• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.9
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• pp.1169-1174
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• 2013

Most products are indeed governed by multiple failure modes. However, there are few cases in which reliability analysis applies to only one failure mode at a time. Furthermore, reliability data do not include information about failure modes, or the reliability analysis is performed using a representative failure mode. The Weibull shape parameter for failure modes is more important than one for products in the reliability qualification test. This paper presents reliability analysis methods for a mechanical component with multiple failure modes. These methods include the competing failure modes (CFM) method and the mixed Weibull method. Pneumatic cylinder test data with three failure modes are presented to estimate the shape parameter for each separate failure mode. In addition, reliability measures (B10 life, characteristic life) of the pneumatic cylinder considering three failure modes were compared with those assuming a single failure mode.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.5
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• pp.399-407
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• 2007

Two reliability models, AFDA(Approximate Full Distribution Approach) and Monte-Carlo simulation method, are directly developed to study on both hydraulic failure mode of berm recession and structural failure mode of armour breakage of berm breakwaters. By comparing the present results with the results of other researcher, it may be confirmed that two reliability models can be straightforwardly applicable to berm breakwaters. Relative influence of each random variable on hydraulic and structural failure probabilities could be properly analyzed. The upper bound and the lower bound of failure probability can be evaluated by using bi-modal bounds of the multiple failure mode analysis, from which it may be possible to investigate some kinds of dependence into between two failure modes. Finally, it may also be found that the structural failure mode of armour breakage could become a main failure mode of berm breakwaters in the condition of more than any allowable berm recession.

• Journal of Korea Water Resources Association
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• v.43 no.11
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• pp.967-976
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• 2010

AFDA (Approximate Full Distribution Approach) model of FORM (First-Order Reliability Model) which can quantitatively calculate the probability that storm sewer reach to performance limit state was developed in this study. It was defined as a failure if amount of inflow exceed the capacity of storm sewer. Manning's equation and rational equation were used to determine the capacity and inflow of reliability function. Furthermore, statistical characteristics and distribution for the random variables were analyzed as a reliability analysis. It was found that the statistical distribution for annual maximum rainfall intensity of 10 cities in Korea is matched well with Gumbel distribution. Reliability model developed in this study was applied to Y shaped storm sewer system to calculate the probability that storm sewer may exceed the performance limit state. Probability of failure according to diameter was calculated using Manning's equation. Especially, probability of failure of storm sewer in Mungyeong and Daejeon was calculated using rainfall intensity of 50-year return period. It was found that probability of failure can be significantly increased if diameter is decreased below the original diameter. Therefore, cleaning the debris in sewer pipes to maintain the original pipe diameter should be one of the best ways to reduce the probability of failure of storm sewer. In sewer system, two sewer pipes can flow into one sewer pipe. For this case, probability of system failure was calculated using multiple failure mode. Reliability model developed in this study can be applied to design, maintenance, management, and control of storm sewer system.

• Journal of Korean Society for Quality Management
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• v.42 no.1
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• pp.43-61
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• 2014

Purpose: This study identifies preventive measures for VOC management by analyzing the causes and effects of factors that contribute to high risk service failure using FMEA on KORAIL VOC data. Methods: Two research methods were used. First, a Risk Priority Number (RPN) was assigned to each KORAIL VOC based on Failure Mode and Effect Analysis (FMEA). Second, multiple regression analysis was run with RPN factors that include severity, occurrence, and detection as the independent variables and customer dissatisfaction as the dependent variable. Results: Multiple regression analysis showed that RPN factors including severity, occurrence, and detection had significantly positive relationship with customer dissatisfaction. Based on these results, an FMEA was performed on VOC categories with high RPN for railroad stations including platform, ticketing, ticket verification, parking, and escalator, and VOC categories with high RPN for trains including entrance doors, cafes, air quality, announcement, and ticket verification. Conclusion: This study has practical implications to service failure management. A priority order using FMEA was established for the list of customer dissatisfactions that should be addressed to actively manage service failure, and strategies for tackling this priority list are offered.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.508-518
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• 2008

Reliability and sensitivity analysis of the design parameters for a section of caisson type quaywall which is the most applicable in Korea were performed. It was tried to estimate probabilities of failure for the system of the multiple failure modes and to analyze LCC in the quaywall structure. The reliability analysis was performed by FORM. Also, sensitivity indices were estimated using the reliability indices, which may be used inferring effects of each design parameter on the reliability indices. As a result, the coefficient of friction between caisson and rubble, the moment by self weight and the moment of resistance mostly affected on the reliability indices in the sliding, overturning and foundation failure, respectively. System reliability theorem was applied in order to estimate the probabilities of failure for the system of the multiple failure modes. As the results of estimation of the probabilities of failure for the system, all cases were more conservative than those for the elements, according to both failure mode and load combination applied to series system. It entirely exceeded the target reliability index, but it was consistent with the theorem. According to the optimum LCC with the width of the caisson, the probability of failure exceeded the target probability of failure at then time. Therefore, it was judged to be insufficient to the practical application.

