• 품질경영학회지
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• 제22권2호
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• pp.33-40
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• 1994

Most software reliability models and other methods attempt to estimate some measures based on its fault history. There are several phases of the software life cycle including testing phase. We can propose it's stopping rule to decide when to stop the testing and pass it on to the next phase by considering the detailed structure of software and calculating the failure rate when each fault was detected. Downs (1985) proposed a method which was developed for estimating the failure rate applicable only to two-level profiles. In this paper, I extended to profiles involving more levels.

• International Journal of Reliability and Applications
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• 제3권1호
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• pp.51-60
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• 2002

This paper presents the methodology for obtaining point and interval estimating of the parameters of a new two-parameter distribution with multiple-censored and singly censored data (Type-I censoring or Type-II censoring) as well as complete data, using the maximum likelihood method. The basis is the likelihood expression for multiple-censored data. Furthermore, this model can be extended to a three-parameter distribution that is added a scale parameter. Then, the parameter estimation can be obtained by the graphical estimation on probability plot.

• 한국안전학회지
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• 제8권4호
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• pp.91-94
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• 1993

The main purpose of this study was to develop fuzzy models in order to decide system failure rate in industrial accident prevention. The purposed linguistic approach uses the Zadeh's concept of a linguistic variable with value which are not number. The problem of measurement Is the assignment of numbers to reprresnt properties of the involved events, object, or situation. Thus, in this study, part standard compatibility function was used.

• 한국국방경영분석학회지
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• 제25권2호
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• pp.144-157
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• 1999

In this paper, we consider a new preventive replacement policy for the system which deteriorates while it is in operation with an increasing failure rate. The system is subject to two types of failure. A type 1 failure is repairable while a type 2 failure is not repairable. In the new policy, a system is replaced at the age of $t_p$ or at the instant the$\textsc{k}^{th}$ type 1 failure occurs, whichever comes first. However, if a type 2 failure occurs before a preventive replacement is performed, a failure replacement should be made. We assume that a type 1 failure can be rectified with a minimal repair. We also assume that a replacement takes a non-negligible amount of time while a minimal repair takes a negligible amount of time. Under a cost structure which includes a preventive replacement cost, a failure replacement cost and a minimal repair cost, we develop a model to find the optimal ($\textsc{k},t_p$) policy which minimizes the expected cost per unit time in the long run while satisfying a system availability constraint.

• Geomechanics and Engineering
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• 제23권1호
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• pp.51-59
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• 2020

In this paper, the WEKA platform was used to mine and analyze measured data of floor failure depth and a prediction system of floor failure depth was developed with Java. Based on the standardization and discretization of 35-set measured data of floor failure depth in China, the grey correlation degree analysis on five factors affecting the floor failure depth was carried out. The correlation order from big to small is: mining depth, working face length, floor failure resistance, mining thickness, dip angle of coal seams. Naive Bayes model, neural network model and decision tree model were used for learning and training, and the accuracy of the confusion matrix, detailed accuracy and node error rate were analyzed. Finally, artificial neural network was concluded to be the optimal model. Based on Java language, a prediction system of floor failure depth was developed. With the easy operation in the system, the prediction from measured data and error analyses were performed for nine sets of data. The results show that the WEKA prediction formula has the smallest relative error and the best prediction effect. Besides, the applicability of WEKA prediction formula was analyzed. The results show that WEKA prediction has a better applicability under the coal seam mining depth of 110 m~550 m, dip angle of coal seams of 0°~15° and working face length of 30 m~135 m.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4287-4306
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• 2016

Network resilience provides an effective way to overcome the problem of network failure and is crucial to Internet protocol (IP) network management. As one of the main challenges in network resilience, recovering from link failure is important to maintain the constancy of packets being transmitted. However, existing failure recovery approaches do not handle the traffic engineering problem (e.g., tuning the routing-protocol parameters to optimize the rerouting traffic flow), which may cause serious congestions. Moreover, as the lack of QoS (quality of service) restrictions may lead to invalid rerouting traffic, the QoS requirements (e.g., bandwidth and delay) should also be taken into account when recovering the failed links. In this paper, we first develop a probabilistically correlated failure model that can accurately reflect the correlation between link failures, with which we can choose reliable backup paths (BPs). Then we construct a mathematical model for the failure recovery problem, which takes maximum rerouting traffic as the optimizing objective and the QoS requirements as the constraints. Moreover, we propose a heuristic algorithm for link failure recovery, which adopts the improved k shortest path algorithm to splice the single BP and supplies more protection resources for the links with higher priority. We also prove the correctness of the proposed algorithm. Moreover, the time and space complexity are also analyzed. Simulation results under NS2 show that the proposed algorithm improves the link failure recovery rate and increases the QoS satisfaction rate significantly.

