• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.145-152
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• 2019

All machines deteriorate in performance over time. The phenomenon that causes such performance degradation is called deterioration. Due to the deterioration, the process mean of the machine shifts, process variance increases due to the expansion of separate interval, and the failure rate of the machine increases. The maintenance model is a matter of determining the timing of preventive maintenance that minimizes the total cost per wear between the relation to the increasing production cost and the decreasing maintenance cost. The essential requirement of this model is that the preventive maintenance cost is less than the failure maintenance cost. In the process mean shift model, determining the resetting timing due to increasing production costs is the same as the maintenance model. In determining the timing of machine adjustments, there are two differences between the models. First, the process mean shift model excludes failure from the model. This model is limited to the period during the operation of the machine. Second, in the maintenance model, the production cost is set as a general function of the operating time. But in the process mean shift model, the production cost is set as a probability functions associated with the product. In the production system, the maintenance cost of the equipment and the production cost due to the non-confirming items and the quality loss cost are always occurring simultaneously. So it is reasonable that the failure and process mean shift should be dealt with at the same time in determining the maintenance time. This study proposes a model that integrates both of them. In order to reflect the actual production system more accurately, this integrated model includes the items of process variance function and the loss function according to wear level.

• Journal of Integrative Natural Science
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• v.7 no.1
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• pp.67-73
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• 2014

We consider the mean value function for NHPP software reliability model and time series regression model in software failure data. We estimate parameters for the proposed models from two data sets. The values of SSE and MSE is presented from two data sets. We compare the predicted number of faults with the actual two data sets using the mean value function and regression curve.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.401-406
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• 2000

Fault tree analysis (FTA) is a widely used methodology for reliability analysis. The method is useful in that it suggests a very comprehensive way of describing the hierarchical relations of causes of faults and the corresponding results. However it is difficult to get appropriate fault trees for given products or systems without very profound knowledge and experience. This work aims to develop a methodology of fault tree construction using the results of function deployment for machine parts, which provides an objective way of preparing fault trees. The failure modes are defined to each function network generated by the function deployment method and the fault tree with respect to each viewpoint is constructed by arranging the failure modes. The fault tree is finally obtained by synthesizing the fault trees with respect to each viewpoint. The example of fault tree construction is also shown.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.997-1005
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• 2003

In this paper, the problem of determining optimal burn-in time is considered under a general failure model. There are two types of failure in the general failure model. One is Type I failure (minor failure) which can be removed by a minimal repair and the other is Type II failure (catastrophic failure) which can be removed only by a complete repair. In this model, when the unit fails at its age t, Type I failure occurs with probability 1 - p(t) and Type II failure occurs with probability p(t), $0{\leq}p(t)\leq1$. Under the model, the properties of optimal burn-in time maximizing mean time to the catastrophic failure during field operation are obtained. The obtained results are also applied to some illustrative examples.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.12-19
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• 2003

This paper presents the effect of boundary conditions in various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the aid of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.2
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• pp.287-292
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• 2021

In this paper, we propose an efficient CNN application method by analyzing the effect of activation function on the failure diagnosis of the inductive motor stator. Generally, the main purpose of the inductive motor stator failure diagnosis is to prevent the failure by rapidly diagnosing the minute turn short. In the application of activation function, experiments show that the Sigmoid function is 23.23% more useful in accuracy of diagnosis than the ReLu function, although it is shown that ReLu has superiority in overall fixer failure in utilizing the activation function.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.59-62
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• 2001

Reliability engineering is regarded as the major and important roll for all industry. And advanced manufacturing systems with high speed and intelligent have been developing for the betterment of machining ability. In this study, we have systemized evaluation of reliability for machinery system. We proposed the reliability assessment and design review method using analyzing critical units of high speed and intelligent machine system. In addition, we have not only designed and developed test bed system for acquiring reliability data, but also apply QFD technique for satisfying quality function which is provided in design phase. From this study, we will expect to guide and introduce the reliability engineering in developing and processing phase of high quality product.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.2
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• pp.35-44
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• 2003

A system reliability method is proposed to decide reliable serviceability of agricultural irrigation system. Even though reliability method is applied to real engineering situations involving actual life environments and maintaining costs, a number of Issues arise as a modeling and analysis level. This article use concepts that can be described the probability of failure with time variant and series-parallel system reliability analysis model. A proposed method use survivor function that can simulate a time-variant performance function for a lifetime before it is required essential maintenance or replacement to define a target probability of failure in agricultural irrigation canal. In the further study, it is required a relationship between a state of probability of failure and current serviceability to make the optimum repair strategy to maintain appropriate serviceability of an irrigation system.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.861-869
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• 2006

Burn-in is a widely used method to improve the quality of products or systems after they have been produced. In this paper, the problem of determining optimal burn-in time for a system which performs given mission is considered. It is assumed that the given mission time is not a fixed constant but a random variable which follows an exponential distribution. Assuming that the underlying lifetime distribution of a system has an eventually increasing failure rate function, an upper bound for the optimal burn-in time which maximizes the probability of performing given mission is derived. The obtained result is also applied to an illustrative example.

• Clinical and Experimental Pediatrics
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• v.50 no.10
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• pp.948-953
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• 2007

Acute renal failure is the generic term for an abrupt and sustained decrease in renal function resulting in retention of nitrogenous and non nitrogenous waste product. This may results in life threatening consequences including volume overload, hyperkalemia, and metabolic acidosis. Acute renal failure is both common and carries high mortality rate, but as it is often preventable, identification of patients at risk and and appropriate management are crucial. This review summarized the most recent information on definition, epidemiology, clinical causes and management of acute renal failure in pediatric patients.