• Proceedings of the KSR Conference
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• 2003.10c
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• pp.103-108
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• 2003

Among welded structure bogies in use for high speed freight car, a part of bogies manufactured in 1999 and 2000 have found problems that failure occurs in its end beam. In case of a freight car a difference of weight between empty and loading conditions are worse than in case of a passenger car. Moreover its brake system is tread brake without second suspension system. A failure of end beam is supposed to be due to loading by brake rather than vertical loading by freight. This failure can make brake system useless and may be a cause of derailment in the worst case. In this study, in order to be proved the cause of failure and to solve the problem it is described that we have measured load history acted on end beam and set up the procedures.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.57-64
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• 2024

In the industrial field, robots are used to increase productivity by replacing labors with dangerous, difficult, and hard tasks. However, failures of individual industrial robots in the entire production process may cause product defects or malfunctions, and may cause dangerous disasters in the case of manufacturing parts used in automobiles and aircrafts. Although requirements for early diagnosis of industrial robot failures are steadily increasing, there are many limitations in early detection. This paper introduces methods for diagnosing robot failures using sound-based data and deep learning. This paper also analyzes, compares, and evaluates the performance of failure diagnosis using various deep learning technologies. Furthermore, in order to improve the performance of the fault diagnosis system using deep learning technology, we propose a method to increase the accuracy of fault diagnosis based on an inference window. When adopting the inference window of deep learning, the accuracy of the failure diagnosis was increased up to 94%.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.357-367
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• 2021

In general, common cause failures (CCFs) have been modeled with the assumption that components within the same group are symmetric. This assumption reduces the number of parameters required for the CCF probability estimation and allows us to use a parametric model, such as the alpha factor model. Although there are various asymmetric conditions in nuclear power plants (NPPs) to be addressed, the traditional CCF models are limited to symmetric conditions. Therefore, this paper proposes the copulabased CCF model to deal with asymmetric as well as symmetric CCFs. Once a joint distribution between the components is constructed using copulas, the proposed model is able to provide the probability of common cause basic events (CCBEs) by formulating a system of equations without symmetry assumptions. In addition, Bayesian inferences for the parameters of the marginal and copula distributions are introduced and Markov Chain Monte Carlo (MCMC) algorithms are employed to sample from the posterior distribution. Three example cases using simulated data, including asymmetry conditions in total failure probabilities and/or dependencies, are illustrated. Consequently, the copula-based CCF model provides appropriate estimates of CCFs for asymmetric conditions. This paper also discusses the limitations and notes on the proposed method.

• Proceedings of the IEEK Conference
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• 2003.07b
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• pp.703-706
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• 2003

Yield enhancement in semiconductor fabrication is important. It is ideal to prevent all the failures. However, when a failure occurs, it is important to quickly specify the cause stage and take countermeasure. The automatic method of failure pattern extraction from fail bit map provides reduced time to analysis and facilitates yield enhancement. This paper describes the techniques to automatically classifies a failure pattern using a fail bit map, a new simple schema which facilitates the failure analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.643-646
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• 2000

As many industrial systems become more complex, it becomes extremely difficult to diagnose the cause of failures. This paper presents a failure diagnosis approach based on discrete event system theory. In particular, the approach is a hybrid of event-based and state-based ones leading to a simpler failure diagnoser with supervisory control capability. The design procedure is presented along with a pump-valve system as an example.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.4
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• pp.609-628
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• 1995

This paper presents a reliability model and a data-analytic procedure for a repairable unit subject to failures due to multiple non-identifiable causes. We regard a failure cause as a state and assume the life distribution for each cause to be exponential. Then we represent the dependency among the causes by a Markov switching model(MSM) and estimate the transition probabilities and failure rates by maximum likelihood(ML) method. The failure data are incomplete due to masked causes of failures. We propose a specific version of EM(expectation and maximization) algorithm for finding maximum likelihood estimator(MLE) under this situation. We also develop statistical procedures for determining the number of significant states and for testing independency between state transitions. Our model requires only the successive failure times of a unit to perform the statistical analysis. It works well even when the causes of failures are fully masked, which overcomes the major deficiency of competing risk models. It does not require the assumption of stationarity or independency which is essential in mixture models. The stationary probabilities of states can be easily calculated from the transition probabilities estimated in our model, so it covers mixture models in general. The results of simulations show the consistency of estimation and accuracy gradually increasing according to the difference of failure rates and the frequency of transitions among the states.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.10a
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• pp.377-380
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• 1999

