• Journal of the Korea Society for Simulation
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• v.25 no.4
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• pp.77-84
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• 2016

This paper proposes a methodology for creating a function based reliability prediction model. Although, there are various works for reliability prediction, one of the features of their research is that the research is based on hardware-centered reliability prediction. Reliability is often defined as the probability that a device will perform its intended function, under operating condition, for a specified period of time, there is a profound irony about reliability prediction problem. In this paper, we proposed four-phase modeling procedure for function-centered reliability prediction. The proposed modeling procedure consists of four models; 1) structure block model, 2) function block model, 3) device model, and 4) reliability prediction model. We performed function-centered reliability prediction for electronic ballast using the proposed modeling procedure and MIL-HDBK-217F which is the military handbook for reliability prediction of electronic equipment.

• Journal of Applied Reliability
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• v.18 no.3
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• pp.250-259
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• 2018

Purpose: Previously, missile reliability prediction is based on theoretical failure prediction model. It has shown that the predicted reliability is inadequate to real field data. Although an MTTF based reliability prediction method using real field data has recently been studied to overcome this issue. In this paper, we present a more realistic method, considering MTBF concept, to predict missile reliability. Methods: In this paper we proposed a modified survival model. This model is considering MTBF as its core concept, and failed missiles in the model are to be repaired and redeployed. We compared the modified model (MTBF) and the previous model (MTTF) in terms of fitness against the real failure data. Results: The reliability prediction result of MTBF based model is closer to fields failure data set than that of MTTF based model. Conclusion: The proposed MTBF concept is more fitted to real failure data of missile than MTTF concept. The methodology of this study can be applied to analyze field failure data of other similar missiles.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.115-123
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• 2021

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.1
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• pp.9-17
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• 2020

Currently, Storage Reliability is analyzed when predicting the reliability of guided missile. However, Mission Reliability and Logistics Reliability should be analyzed according to the definition of reliability in MIL-STD-785B. Therefore, it is necessary to accurately predict the reliability of guided missile based on the definition of reliability. In this paper, we proposed improved the reliability procedure and model for guided missile based on which the definition of reliability considering the mission profile. The proposed model can calculate the final failure rate by applying the ratio of the dormant and storage according to the mission profile. The proposed model has been confirmed to be more accurate than the existing model compared to the actual failure rate value. The results of this study can be useful for applying the reliability prediction to any guided missile.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.475-481
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• 1993

The objective of this study is to develope the reliability prediction model for Float Rated Integrating Gyroscope( :FRIG) at maximum loading. The equation of motion for FRIG is firstly derived to set up the reliability prediction model. To analysis reliability or all parts of the gyro is not easy due to their complicated structure. Therefore the failure parts are chosen by Failure Mode Effective Analysis (:FMEA). F.E.M is utilized to calculate loads for the selseced rotating assembly and pivot / jewel. The technical reliability is calculated by applying reliability design theory with these results and the performance reliability is sought through distribution estimation with error test data. The bulk reliability of gyroscope is sought by applying the two results. The present prediction results are compared with the accumulation time in good agreement.

• Journal of the Korea Safety Management & Science
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• v.10 no.3
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• pp.81-87
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• 2008

The reliability prediction and evaluation for general electronic components are required to guarantee in quality and in efficiency. Although many methodologies for predicting the reliability of electronic components have been developed, their reliability might be subjective according to a particular set of circumstances, and therefore it is not easy to quantify their reliability. In this study reliability prediction of electronic components, that is the interface card, which is used in the CNC(Computerized Numerical Controller) of machine tools, was carried out using PRISM reliability prediction specification. Reliability performances such as MTBF(Mean Time Between Failure), failure rate and reliability were obtained, and the variation of failure rate for electronic components according to temperature change was predicted. The results obtained from this study are useful information to consider a counter plan for weak components before they are used.

• Journal of Applied Reliability
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• v.17 no.4
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• pp.296-304
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• 2017

Purpose: Recent weapon systems in defense have increased the complexity and importance of software when developing multifunctional equipment. In this study, we analyze the accuracy of the proposed software reliability model when applied to weapon systems. Methods: Determine the similarity between software reliability analysis results (prediction/estimation) utilizing data from developing weapon systems and system failures data during operation of weapon systems. Results: In case of a software reliability prediction model, the predicted failure rate was higher than the actual failure rate, and the estimation model was consistent with actual failure history data. Conclusion: The software prediction model needs to adjust the variables that are appropriate for the domestic weapon system environment. As the reliability of software is increasingly important in the defense industry, continuous efforts are needed to ensure accurate reliability analysis in the development of weapon systems.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2076-2085
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• 2000

Almost all existing software reliability models are based on the assumptions of he software usage and software failure process. There, therefore, is no universally applicable software reliability model. To develop a universal software reliability model this paper suggests the predictive filter as a general software reliability prediction model for time domain failure data. Its usefulness is empirically verified by analyzing the failure datasets obtained from 14 different software projects. Based on the average relative prediction error, the suggested predictive filter is compared with other well-known neural network models and statistical software reliability growth models. Experimental results show that the predictive filter generally results in a simple model and adapts well across different software projects.

• Proceedings of the Korean Reliability Society Conference
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• 2000.04a
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• pp.213-222
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• 2000

In present study, a stochastic model is developed for the low cycle fatigue life prediction and reliability assessment of 316L stainless steel under variable multiaxial loading. In the proposed model, fatigue phenomenon is considered as a Markov process, and damage vector and reliability are defined on every plane. Any low cycle fatigue damage evaluating method can be included in the proposed model. The model enables calculation of statistical reliability and crack initiation direction under variable multiaxial loading, which are generally not available. In present study, a critical plane method proposed by Kandil et al., maximum tensile strain range, and von Mises equivalent strain range are used to calculate fatigue damage. When the critical plane method is chosen, the effect of multiple critical planes is also included in the proposed model. Maximum tensile strain and von Mises strain methods are used for the demonstration of the generality of the proposed model. The material properties and the stochastic model parameters are obtained from uniaxial tests only. The stochastic model made of the parameters obtained from the uniaxial tests is applied to the life prediction and reliability assessment of 316L stainless steel under variable multiaxial loading. The predicted results show good accordance with experimental results.

• Computers and Concrete
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• v.12 no.6
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• pp.775-783
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• 2013

A novel reliability-based work model of k/n (G) system has been developed. Unit failure probability is given based on the load and strength distributions and according to the stress-strength interference theory. Then a dynamic reliability prediction model of repairable k/n (G) system is established using probabilistic differential equations. The resulting differential equations are solved and the value of k can be determined precisely. The number of work unit k in repairable k/n (G) system is obtained precisely. The reliability of whole life cycle of repairable k/n (G) system can be predicted and guaranteed in the design period. Finally, it is illustrated that the proposed model is feasible and gives reasonable prediction.