• IE interfaces
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• v.7 no.3
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• pp.155-168
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• 1994

In computer integrated manufacturing environment, tool management plays an important role in controlling tool performance for machining operations. Knowledge of tool behavior during the cutting process and effective tool-behavior prediction contribute to controlling machine costs by avioding production delays and off-target parts due to tool failure. The purpose of this paper is to review and develop the tool condition monitoring scheme for drilling operation to assure a fast corrective response to minimize the damage if tool failures occur. If one desires to maximize system through-put and product quality as well as tooling resources, within an economic environment, real-time tool sensing system and information processing system can be coupled to provide the necessary information for the effective tool management. The example is demonstrated as to drilling operation when the aluminum composites are drilled with carbide-tipped HSS drill bits. The example above is limited to the situation that the tool failure mode of drill bits is wear.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.2
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• pp.143-148
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• 2013

In FMEA, occurrence and detectability are not related to only failure modes itself but also their causes. It is assumed that any failure occurs after at least one cause corresponding to failure occurs in advance. Occurrence of the failure mode is described by occurrence time of its cause and elapsed time to the actual failure. Under the periodic monitoring plan, the monitoring interval is another factor to determine the detectability and occurrence of each failure mode. When a failure cause occurs, the failure does not occur if the cause is identified and remedied before it actually occurs. Under this situation, we construct an economic model for prioritizing failure modes. The loss function is based on the unfulfilled mission period. We also provide an optimal monitoring plan with an illustrative example.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2004.11a
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• pp.158-161
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• 2004

In recent, the automotive number of korea has risen above 14millions vehicles. The automotive was settled down goods haying to live. In a flood of this automotive the accuracy diagnosis for the vehicle certainly need for people referencing car. To do this diagnosis, the researcher has to experience many example in the field and need to system them. Expecially, the study for failure of the engine nearly research in the korea. When moving parts of engine no problem. In order to work, the engine must operate normality state. In this paper the purpose study the failure for the tribological example of engine.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.1
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• pp.70-75
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• 2007

This paper discusses condition based preventive replacement for deteriorating systems. The system continuouslydeteriorates in time and fails at any deterioration level which is always monitored, It is replaced at failure or atsome deteriorated level preventively before failure. The deterioration process is represented by a Weibulldistribution with a time-linear scale parameter. The cost rate function is formed considering replacement costand opportunity loss cost and deterioration dependent failure distribution, If the system has an increasingdeterioration dependent failure rate, the optimal deterioration level for preventive replacement can be determinedfrom minimizing the cost rate. An illustrative example is given for a Weibull deterioration dependent failuredistribution.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.35-38
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• 1995

We proposed in this paper a systematic way for analyzing discrete event dynamic systems to classify faults and failures quantitatively and to find tolerable fault event sequences embedded in the system. An automated failure diagnosis scheme with respect to the nominal normal operating event sequences and the supervisory control problem for tolerable fault event sequences is presented. Moreover the supervisor failure diagnosis problem with respect to the tolerable fault event sequences is considered. Finally, a plasma etching system example is presented.

• International Journal of Reliability and Applications
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• v.8 no.1
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• pp.83-94
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• 2007

In this paper, we consider a standby redundant structure with a function of switchover processing which may not be not perfect. The switchover processing is governed by a control module whose failure may cause the failure of the whole system. The parameters measuring such an effect of failure of the control module is included in our reliability model. We compute several reliability measures such as reliability function, failure rate, MTBF, mean residual life function, and the steady state availability. We also compare a single unit structure and the redundant structure with regard to those reliability measures. An example is given to illustrate our results.

• 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.

• Journal of the Korean Society of Safety
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• v.26 no.6
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• pp.104-110
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• 2011

In FMEA, the risk priority number(RPN) is used for risk evaluation on each failure mode. It is obtained by multiplying three components, i.e., severity, occurrence, and detectability of the corresponding failure mode. Each of the three components are usually determined on the basis of the past experience and technical knowledge. But this approach is not strictly objective in evaluating risk of a given failure mode and thus provide somewhat less scientific measure of risk. Assuming a homogeneous Poisson process for occurrence of the failures and causes, we propose a more scientific approach to evaluation of risk in FMEA. To quantify severity of each failure mode, the mission period is taken into consideration for the system. If the system faces no failure during its mission period, there are no losses. If any failure occurs during its mission period, the losses corresponding to the failure mode incurs. A longer remaining mission period is assumed to incur a larger loss. Detectability of each failure mode is then incorporated into the model assuming an exponential probability law for detection time of each failure cause. Based on the proposed model, an illustrative example and numerical analyses are provided.

• 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.