• 한국신뢰성학회지:신뢰성응용연구
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• 제18권3호
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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.

• 한국신뢰성학회:학술대회논문집
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• 한국신뢰성학회 2011년도 춘계학술발표대회 논문집
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• pp.21-26
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• 2011

Initial reliability prediction done by calculation would be more practical if support by evidence from customer usage profile and field failure data to improve the prediction. Thus, the consistency of the design and the product would be practically validated. In this paper, it will address rationale and method to decide on Acceleration Factor (AF) to be used in Accelerated Life Test (ALT) through usage profile and field failure. The case study of tractor transmission is used to demonstrate the method which data obtained from surveys done on farmers, field visits and field failure data from service center. By considering all the elements, it will determine more relevant AF which indicates the real use conditions of the component.

• 대한산업공학회지
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• 제33권1호
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• pp.52-60
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• 2007

Estimating parameters of the lifetime distribution is investigated when field failure data are not completelyreported. To take into account the reality and the accuracy of the estimates in such a case, the failure reportingprobability is incorporated in estimating parameters, Firstly, method of maximum likelihood estimate (MLE) isused to estimate parameters of the lifetime distribution when failure reporting probability is known, Secondly,Expectation and Maximization (EM) algorithm is used to estimate the failure reporting probability and parame-ters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both cases,procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simula-tion results show that MLE obtained by the proposed method is more accurate than the conventional MLE.

• 대한안전경영과학회지
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• 제3권4호
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• pp.65-76
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• 2001

Field data have been recorded as the time to failure or the number of failure of systems. We consider the time to failure and covariate variables in some pre-specified follow-up or warranty period. This paper aims to investigate study on the reliability estimation when some additional field data can be collected within-warranty period or after-warranty period. A various likelihood-based methods are outlined and examined for exponential or Weibull distribution.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2002년도 가을 학술발표회 논문집
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• pp.513-520
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• 2002

The stability analysis of rock slope can be predicted using a suitable field data but it cannot be predicted unless suitable field data was taken. In this study, artificial neural networks theory is applied to predict plane failure that has a few data. It is well known that human brain has the advantage of handling disperse and parallel distributed data efficiently. On the basis of this fact, artificial neural networks theory was developed and has been applied to various fields of science successfully In this study, error back-propagation algorithm that is one of the teaching techniques of artificial neural networks is applied to predict plane failure. In order to verify the applicability of this model, a total of 30 field data results are used. These data are used for training the artificial neural network model and compared between the predicted and the measured. The simulation results show the potentiality of utilizing the neural networks for effective safety factor prediction of plane failure. In conclusion, the well-trained artificial neural network model could be applied to predict the plane failure stability of rock slope.

• Journal of the Korean Data and Information Science Society
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• 제22권4호
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• pp.755-764
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• 2011

기업은 종종 과거의 필드 고장 데이터를 이용하여 미래에 필드에서 고장이 얼마나 일어날 것인지 예측한다. 특히 이런 예측은 필드에서 예기치 않던 고장모드 (failure mode)가 발견될 때 더욱 하고 싶어진다. 왜냐하면 기업은 이런 예측을 통해 미래에 품질보증 비용이 얼마나 될 것인지 파악하고, 고장 난 부품을 재빨리 수리하는데 필요한 여유 부품의 수를 파악하고 싶기 때문이다. 본 연구에서는 기업에서 생길 수 있는 요약 데이터를 사용하여 미래 필드에서 고장이 얼마나 발생할 것인지 예측하고, 이런 요약 데이터이외에 또 어떤 데이터가 생길 수 있으며 이때 분석결과가 어떻게 나올 수 있는지 알아본다.

• 대한산업공학회지
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• 제42권5호
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• pp.327-336
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• 2016

Prediction of customer failure rates plays an important role for establishing appropriate management policies and improving the profitability for industries. For these reasons, many LCD (Liquid crystal display) manufacturing industries have attempted to construct prediction models for customer failure rates. However, most traditional models are based on the parametric approaches requiring the assumption that the data follow a certain probability distribution. To address the limitation posed by the distributional assumption underpinning traditional models, we propose using parameter-free data mining models for predicting customer failure rates. In addition, we use various information associated with product attributes and field return for more comprehensive analysis. The effectiveness and applicability of the proposed method were demonstrated with a real dataset from one of the leading LCD companies in South Korea.

• 산업경영시스템학회지
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• 제32권3호
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• pp.127-134
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• 2009

RAM(Reliability, Availability, Maintainability) is important performance factor to keep combat readiness and optimize operational and maintenance cost of weapon systems. This paper discusses the method to establish RAM for combat readiness by using field failure data from similarity equipments. Operational availability is estimated from a binomial distribution function of user's operational conditions such as combat readiness preservation probability, operational rate, operational availability and total number of equipment. Reliability and maintainability is estimated from field failure data from similarity equipment to accomplish operational availability. The effectiveness of established RAM is verified through analysis of combat readiness preservation probability and mission reliability. A case study of weapon system illustrates the process of the proposed method.

• 한국군사과학기술학회지
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• 제21권5호
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• pp.599-606
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• 2018

Failure data of systems in many field can be erroneous, which influences the reliability analysis of the systems. The general form of failure data is right censored data with accurate time information. But due to its nature of data collection in the military field, failure time of one-shot weapon systems can have errors which are related to the maintenance period. So this paper suggests a model that can reduce the error by utilizing interval censored data as an alternative to right censored data in weibull distribution.

• Nuclear Engineering and Technology
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• 제55권10호
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• pp.3677-3691
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• 2023

Since containment building is the major shielding structure to ensure safety of nuclear power plant, the structural behavior and ultimate pressure capacity of containments must be studied in depth. This paper addresses ambiguous issue of determining free-field position for liner failure by suggesting an expanded free-field region and comparing internal pressure capacities obtained by test data, conservative assumption and suggested free-field region. For this purpose, a practical approach to determine the free-field position for the evaluation of liner tearing is carried out. The maximum principal strain histories versus internal pressure capacities among different free-field positions at various azimuths and elevations are compared with those at the equipment hatch as a conservative assumption. The comparison shows that there are considerable differences in the internal pressure capacity at liner failure within the expanded free-field region compared to the vicinity of the equipment hatch. Additionally, this study proposes an approximate correlation with conservative factors by considering the expanded free-field ranges and material characteristics to determine realistic failure criteria for liner. The applicability of the proposed correlation is demonstrated by comparing the internal pressure capacities of full-scale containment buildings following liner failure criteria according to RG 1.216 and an approximate correlation.