• Journal of Korean Society of Industrial and Systems Engineering
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• 제42권4호
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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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• 제9권3호
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• pp.306-311
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• 2016

Software reliability in the software development process is an important issue. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, reliability software cost model considering logarithmic and exponential fault detection rate based on observations from the process of software product testing was studied. Adding new fault probability using the Goel-Okumoto model that is widely used in the field of reliability problems presented. When correcting or modifying the software, finite failure non-homogeneous Poisson process model. For analysis of software reliability model considering the time-dependent fault detection rate, the parameters estimation using maximum likelihood estimation of inter-failure time data was made. The logarithmic and exponential fault detection model is also efficient in terms of reliability because it (the coefficient of determination is 80% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, the software developers have to consider life distribution by prior knowledge of the software to identify failure modes which can be able to help.

• Journal of the Korea Society of Computer and Information
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• 제10권6호
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• pp.27-36
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• 2005

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates Per fault. This Paper Proposes reliability model using the generalized gamma distribution, which can capture the monotonic increasing(or monotonic decreasing) nature of the failure occurrence rate per fault. Equations to estimate the parameters of the generalized gamma finite failure NHPP model based on failure data collected in the form of interfailure times are developed. For the sake of proposing shape parameter of the generalized gamma distribution, used to the special pattern. Data set, where the underlying failure process could not be adequately described by the knowing models, which motivated the development of the gamma or Weibull model. Analysis of failure data set for the generalized gamma modell, using arithmetic and Laplace trend tests . goodness-of-fit test, bias tests is presented.

• Journal of the Computational Structural Engineering Institute of Korea
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• 제34권6호
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• pp.393-401
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• 2021

In this paper, we proposed a numerical model based on moment-curvature, to evaluate the resistance of reinforced concrete (RC) members subjected to blast loading. To consider the direct shear failure mode, we introduced a dimensionless spring element based on the empirical direct shear stress-slip relation. Based on the dynamic increase factor equations for materials, new dynamic increase factor equations were constructed in terms of the curvature rate for the section which could be directly applied to the moment-curvature relation. Additionally, equivalent bending stiffness was introduced in the plastic hinge region to consider the effect of bond-slip. To verify the validity of the proposed model, a comparative study was conducted against the experimental results, and the superiority of this numerical model was confirmed through comparison with the analytical results of the single-degree of freedom model. Pressure-impulse (P-I) diagrams were produced to evaluate the resistance of members against bending failure and direct shear failure, and additional parametric studies were conducted.

• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.801-812
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• 1999

Change-point hazard rate models arise for example in applying "burn-in" techniques to screen defective items and in studing times until undesirable side effects occur in clinical trials. Sometimes in screening defectives it might be sensible to model two stages of burn-in. In a clinical trial there might be an initial hazard rate for a side effect which after a period of time changes to an intermediate hazard rate before settling into a long term hazard rate. In this paper we consider the multiple change points hazard rate model. The classical approach's asymptotics can be poor for the small to all moderate sample sizes often encountered in practice. We propose a Bayesian approach avoiding asymptotics to provide more reliable inference conditional only upon the data actually observed. The Bayesian models can be fitted using simulation methods. Model comparison is made using recently developed Bayesian model selection criteria. The above methodology is applied to a generated data and to a generated data and the Lawless(1982) failure times of electrical insulation.

• Journal of the Korean Operations Research and Management Science Society
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• 제22권4호
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• pp.151-165
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• 1997

We propose a method for estimating the probability of perfect PM from successive failure times of a repairable system. The system under study is maintained preventively at periodic times, and it undergoes minimal repair at failure. We consider Brown-Proschan imperfect PM model in which the system is restored to a condition as good as new with probability P and is otherwise restored to its condition just prior to failure. We discuss the identifiability problem when the PM modes are not recorded. The expectation-maximization principle is employed to handle the incomplete data problem. We assume that the lifetime distribution belongs to a parametric family with increasing failure rate. For the two parameter Weibull lifetime distribution, we propose a specific algorithm for finding the maximum lifelihood estimates of the reliability parameters : the probability of perfect PM (P), as well as the distribution parameters. The estimation method will provide useful results for maintaining real systems.

• Proceedings of the Safety Management and Science Conference
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• 대한안전경영과학회 2004년도 추계학술대회
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• pp.115-123
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• 2004

Replacement problems can be classed as either deterministic of stochastic. Deterministic problems are those in which the timing and the outcome of the replacement action are assumed to be known with certainty. Before proceeding with development of replacement models it is important to note that preventive replacement actions, that is, ones taken before equipment reaches a failed state, require two necessary conditions: (1) The total cost of the replacement must be greater after failure than before. (2) The failure rate of the equipment must be increasing. Equipment is subject to failure. On failure, one of two possible actions can be taken : repair or complete replacement of the failed equipment. In this paper, we proposed optimal overhaul, repair, replacement maintenance model with two-state.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제17권32호
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• pp.221-226
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• 1994

Almost preventive maintenance policies assumed that the system after pm has failure rate as before pm with probability p and as good as new with probability 1-p. This paper considers the s-expected cost of the model with imperfect periodic preventive maintenance that increasing minimal repair costs at failure and obtains the optimum periodic preventive maintenance time. Numerical example are shown in which the failure time of the system has gamma distribution.

• The Transactions of The Korean Institute of Electrical Engineers
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• 제56권9호
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• pp.1589-1595
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• 2007

This paper suggests the advanced reliability assessment tool for railway signaling Hot-Standby sparing system. Existing reliability assessment for Hot-Standby sparing system controller is done by using single module mean failure rate based on approximated Hot standby sparing system function. Although approximated Hot standby sparing system function can be applied to various Hot standby sparing system, however, it is not able to reflect the exact system structure. In this paper, we suggest the advanced reliability function by identifying changeover-related failure factors and common failure mode which is not considered in existing approximated Hot standby sparing system reliability function via developing Hot standby sparing system model for railway signaling and applying FMECA to this model. Also. we compare reliability assessment results for model system to reliability assessment for existing system.

• Journal of Korean Institute of Industrial Engineers
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• 제33권2호
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• pp.273-281
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• 2007

The decision of how long performing system burn-in must be answered with a probabilistic model of a system lifetime at which infant mortality failures created during assembly processes are quantified. In this paper, we propose such a model which is modified from previous results. Using the system model, we derived system reliability in terms of component and system burn-in times for the two cases of minimal repair at system failure and of component replacement and connection repair at their failure times. The procedure is illustrated with a bridge system and the optimal system burn-in times are obtained for maximizing system reliability. The result suggests that an assumption of minimal repair at system failure may underestimate the optimal burn-in time in practice.