure were enrolled and clinical and pathological details were recorded. Bone marrow biopsies were obtained from the iliac crest and touch prints made, micrometastasis (mM) being detected using anti-PSA. The clinical parameters of total serum PSA, PSA velocity, PSA doubling time and time to biochemical failure, age, Gleason score and pathological stage were registered. Results: A total of 147 men, mean age $71.6{\pm}8.2years$, with a median time to biochemical failure of 5.5 years (IQR 1.0-6.3 years) participated in the study. Bone marrow samples were positive for micrometastasis in 98/147 (67%) of patients at the time of biochemical failure. The results of bone marrow micrometastasis detected by immunocytochemistry were not concordant with local relapse as defined by PSA velocity, time to biochemical failure or Gleason score. In men with a PSA doubling time of < six months or a total serum PSA of >2,5ng/ml at the time of biochemical failure the detection of bone marrow micrometastasis was significantly higher. Conclusions: The detection of bone marrow micrometastasis could be useful in defining systemic relapse, this minimally invasive procedure warranting further studies with a larger group of patients.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.11
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• pp.548-556
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• 2005

Reliability evaluation of power distribution system is very important to both power utilities and customers. It present the probabilistic number and duration of interruption such as failure rate, SATDI, SAIFI, and CAIDI. However, it has a fatal weakness at reliability index because of accuracy of failure rate. In this paper, the Time-varying Failure Rate(TFR) of power distribution system equipment is extracted from the recorded failure data of KEPCO(Korea Electric Power Corporation) in Korea. For TFR extraction, it is used that the fault data accumulated by KEPCO during 10 years. The TFR is approximated to bathtub curve using the exponential(random failure) and Weibull(aging failure) distribution function. In addition, Kaplan-Meier estimation is applied to TFR extraction because of incomplete failure data of KEPCO. Finally, Probability plot and regression analysis is applied. It is presented that the extracted TFR is more effective and useful than Mean Failure Rate(MfR) through the comparison between TFR and MFR

• Journal of IKEEE
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• v.23 no.1
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• pp.254-260
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• 2019

The failure rate of bidirectional dc-to-dc converter is predicted through the failure mode and effect analysis (FMEA) and the fault-tree analysis (FTA) considering the operational risk. In order to increase the driving voltage of the electric vehicle efficiently, the bidirectional converter is attached to the front of the inverter. It has a boost mode for discharging battery power to the dc-link capacitor and a buck mode for charging the regenerative power to the battery. Based on the results of the FMEA considering the operating characteristics of the bidirectional converter, the fault-tree is designed considering the risk of the converter. After setting the design parameters for the MCU for the electric vehicle, we analyze the failure rate of the capacitor due to the output voltage ripple and the inductor component failure rate due to the inductor current ripple. In addition, we obtain the failure rate of major parts according to operating temperature using MIL-HDBK-217F. Finally, the failure rate and the mean time between failures (MTBF) of the converter are predicted by reflecting the part failure rate to the basic event of the fault-tree.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.18-24
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• 2020

This research conducted an the failure analysis was performed based on the failure and operation data for Seven years using the Reliability, Availability, Maintainability, and Safety(RAMS) constructed at the operation stage after the opening of the D urban railway. therefore, the risk priority was selected for failure frequency component within the door system that showed high failure. Finally, the goal was to suggest ways to improve the door system. For this purpose, the analysis of thermal characteristics of failed components such as Door Control Unit(DCU) in the door system based on the Seven-year failure analysis data of RAMS was performed. These results were applied to the main component exchange cycle of the door unit, the mean time between failure(MTBF) and mean kilometer between failure(MKBF) values of RAMS increased by 26% in 2017-2018 when the improvement measures were taken, and the MTBF value of DCU was 300,000 hours, which was a 57% improvement in reliability. The results of this thesis identify potential enhancements in reliability and improvements in maintenance of the door system that, if implemented, would contribute to train safety and reduce instances of failure in the future.

• 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.

• International Journal of Reliability and Applications
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• v.11 no.2
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• pp.123-138
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• 2010

This paper investigates a mathematical model of a system composed of two non-identical unit parallel system with common-cause failure, critical human error, non-critical human error, preventive maintenance and two type of repair, i.e. cheaper and costlier. This system goes for preventive maintenance at random epochs. We assume that the failure, repair and maintenance times are independent random variables. The failure rates, repair rates and preventive maintenance rate are constant for each unit. The system is analyzed by using the graphical evaluation and review technique (GERT) to obtain various related measures and we study the effect of the preventive maintenance preventive maintenance on the system performance. Certain important results have been derived as special cases. The plots for the mean time to system failure and the steady-state availability A(${\infty}$) of the system are drawn for different parametric values.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1989-1992
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• 2009

Maintenance is classified preventive maintenance before performing equipment failure and corrective maintenance after performing equipment failure. In preventive maintenance, we may analyze the failure data to end from beginning of equipment and allocate maintenance method and calculate maintenance cycle quantitatively by the failure data analysis. So, it has a merit to reduce system maintenance cost and to operate effectively but, it require high cost in system introducing and continuous operation to end of system. In corrective maintenance, we may calculate MTTR(mean time to repair) quantitatively based on function failure time. it can be based on establishing maintenance system for operation efficiency. In this paper, we may reflect the MTTR for the onboard equipped in Tilting train to establish maintenance system for Tilting train operation efficiency.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.1007-1015
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• 2013

A stochastic probability model based on the non-homogeneous Poisson process is represented that can correctly analyze the time-dependent linear and nonlinear behaviors of total damage over the occurrence process of loads. Introducing several types of damage intensity functions, the probability of failure and the total damage with respect to mean time to failure has been investigated in detail. Taking particularly the limit state to be the random variables followed with a distribution function, the uncertainty of that would be taken into consideration in this paper. In addition, the stochastic probability model has been straightforwardly applied to the rubble-mound breakwaters with the definition of damage level about the erosion of armor units. The probability of failure and the nonlinear total damage with respect to mean time to failure has been analyzed with the damage intensity functions for armor units estimated by fitting the expected total damage to the experimental datum. Based on the present results from the stochastic probability model, the preventive management for the armor units of the rubble-mound breakwaters would be suggested to make a decision on the repairing time and the minimum amounts repaired quantitatively.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.761-769
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• 2002

Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed. The testing time on the right is truncated in this model. The instantaneous failure rate, mean-value function, error detection rate, reliability of the software, estimation of parameters and the simple applications of this model are discussed .