• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.678-685
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• 2005

Estimating parameters of the lifetime distribution is investigated when field failure data are not completely reported. To take into account the reality and the accuracy of the estimates in such a case, the failure reporting probability is incorporated in estimating parameters. Firstly, method of maximum likelihood estimate(MLE) is used 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 parameters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both case, procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simulation results show that MLE obtained by the proposed method is more accurate than the conventional MLE.

• 산업경영시스템학회지
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• 제42권2호
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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.

• 품질경영학회지
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• 제40권3호
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• pp.278-285
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• 2012

Purpose: Weapon systems have the long life cycle unlike the consumer product. Thus, the reliability of weapon system is improved during the life cycle through the steady technical change. In this paper, we deal with the method of evaluating the reliability of weapon system with the field failure data. Methods: Especially, we present how to gather the field failure data and evaluate the reliability through the case of K-series weapon system. To evaluate reliability, the reliability growth model is used and the result is discussed. Results: It is steadily improved the reliability of K-series weapon system deployed from 2000 to 2004. The frequency of the failures that affect the mission is largely reduced and MTBMF(mean time between mission failure) is also improved. Conclusion: We can guess the trend of the reliability of weapon system with the field data through this study. Furthermore, it can be used to improve the reliability and make maintenance policy.

• 시스템엔지니어링학술지
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• 제10권1호
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• pp.43-48
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• 2014

The door system for railway vehicles is the critical device directly influences on safety and satisfaction of passengers, Recently, electrical type of passenger door system is widely used for EMU type train instead of pneumatic type of passenger door system. The estimation of MTBF and failure rates for electrical type door system is essential. The manufacturor simply provides intrinsic reliability data for the railway operator. But actual reliability data based on operation and maintenance data is not complying with intrinsic reliability. In this study, operation and failure data associated with electrical door system were analyzed in order to determine actual MTBF and failure data. Intrinsic reliability data and service reliability data were studied to finallize much more practical and reliable actual reliability. Relax 2011 was used to predict intrinsic reliability and 217Plus model was also used to estimate of actual reliability data based on field data. Furthermore, it is necessary to keep studying on reliability prediction methodology and applying it in the field and doing research on improvement of reliability through feedback as well.

• 한국산업정보학회논문지
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• 제16권5호
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• pp.107-114
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• 2011

신제품 개발 또는 개선 과정에 있어서 내구 수명의 평가는 장기간이 소요되는 작업으로서, 제품의 개발 또는 개선 기간에 큰 영향을 미치게 된다. 따라서 고장 메커니즘을 분석하여 제품의 신뢰성을 정확히 평가하는 것은 제품의 초기 시장 진입 기간을 단축하여 시장 경쟁력을 강화하는데 중요한 요소로 작용하게 된다. 본 논문에서는 트랙터의 무상보증기간에 이루어진 고장 데이터에 근거하여 주요 고장 부품에 대한 고장 메커니즘 분석을 통하여 고장형태를 규명하고, 신뢰성 분석을 통하여 파워트레인에 대한 B10 수명을 향상시키기 위한 대상 부품을 규명하였다.

• International Journal of Reliability and Applications
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• 제4권2호
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• pp.79-95
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• 2003

Manufacturers collect and analyze field reliability data to enhance the quality and reliability of their products and to improve customer satisfaction. To reduce the data collecting and maintenance costs, the amount of data maintained for evaluating product quality and reliability should be minimized. With this in mind, some industrial companies assemble warranty databases by gathering data from different sources for a particular time period. This “marginal count failure data” does not provide (i) the number of failures by when the product entered service, (ii) the number of failures by product age, or (iii) information about the effects of the operating season or environment. This article describes a method for estimating age-based claim rates from marginal count failure data. It uses covariates to identify variations in claims relative to variables such as manufacturing characteristics, time of manufacture, operating season or environment. A Poisson model is presented, and the method is illustrated using warranty claims data for two electrical products.

• 전기학회논문지
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• 제58권2호
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• pp.308-313
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• 2009

This paper presents a reliability analysis of S-bonds for AF track circuits, which detect train movement and transmit a speed control signal to the train. Field survey shows that S-bonds are exposed to very large vibrations transferred from rail, and suffer from frequent failures when they were installed on ballasted track. We collected the time-to-failure data of S-bonds from the maintenance field of Seoul metro line 2, and made a parametric approach to estimate the statistical distribution that fits the time-to-failure data. The analysis shows that S-bonds have time-to-failure characteristics described by Weibull distribution. The estimated shape parameter of Weibull distribution is 1.1, which means the distribution has constant failure rate characteristics like exponential distribution. The reliability function, hazard function, percentiles and mean lifetime are derived for maintenance support.

• 산업경영시스템학회지
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• 제42권4호
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• pp.194-202
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• 2019

Reliability analysis of the components frequently starts with the data that manufacturer provides. If enough failure data are collected from the field operations, the reliability should be recomputed and updated on the basis of the field failure data. However, when the failure time record for a component contains only a few observations, all statistical methodologies are limited. In this case, where the failure records for multiple number of identical components are available, a valid alternative is combining all the data from each component into one data set with enough sample size and utilizing the useful information in the censored data. The ROK Navy has been operating multiple Patrol Killer Guided missiles (PKGs) for several years. The Korea Multi-Function Control Console (KMFCC) is one of key components in PKG combat system. The maintenance record for the KMFCC contains less than ten failure observations and a censored datum. This paper proposes a Bayesian approach with a Dirichlet mixture model to estimate failure time density for KMFCC. Trends test for each component record indicated that null hypothesis, that failure occurrence is renewal process, is not rejected. Since the KMFCCs have been functioning under different operating environment, the failure time distribution may be a composition of a number of unknown distributions, i.e. a mixture distribution, rather than a single distribution. The Dirichlet mixture model was coded as probabilistic programming in Python using PyMC3. Then Markov Chain Monte Carlo (MCMC) sampling technique employed in PyMC3 probabilistically estimated the parameters' posterior distribution through the Dirichlet mixture model. The simulation results revealed that the mixture models provide superior fits to the combined data set over single models.

• 품질경영학회지
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• 제27권4호
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• pp.241-255
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• 1999

This paper concerns Reliability Analysis System(RAS) developed by LG Electronics, Inc. for collecting, classifying, and analyzing field failure data. To develop this system, a database for the management of field failure data was built and several functions were included to analyze and assess the product reliability. Nonparametric estimation and cumulative hazard plotting techniques were applied to estimate the reliability for a specific period. This system serves not only engineers in charge of quality but also designers who wish to monitor the reliability of their own products.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2006년도 추계 학술발표회 논문집
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• pp.97-112
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• 2006

FRACAS(Failure Reporting, Analysis and Corrective Action System) is intended to provide management visibility and control for reliability and maintainability improvement of hardware and associated software by timely and disciplined utilization of failure and maintenance data to generate and implement effective corrective actions to prevent failure recurrence and to simplify or reduce the maintenance tasks. This process applies to acquisition for the design, development, fabrication, test, and operation or military systems, equipment, and associated computer programs. This paper shows the FRACAS development process and developed FRACAS system for a defense equipment.