• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.41 no.5
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• pp.240-245
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• 2015

Objectives: This study was performed to evaluate patterns of failure time after insertion, failure rate according to loading time after insertion, and the patterns of failure after loading. Materials and Methods: A total of 331 mini-implants were classified into the non-failure group (NFG) and failure group (FG), which was divided into failed group before loading (FGB) and failed group after loading (FGA). Orthodontic force was applied to both the NFG and FGA. Failed mini-implants after insertion, ratio of FGA to NFG according to loading time after insertion, and failed mini-implants according to failed time after loading were analyzed. Results: Percentages of failed mini-implants after insertion were 15.79%, 36.84%, 12.28%, and 10.53% at 4, 8, 12, and 16 weeks, respectively. Mini-implant failure demonstrated a peak from 4 to 5 weeks after insertion. The failure rates according to loading time after insertion were 13.56%, 8.97%, 11.32%, and 5.00% at 4, 8, 12, and 16 weeks, respectively. Percentages of failed mini-implants after loading were 13.79%, 24.14%, 20.69%, and 6.9% at 4, 8, 12, and 16 weeks, respectively. Conclusion: Mini-implant stability is typically acquired 12 to 16 weeks after insertion, and immediate loading can cause failure of the mini-implant. Failure after loading was observed during the first 12 weeks.

• 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.11 no.2
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• pp.167-176
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• 2011

This paper introduces models for preventive maintenance policies and considers periodic preventive maintenance policy with minimal repair when the failure of system occurs. It is assumed that minimal repairs do not change the failure rate of the system. The failure rate under prevention maintenance received an effect by a previously prevention maintenance and the slope of failure rate increases the model where it considered. Also the start point of failure rate under prevention maintenance considers the degradation of system and that it increases quotient, it assumed. Per unit time it bought an expectation cost from under this prevention maintenance policy. We obtain the optimal periodic time and the number for the periodic preventive maintenance by using Nakagawa's Algorithm, which minimizes the expected cost per unit time.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.121-130
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• 2021

Cascading failure is the main cause of large blackouts in electrical power systems; this paper analyzes a cascading failure in Hanbit nuclear power plant unit two (2) caused by a circuit breaker (CB) operation failure. This malfunction has been expanded to the loss of offsite power (LOOP). In this study, current practices are reviewed and then the methodologies of how to prevent cascading failures in protection power systems are introduced. An overview on the implementation of IEC61850 GOOSE messaging-based zone selective interlocking (ZSI) scheme as key solution is proposed. In consideration of ZSI blocking time, all influencing factors such as circuit breaker opening time, relay I/O response time and messages travelling time in the communication network should be taken into account. The purpose of this paper is to elaborate on the effect of cascading failure in NPP electrical power protection system and propose preventive actions for this failures. Finally, the expected advantages and challenges are elaborated.

• ETRI Journal
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• v.36 no.6
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• pp.1023-1031
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• 2014

Failure analysis is necessary to clarify the root cause of a failure, predict the next time a failure may occur, and improve the performance and reliability of a system. However, it is not an easy task to analyze and interpret failure data, especially for complex systems. Usually, these data are represented using many attributes, and sometimes they are inconsistent and ambiguous. In this paper, we present a scalable approach for the analysis and interpretation of failure data of high-performance computing systems. The approach employs rough sets theory (RST) for this task. The application of RST to a large publicly available set of failure data highlights the main attributes responsible for the root cause of a failure. In addition, it is used to analyze other failure characteristics, such as time between failures, repair times, workload running on a failed node, and failure category. Experimental results show the scalability of the presented approach and its ability to reveal dependencies among different failure characteristics.

• Communications for Statistical Applications and Methods
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• v.23 no.4
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• pp.335-341
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• 2016

Interval censored failure time data often occurs in an observational study where a subject is followed periodically. Instead of observing an exact failure time, two inspection times that include it are made available. Several methods have been suggested to analyze interval censored failure time data (Sun, 2006). In this article, we are concerned with a binary time-varying covariate whose changing time is interval censored. A modified estimating equation is proposed by extending the approach suggested in the presence of a missing covariate. Based on simulation results, the proposed method shows a better performance than other simple imputation methods. ACTG 181 dataset were analyzed as a real example.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.9-11
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• 2006

This paper suggests a revision method for historical fault data using Proportional Aging Reduction(PAR) to consider maintenance effect in time-varying failure rate. In order to product time-varying failure rate, the historical fault data are necessary. However, the maintenance record could be left out in historical data by spot operator's mistake. In this case, the failure rate is produced less than the average failure rate for increasing equipments' life-time by maintenance effect. Hence, it is necessary for new time-varying failure rate to extract maintenance effect from the existing fault data. In this paper, the revision method to reduce equipments' life-time, adversely using PAR among three techniques to consider maintenance effect.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.139-146
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• 1995

This study is concerned with cost analysis in periodic maintenance policy. Generally periodic maintenance policy in which item is repaired periodic interval times. And in the article minimal repair is considered. Minimal repair means that if a unit fails, unit is instantaneously restored to same hazard rate curve as before failure. In the paper periodic maintenance policy with minimal repair is as follows; Operating unit is periodically replaced in periodic maintenance time, if a failure occurs between minimal repair and periodic maintenance time, unit is replaced by a spate until the periodic time comes. Also unit undergoes minimal repair at failures in minimal-repair-for-failure interval. Then total expected cost per unit time is calculated according to maintenance period and scale parameter of failure distribution. Total cost factors ate included operating, fixed, minimal repair, periodic maintenance and replacement cost Numerical example is shown in which failure time of system has erlang distribution.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.287-295
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• 1995

This paper is concerned with cost analysis model in periodic maintenance policy. Generally periodic maintenance policy in which item is repaired periodic interval times. And in the article minimal repair is considered. Mimimal repair means that if a unit fails, unit is instantaneously restored to same hazard rate curve as before failure. In the paper periodic maintenance policy with minimal repair is as follows; Operating unit is periodically replaced in periodic maintenance time, if a failure occurs between minimal repair and periodic maintenance time, unit is replaced by a new item until tile periodic maintenance time comes. Also unit undergoes minimal repair at failures in minimal-repair-for-failure interval. Then total expected cost per unit time is calculated according to scale parameter of failure distribution. Maintenance cost factors are included operating, fixed, minimal repair, periodic maintenance and new item replacement cost. Numerical example is shown in which failure time of system has weibull distribution.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.11
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• pp.476-484
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• 2006

The failure prediction and preventive maintenance for the equipment of nuclear power plant area using reliability-centered maintenance have been grown. On the other hand, the maintenance for power distribution system consists of time-based maintenance mainly. In this paper, the new maintenance algorithms for power distribution system are developed considering reliability indices. First of all, Time-varying failure rates are extracted from data accumulated at KEPCO using exponential distribution function and weibull distribution function. Next, based on the extracted failure rate, reliability for real power distribution system is evaluated for applying the effective maintenance algorithm which is the analytic method deciding the maintenance point of time and searching the feeder affecting the specific customer. Also the algorithm deciding the maintenance priority order are presented based on sensitivity analysis and equipment investment plan are analyzed through the presented algorithm at real power distribution system.