This paper dscribes an experimental investigation into the cause of flexural-shear failure in RC beams. The experimental variables are bottom flange width and tension bar location. Then these test results were compared and analyzed to deduce the major cause of critical-shear cracking. As a result, it was found that the propagation of the critical shear crack depended exclusively on the intensity of horizontal cracking.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.794-799
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• 2005

The failure of blades frequently happened in the 300MW LP turbine until now and they are maintaining the blades periodically during outage. So the blade-disk system is analysed by FEM in order to identify the main cause of failure of blade row. It is found that the stress of root's hole is highest in comparison with other parts from the result of the steady stress analysis. Also, the two dangerous frequencies which is related to the resonance condition are found in the interference diagram. one is 1,516 Hz which is related to the operating speed. The other is 2,981 Hz which is related to the 1 nozzle passing frequency. The dynamic stress analysis is per-formed to identify more accurate root cause for failure of blade row. It is confirmed that the dynamic stress of the latter is higher than one of the former. From these results, it is concluded that the former has deeply something to do with the failure of blades more than the latter. Based on versatile investigation and deliberation, the change of blade's grouping is determined to avoid the resonance condition with the operating speed. After the blade grouping is changed, the former frequency vanish completely but the latter is still in existence in the interference diagram. Fortunately, It is confirmed that the dynamic stress of the new blade grouping is lower than one of the old blade grouping. 2 years has passed since modification and the LP turbine is operated well without failure so far.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.9 s.102
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• pp.1100-1107
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• 2005

The failure of blades frequently happened in the 300 MW LP(low pressure) turbine until now and they are maintaining the blades periodically during outage. So the blade-disk system is analysed by FEM in order to identify the main cause of failure of blade row. It is found that the stress of root's hole is highest in comparison with other parts from the result of the steady stress analysis. Also, the two dangerous frequencies which is related to the resonance condition are found in the interference diagram. One is 1,316 Hz. The other is 2,981 Hz which is related to the 1 nozzle passing frequency. The dynamic stress analysis is performed to identify more accurate root cause for failure of blade row It is confirmed that the dynamic stress of the former is higher than one of the latter From these results, it is concluded that the former has deeply something to do with the failure of blades more than the tatter. Based on versatile investigation and deliberation, the change of blade's grouping is determined to avoid the resonance condition with the operating speed. After the blade grouping is changed, the former frequency vanish completely but the latter is still in existence in the interference diagram. Fortunately, It is confirmed that the dynamic stress of the new blade grouping is lower than one of the old blade grouping. 2 years has passed since modification and the LP turbine is operated well without failure so far.

• Journal of Chest Surgery
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• v.19 no.1
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• pp.92-100
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• 1986

Results of reoperation for tissue valve failure were presented with review of current knowledge. Through January 1986, 19 patients required reoperation: 18 had undergone mitral, 2 aortic, and 1 tricuspid valve. Primary tissue failure was the main cause of tissue valve failure: it occurred in 18 valves [15 mitral, 2 aortic, and 1 tricuspid] at a mean postoperative interval of 54-25 months [range 29-120]. During the same period, 2 patients required reoperation for prosthetic valve endocarditis, 1 for paravalvular leakage. The types of valves failed were 12 lonescu-Shiley valves, 5 Hancock valves, and 1 Carpentier-Edwards valve. All 6 patients younger than 15 years of age at first operation had been implanted with lonescu-Shiley valves and failed after a mean interval of 35 months. In contrast, 11 patients older than 15 years had been implanted with 5 Hancock, 6 lonescu-Shiley, and 1 Carpentier-Edwards valve initially, and eventually failed after mean intervals of 81, 53, 47 months each other. The kinds of valves used at reoperation were 8 lonescu-Shiley, 4 Bjork-Shiley, and 6 St. Jude Medical valves for primary tissue failure cases and 3 lonescu-Shiley valves for the other 3 cases. Overall mortality at reoperation was 10%: 5.6% for primary tissue failure, 50% for prosthetic valve endocarditis. In 15 cases [all mitral] primary tissue failure were caused by calcification associated with or without leaflet destruction or fibrous ingrowth, and in 2 cases [all aortic] caused by cusp perforation and tearing without any evidence of calcification. In conclusion: 1 primary tissue failure is the main cause of reoperation in patients with tissue valve failure; 2. the majority of the failed valves is in mitral position; 3. leaflet calcification is the leading pathology of primary tissue failure; 4, reoperation for tissue valve failure may be a major concern, although the mortality is low; 5. the limited durability of tissue valve suggests its use be restricted to selected cases.