• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.223-230
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• 2018

In the case of a one-shot logistic equipment system that has been stored for a long time, reliability changes with the passage of time. Therefore, when the time comes to use, the storage reliability of the product is an important quality characteristic, and the existing studies have focused on the research for calculating the optimal period inspection cycle to improve the storage reliability. In this study, we analyzed the influence of the two factors on the storage reliability at the convergence point by analyzing the design reliability as well as the periodic inspection cycle. To do this, we applied the existing Martinez storage reliability model to the missile, a representative product of a one-shot system, and analyzed the quantitative effects of the design reliability and the periodic inspection cycle. From the results of the analysis, it was confirmed that the maintenance of the periodic inspection cycle is more important for the improvement of the storage reliability than the design reliability in the design reliability category of the current product.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.96-104
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• 2017

A one-shot system (device) refers to a system that is stored for a long period of time and is then disposed of after a single mission because it is accompanied by a chemical reaction or physical destruction when it operates, such as shells, munitions in a defense weapon system and automobile airbags. Because these systems are primarily related with safety and life, it is required to maintain a high level of storage reliability. Storage reliability is the probability that the system will operate at a particular point in time after storage. Since the stored one-shot system can be confirmed only through inspection, periodic inspection and maintenance should be performed to maintain a high level of storage reliability. Since the one-shot system is characterized by a large loss in the event of a failure, it is necessary to determine an appropriate inspection period to maintain the storage reliability above the reliability goal. In this study, we propose an optimal inspection policy that minimizes the total cost while exceeding the reliability goal that the storage reliability is set in advance for the one-shot system in which periodic inspections are performed. We assume that the failure time is the Weibull distribution. And the cost model is presented considering the existing storage reliability model by Martinez and Kim et al. The cost components to be included in the cost model are the cost of inspection $c_1$, the cost of loss per unit time between failure and detection $c_2$, the cost of minimum repair of the detected breakdown of units $c_3$, and the overhaul cost $c_4$ of $R_s{\leq}R_g$. And in this paper, we will determine the optimal inspection policy to find the inspection period and number of tests that minimize the expected cost per unit time from the finite lifetime to the overhaul. Compare them through numerical examples.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.1
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• pp.1-13
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• 2013

Some systems such as missiles and ammunitions are used only one time in combat or emergency situation. Predicting correct storage reliability is very important for those systems which are inspected periodically. Many researches have been done for predicting the storage reliability using generally exponential or Weibull failure distribution. However, recent studies show the hazard functions follow various types of failure distributions. So in this paper, we proposed a generalized model that measures the storage reliability regardless of type of failure distributions. And this model reflects inspection error and failures that might be occurred during periodical check and within storage term as well.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.6
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• pp.248-262
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• 2008

As the number of large size multimedia files increases and the importance of individual's digital data grows, storage devices have been advanced to store more data into smaller spaces. In such circumstances, a physical damage in a storage device can destroy large amount of important data. Therefore, it is needed to verify the robustness of various physical faults in storage device before certain systems are used. We developed SOAR(Storage Reliability Analyzer), Storage Reliability Analyzer, to detect physical faults in diverse kinds of HDD hardware components and to recover the systems from those faults. This is a useful tool to verify robustness and reliability of a disk. SOAR uses three unique methods of creating physical damages on a disk and two unique techniques to apply the same feature on file systems. In this paper, we have performed comprehensive tests to verify the robustness and reliability of storage device with SOAR, and from the verification result we could confirm SOAR is a very efficient tool.

• Journal of Applied Reliability
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• v.16 no.1
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• pp.32-40
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• 2016

Purpose: The purpose of this study is to analyze the effect of sampling points on accuracy of storage reliability estimation for one-shot systems by assuming a weibull distribution as a storage reliability distribution. Also propose method for determining of sampling points for increase the accuracy of reliability estimation. Methods: Weibull distribution was divided into three sections for confirming the possible to estimate the parameters of the weibull distribution only some section's sample. Generate quantal response data for failure data. And performed parameter estimation with quantal response data. Results: If reduce sample point interval of 1 section, increase the accuracy of reliability estimation although sampling only section 1. Even reduce total number of sampling point, reducing sampling time interval of the 1 zone improve the accuracy of reliability estimation. Conclusion: Method to increase the accuracy of reliability estimation is increasing number of sampling and the sampling points. But apply this method to One-shot system is difficult because test cost of one-shot system is expensive. So propose method of accuracy of storage reliability estimation of one-shot system by adjustment of the sampling point. And by dividing the section it could reduce the total sampling point.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.28-35
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• 2019

