• Journal of Korean Institute of Industrial Engineers
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• v.26 no.2
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• pp.128-135
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• 2000

This paper considers a consecutive k-out-of-n:F system when the failure of a component in the system induces higher failure rate of the preceding survivor. The reliability, mean time to failure(MTTF), and average failure number of a consecutive k-out-of-n:F system are obtained, when the failure of a component increases the failure rate of the survivor which is working just before the failed component. Then the optimal number of consecutive failed components to minimize this long run average cost rate can be obtained. An example is considered to calculate the reliability, MTTF and average failure number of the system. And two procedures that find the optimal number of consecutive failed components are studied. Then, various cases of system parameters are also studied.

• International Journal of Reliability and Applications
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• v.12 no.2
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• pp.95-102
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• 2011

This paper uses the auto regression model to modeling failure number of a bus fleet. The fitted model can be used to predict the failure number in the future. A numerical example is presented to illustrate the modeling process and the appropriateness of the fitted model. At last, some possible applications of the model are discussed.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.10a
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• pp.363-366
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• 2008

It was accomplished that failure analysis not only failure numbers but also power system components every years. and these informations help power system operation considerably. power system equipment were occurred a break down by natural phenomenon and aging but it was not able to predict this failure number. But many papers and technical repots study for each equipment failure rate and reliability evaluation methods. so this paper show a failure number prediction whole power system component using Markov theory not each component failure probability. the result present a next month system failure number prediction.

• Proceedings of the Korean Reliability Society Conference
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• 2000.11a
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• pp.387-395
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• 2000

Circular consecutive-k-out-of-n:F system when the failure of component is dependent is studied. We assume that the failure of a component in the system increase the failure rate of the survivor which is working just before the failed component. In this case, a mean time to failure (MTTF), a average failure number of the system, and the expected cost per unit time are obtained. Then the minimum number of consecutive failed components to cause system failure to minimize the expected cost per unit time is determined as searching paths to system failure. And various numerical examples are studied.

• Journal of Welding and Joining
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• v.28 no.6
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• pp.45-50
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• 2010

Most of joining processes for machine and steel structure are performed by butt and fillet welding. The mechanical properties and fatigue strength of their welding zone can be effected largely by the differential of generated heat and changes of grain size according to thickness of material and number of passes in welding process. In this study, it was investigated about characteristics of fatigue failure according to thickness of material and number of passes in cruciform fillet weld zone as the basic study for safe and economic design of welding structures. Fracture modes in cruciform fillet weld zone are classified into toe failure and root failure according to non-penetrated depth. It can be accomplished economic design of welding structures considering fatigue strength when the penetrated depth in fillet weld zone is controled properly.

• Journal of the Korean Society of Safety
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• v.31 no.5
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• pp.7-15
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• 2016

The purpose of this paper is to carry out Failure Modes and Effects Analysis (FMEA) and use criticality in order to determine risk priority number of the components of electric power installations in Engineering college building of D university. In risk priority number, GROUP A had 7 failure modes; more specifically, Transfomer had 4 modes, Filter(C)(1 mode), LA(1 mode), and CB(MCCB)(1 mode), and thus 4 components had failure modes. In terms of criticality, high-grade group a total of 16 failure modes, and 7 components-LA(1 mode), CB(MCCB)(1 mode), MOF(2 modes), PT(1 mode), Transformer(7 modes), Cable(3 modes), and Filter(C)(1 mode)-had failure modes. Comparison of risk priority number and criticality was made. The components which had high risk priority number and high criticality were Transformer, Filter(C), LA, and CB(MCCB). The components which had high criticality were MOF and cable. In particular, Transformer(RPN: 4 modes, Criticality: 7 modes) was chosen as an intensive management component.

• Journal of Applied Reliability
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• v.17 no.1
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• pp.11-21
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• 2017

Purpose: The occurrence ranks of failure modes can come from the real failure but the severity ranks of failure modes require a highly subjective point of view of users. The severity ranks have to find more objective and scientific values. Methods: We found the optimal values by using the correlation analysis between failure mode effects and the criticality number like RPN (Risk Priority Number) in RCM. Result: This paper shows the result that verified whether the weighted values on each failure effect in criticality number calculation is suitable to the actual failures or not. To get the verification, it used the 5 year data and correlation analysis. Based on the analyzed result, We proposed the more suitable values. Conclusion: This correlation analysis approach can provide guidance of RCM analysis across many industries and situations.

• Journal of the Korean Society of Safety
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• v.31 no.2
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• pp.10-17
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• 2016

The purpose of this paper is to deduct components that are in the group of highest risk(top 10%). the group is conducted for classification into groups by values according to risk priority through risk priority number(RPN) of FMEA(Failure modes and effects analysis) sheet. Top 10% of failure mode among total potential failure modes(72 failure modes) of ESS included 5 BMS(battery included) failure modes, 1 invert failure mode, and 1 cable connectors failure mode in which BMS was highest. This is because ESS is connected to module, try, and lack in the battery part as an assembly of electronic information communication and is managed. BMS is mainly composed of the battery module and communication module. There is a junction box and numerous connectors that connect these two in which failure occurs most in the connector part and module itself. Finally, this paper proposes RPN by each step from the starting step of ESS design to installation and operation. Blackouts and electrical disasters can be prevented beforehand by managing and removing the deducted risk factors in prior.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.17-26
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• 1989

This paper is concerned with forecasting the existing number of errors in the computer software and optimizing the stopping time of the software test based upon the forecasted number of errors. The most commonly used models have assessed software reliability under the assumption that the software failure late is proportional to the current fault content of the software but invariant to time since software faults are independents of others and equally likely to cause a failure during testing. In practice, it has been observed that in many situations, the failure rate decrease. Hence, this paper proposes a mathematical model to describe testing situations where the failure rate of software limearly decreases proportional to testing time. The least square method is used to estimate parameters of the mathematical model. A cost model to optimize the software testing time is also proposed. In this cost mode two cost factors are considered. The first cost is to test execution cost directly proportional to test time and the second cost is the failure cost incurred after delivery of the software to user. The failure cost is assumed to be proportional to the number of errors remained in the software at the test stopping time. The optimal stopping time is determined to minimize the total cost, which is the sum of test execution cast and the failure cost. A numerical example is solved to illustrate the proposed procedure.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.11a
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• pp.527-534
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• 2000

136 cut slopes which extends from Namyangju to Chunchon city along the 46th national highway were investigated to analyze the influence factors affecting slope instability. Geologic and geotechnical conditions were examined and the detailed investigation were carried out for fifty five failed slopes. failure mode (wedge failure, planar failure, circular failure, sheet eroison and rock falls) are examined with respect to slope inclination, rock type, weathering grade and discontinuity patterns. It is suggested that the failure modes and their dimensions have relations to the morphology and geologic conditions of the slopes. Wedge failure has highest is the most frequent failure mode and falls, sheet erosions, planar failures and circular in descending order of failure percentage. Wedge failure is most dominant failure type over all lithology except quartzite formation. In slopes of well foliated and banded gneiss, failure ratio of wedge is up to 50% ca. Failure ratio(number of rock fall/number of total failure) of rock fall increases with increase fo slope inclinations and decrease of weathering grade. Dimension analyses of failed slopes shows wedge and circular failure has higher value of D/L and D/H than planar failure and sheet erosion.