• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.351-352
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• 2006

There are many methodologies fur doing analysis of system's reliability in early design stage. Among the methods, PRISM is, as compared to MIL-HDBK-217, a newly developed technology but not easy to use. Because PRISM provides models that predict a part failure rate and field database, called EPRD and NPRD that can be combined with prediction models. This paper presents some capabilities of the prediction models in PRISM and usability of EPRD and NPRD database in system level reliability prediction.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.5
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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.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1749-1753
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• 2007

The reliability, that is Long-Term Quality, require an approaching different from Short-Term Quality which is used before. As the electronic components are able to be easily normalized on the reliability testing, various testing standards are used. In this study, we proposed two reliability simulator that is PoF(Physics of Failure)-based and failure rate models-based. PoF-based simulator is introduced based on CalceEP program that is created by University of Maryland. This simulator can be modified by user interface of properties and PoF models and operated on stand alone system. Failure rate models-based simulator introduced according to analyzing reliability prediction documents. Also, unified database including failure data models is built from existing MIL-HDBK-217F N2, PRISM, and Bellcore, and web-based simulator is developed. The developed reliability simulator will service of the PoF model, properties, failure rate model accumulated and its data by web and internet.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.1
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• pp.71-78
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• 1993

A Baysian approach is proposed is estimating the mission failure rates by criticalities. A mission failure which occurs according to a Poisson process with unknown rate is assumed to be classified as one of the criticality levels with an unknown probability. We employ the Gamma prior for the mission failure rate and the Dirichlet prior for the criticality probabilities. Posterior distributions of the mission rates by criticalities and predictive distributions of the time to failure are derived.

• Journal of Applied Reliability
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• v.17 no.2
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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.

• 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.

• Geomechanics and Engineering
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• v.35 no.6
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• pp.647-663
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• 2023

The investigation of the disc cutter wear prediction has an important guiding role in TBM equipment selection, project planning, and cost forecasting, especially when tunneling in a long-distance rock formations with high strength and high abrasivity. In this study, a comprehensive database of disc cutter wear data, geological properties, and tunneling parameters is obtained from a 1326 m excavated metro tunnel project in leptynite in Shenzhen, China. The failure forms and wear consumption of disc cutters on site are analyzed with emphasis. The results showed that 81% of disc cutters fail due to uniform wear, and other cutters are replaced owing to abnormal wear, especially flat wear of the cutter rings. In addition, it is found that there is a reasonable direct proportional relationship between the uniform wear rate (WR) and the installation radius (R), and the coefficient depends on geological characteristics and tunneling parameters. Thus, a preliminary prediction formula of the uniform wear rate, based on the installation radius of the cutterhead, was established. The correlation between some important geological properties (K_V and UCS) along with some tunneling parameters (F_n and p) and wear rate was discussed using regression analysis methods, and several prediction models for uniform wear rate were developed. Compared with a single variable, the multivariable model shows better prediction ability, and 89% of WR can be accurately estimated. The prediction model has reliability and provides a practical tool for wear prediction of disc cutter under similar hard rock projects with similar geological conditions.

• Journal of Industrial Technology
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• v.27 no.B
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• pp.255-261
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• 2007

Product reliability plays a significantly important role these days. This study has been performed to examine the widely being used specifications, MIL-HDBK-217 and SR-332 for electronic parts. We specifically selected an electronic ballast of the low wattage fluorescent lamp for the study. We briefly reviewed the reliability specifications with the basic concepts of the ballast. We then valuated failure rates of the parts using MIL-HDBK-217 and SR-332 specifications. Since the quality and environment factor values are subjectively determined for failure rate evaluations, we excluded them for comparison.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.11
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• pp.218-226
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• 1998

In this study a neural network based expert system designed to diagnose operating status of a rotating spindle system supported by ball bearings was introduced. In order to facilitate practical failure situations, five exemplary abnormal status was fabricated. Out of several possible data source locations, seven most effective spots were chosen and proven to be the most successful in predicting single and multiple abnormalities. Increased signal strength was measured around where abnormality was embedded. Signal mea-surement locations producing high prediction rate were also classified. Even though multiple abnormalities were hard to be decoupled into their individual causes, proposed diagnostic system was somewhat effective in predicting such cases under certain combination of sensor locations. Among several abnormal operating conditions, highest prediction rate can be expected when signal is spoiled by the failure or damage in outer race. Proposed diagnostic system was again proven to be the most effective system in analyzing and ranking the importance of data sources.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.873-876
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• 2002

This paper presents the effect of internal corrosion, external corrosion, material properties, operation condition, earthquake, traffic load and design thickness in pipeline on the failure prediction using a failure probability model. A nonlinear corrosion is used to represent the loss of pipe wall thickness with time. The effects of environmental, operational, and design random variables such as a pipe diameter, earthquake, fluid pressure, a corrosion rate, a material yield stress and a pipe thickness on the failure probability are systematically investigated using a failure probability model for the corrosion pipeline.