• Korean Chemical Engineering Research
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• 제56권1호
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• pp.133-138
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• 2018

2000년대 이후 대두된 안전, 환경 이슈들로 인해 안전 관리는 더욱 더 중요해졌다. 하지만 안전 관리는 많은 경험적 데이터들을 요구하므로 한계점들이 많다. 안전 분야 중 하나인 배관 안전의 경우 현재 배관을 관리하는 시뮬레이션 프로그램들이 존재하지만, 배관 내부 침식에 대해서는 데이터를 얻기 힘들어 시뮬레이션에 반영이 잘 되어있지 않은 상태이다. 이러한 문제점에서 착안해 본 연구에서는 전산유체역학(CFD)을 이용하여 배관 내부의 곡면에 일어나는 침식을 모사하였고, 계산한 침식 속도를 바탕으로 한계상태함수를 이용하여 배관의 실패 주기를 분석하였다. CFD 대상 배관의 경우 여수 산업 단지에 실제로 운영되고 있는 표본을 사용하였다. DPM (Discrete Phase Model)과 부식 모델을 이용하여 CFD 결과로 $3.093mm{\cdot}yr^{-1}$ 수치의 침식 속도를 얻을 수 있었고, 이 결과를 한계상태함수에 적용한 결과 배관에 누출(leak)을 유발하는데 14.2년, 파열(burst)를 유발하는데 28.2년이라는 실패 주기를 얻어낼 수 있었다. 이러한 과정들을 통해 배관 곡면 침식이 배관 안전 진단에 유효한 실패 모드임을 도출할 수 있었다. 본 연구는 실패 연도를 구할 수 있는 방법론들을 제시하여 데이터의 한계점을 극복하고, 배관 안전 진단에 좀 더 정밀하고 발전된 방법을 제시한 것에 대해 의의를 가진다.

• International Journal of Reliability and Applications
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• 제18권1호
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• pp.1-8
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• 2017

In this paper, we study an extended warranty model under minimal repair-replacement warranty (MRRW) which is suggested by Park, Jung and Park (2013). Under MRRW policy, the manufacturer is responsible for providing the minimal repair-replacement services upon the system failures during the warranty period. And if the failure occurs during the extended warranty period, only the minimal repair is conducted. Following the expiration of extended warranty, the user is solely responsible for maintaining the system for a fixed length of time period and replaces the system at the end of such a maintenance period. During the maintenance period, only the minimally repair is given for each system failure. The main purpose of this article is to suggest the extended warranty and replacement model with MRRW. Given the cost structures incurred during the life cycle of the system, we formulate the expected cost and the expected length of life cycle to obtain the expected cost rate.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권2호
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• pp.103-111
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• 2017

Purpose: Accelerated degradation tests can speed time to market and reduce the test time and costs associated with long term reliability tests to verify the required service life of a product or material. This paper proposes a service life prediction method for components or materials using an accelerated degradation tests based on the relationships between temperature and the rate of failure-causing chemical reaction. Methods: The relationship between performance degradation and the rate of a failure-causing chemical reaction is assumed and least square estimation is used to estimate model parameters from the degradation model. Results: Methods of obtaining acceleration factors and predicting service life using the degradation model are presented and a numerical example is provided. Conclusion: Service life prediction of a component or material is possible at an early stage of the degradation test by using the proposed method.

• 품질경영학회지
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• 제51권4호
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• pp.551-571
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• 2023

Purpose: The purpose of this study is to propose useful suggestions by analyzing the causal effect relationship between the failure rate of quality and the process variables in the C5ISR domain of the defense industry. Methods: The collected data through the in house Systems were analyzed using Big data analysis. Data analysis between quality data and A/S history data was conducted using the CRISP-DM(Cross-Industry Standard Process for Data Mining) analysis process. Results: The results of this study are as follows: After evaluating the performance of candidate models for the influence of inspection data and A/S history data, logistic regression was selected as the final model because it performed relatively well compared to the decision tree with an accuracy of 82%/67% and an AUC of 0.66/0.57. Based on this model, we estimated the coefficients using 'R', a data analysis tool, and found that a specific variable(continuous maximum discharge current time) had a statistically significant effect on the A/S quality failure rate and it was analysed that 82% of the failure rate could be predicted. Conclusion: As the first case of applying big data analysis to quality issues in the defense industry, this study confirms that it is possible to improve the market failure rates of defense products by focusing on the measured values of the main causes of failures derived through the big data analysis process, and identifies improvements, such as the number of data samples and data collection limitations, to be addressed in subsequent studies for a more reliable analysis model.