Since guided missiles with the characteristics of the one-shot system remain stored throughout their entire life cycle, it is important to maintain their storage reliability until the launch. As part of maintaining storage reliability, period of preventive test is set up to perform preventive periodic test, in this case failure detection rate has a great effect on setting up period of preventive test to maintain storage reliability. The proposed method utilizes failure rate predicted by the software on the basis of MIL-HDBK-217F and failure mode analyzed through FMEA (Failure Mode and Effect Analysis) using data generated from the actual field. The failure detection rate of using the proposed method is applied to set periodic test of the actual guided missile. The proposed method in this paper has advantages in accuracy and objectivity because it utilizes a large amount of data generated in the actual field.

• Structural Engineering and Mechanics
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• v.70 no.5
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• pp.563-570
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• 2019

To analyze the seismic reliability of concrete rectangular liquid storage structures (CRLSSs), assuming that the wall thickness and internal liquid depth of CRLSSs are random variables, calculation models of CRLSSs are established by using the Monte Carlo finite element method (FEM). The principal stresses of the over-ground and buried CRLSSs are calculated under three rare fortification intensities, and the failure probabilities of CRLSSs are obtained. The results show that the seismic reliability increases with the increase of wall thickness, whereas it decreases with the increase of liquid depth. Between the two random factors, the seismic reliability of CRLSSs is more sensitive to the change in wall thickness. Compared with the over-ground CRLSS, the buried CRLSS has better reliability.

• Journal of the Korean Society of Safety
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• v.29 no.4
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• pp.116-122
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• 2014

This study proposes a system reliability analysis of rack storage facilities subjected to forklift colliding events. The proposed system reliability analysis consists of two steps: the first step is to identify dominant failure modes that most contribute to the failure of the whole rack facilities, and the second step is to evaluate the system failure probability. In the first step, dominant failure modes are identified by using a simulation-based selective searching technique where the contribution of a failure mode to the system failure is roughly estimated based on the distance from the origin in the space of the random variables. In the second step, the multi-scale system reliability method is used to compute the system reliability where the first-order reliability method (FORM) is initially used to evaluate the component failure probability (failure probability of one member), and then the probabilities of the identified failure modes and their statistical dependence are evaluated, which is called as the lower-scale reliability analysis. Since the system failure probability is comprised of the probabilities of the failure modes, a higher-scale reliability analysis is performed again based on the results of the lower-scale analyses, and the system failure probability is finally evaluated. The illustrative example demonstrates the results of the system reliability analysis of the rack storage facilities subjected to forklift impact loadings. The numerical efficiency and accuracy of the approach are compared with the Monte Carlo simulations. The results show that the proposed two-step approach is able to provide accurate reliability assessment as well as significant saving of computational time. The results of the identified failure modes additionally let us know the most-critical members and their failure sequence under the complicated configuration of the member connections.

• Journal of Korean Society for Quality Management
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• v.41 no.1
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• pp.135-148
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• 2013

Purpose: This paper presents a method to evaluate the stockpile reliability of propelling charge for performance and storage safety with storage time. Methods: We consider a performance failure level is the amount of muzzle velocity drop which is the maximum allowed standard deviation multiplied by 6. The lifetime for performance is estimated by non-linear regression analysis. The state failure level is assumed that the content of stabilizer is below 0.2%. Because the degradation of stabilizer with storage time has both distribution of state and distribution of lifetime, it must be evaluated by stochastic process method such as gamma process. Results: It is estimated that the lifetime for performance is 59 years. The state distribution at each storage time can be shown from probability density function of degradation. It is estimated that the average lifetime as $B_{50}$ life is 33 years from cumulative failure distribution function curve. Conclusion: The lifetime for storage safety is shorter than for performance and we must consider both the lifetime for storage safety and the lifetime performance because of variation of degradation rate.

• Journal of the Korean Society of Propulsion Engineers
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• v.23 no.4
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• pp.42-49
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• 2019

This paper presents a method to predict the storage reliability of springs for turbo engine components based on an accelerated degradation test. The reliability assessment procedure for springs is established to proceed with the accelerated degradation test. The spring constant is selected as the performance degradation characteristic, the temperature is determined to be the stress factor that deteriorates the spring constant. The storage tests are performed at three temperature test conditions. The spring constant is measured periodically to check the degradation status of the springs. Failure times of the springs are predicted by using the degradation model. Finally, the storage lifetime of the springs at normal use conditions is predicted using an accelerated model and failure times of all test conditions.