• Journal of the Korean Geotechnical Society
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• v.29 no.9
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• pp.71-80
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• 2013

This work studies the reliability analysis of a slope that considers multiple failure modes. The analysis consists of two parts. First, significant failure modes that contribute most to system reliability are determined. The so-called barrier method proposed by Der Kiureghian and Dakessian to identify significant failure modes successively is employed. Second, the failure probability for the slope is estimated on the basis of the identified significant failure modes and corresponding design points. For reliability problems entailing multiple design points, failure probability can be estimated by the multi-point first-order reliability method (FORM), Ditlevsen's bounds method, and Monte Carlo simulation. In this paper, a comparative study between these methods has been made through example problems. Analysis results showed that while a soil slope may have a large number of potential slip surfaces, its system failure probability is usually governed by a few significant slip surfaces. Therefore, the most important step in the system reliability analysis for a soil slope is to identify all the significant failure modes in an efficient way.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.12
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• pp.85-91
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• 2021

In our daily life, artificial intelligence performs simple and complicated tasks like us, including operating mobile phones and working at homes and workplaces. Artificial intelligence is used in industrial technology for diagnosing various types of equipment using the machine learning technology. This study presents a fault mode effect analysis (FMEA) of start motors using machine learning and big data. Through multiple data collection, we observed that the primary failure of the start motor was caused by the melting of the magnetic switch inside the start motor causing it to fail. Long-short-term memory (LSTM) was used to diagnose the condition of the magnetic locations, and synthetic data were generated using the synthetic minority oversampling technique (SMOTE). This technique has the advantage of increasing the data accuracy. LSTM can also predict a start motor failure.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.2
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• pp.137-147
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• 2008

A reliability analysis has been performed to investigate the systematic stability of multi-failure modes of rubble-mound breakwaters. The reliability functions of four different failure modes are established straightforwardly. AFDA(Approximate Full Distribution Approcah) reliability models for each failure modes are directly developed and satisfactorily calibrated through the comparison with CIAD's results. In the reliability analysis of single failure mode, the probabilities of failure are calculated and the influence coefficients of random variables in the failure modes are properly evaluated. Meanwhile, three different models such as uni-modal bounds, bimodal bounds, and PNET are applied to evaluate the probabilities of failure of multi-failure modes for rubble-mound breakwaters. It may be found that uni-modal bounds tend to overestimate the probability of failure of multi-failure modes. Therefore, for the systematic reliability analysis of multi-failure modes, it is recommended to use bi-modal bounds or PNET which consider the correlation between the failure modes for rubble-mound breakwaters. By introducing the reliability analysis of multi-failure modes, it could be possible to find out the additional probabilities of failure occurred by the multi-failure modes of a multi-component system such as rubble-mound breakwaters.

• Structural Monitoring and Maintenance
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• v.5 no.3
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• pp.345-361
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• 2018

The set of processes performed to determine the dynamic characteristics of the constructed structures is named experimental modal analysis. Using experimental modal analysis and interpreting its results, structural failure can be assessed and then it would be possible to plan for their repair and maintenance. The purpose of the experimental modal analysis is to determine the resonance frequencies, mode shapes and Mode damping for the structure. Diverse methods for determining the shape of the mode by various researchers have been presented. There are pros and cons for each of these methods. This paper presents a method for determining the mode shape of the structures using the response spectrum in the experimental modal analysis. In the first part, the principles of the proposed method are described. Then, to check the accuracy of the results obtained from the proposed method, single and multiple degrees of freedom models were numerically and experimentally investigated.

• Journal of the Society of Naval Architects of Korea
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• v.28 no.2
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• pp.251-267
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• 1991

Plastic strength analysis using plastic failure mode as a limit state is adopted instead of a conventional elastic structural analysis to predict the ultimate strength of Web frame idealized by a plane frame. Linear programming arid Compact procedure are developed for determining the collapse load factor. It is found that the final results are good agreement with the results of Elasto-plastic analysis. Besides, the redundant structures like Web frame is known to have multiple failure modes. Web frame may collapse under any of the possible failure modes. Thus, the identification of these possible failure modes is necessary and very important in the reliability analysis of Web frame. In order to deal with multiple failure modes, automatic generation method of all failure modes and basic failure modes is used for selecting the dominant failure modes. The probability of failure pastic collapse of Web frame is calculated using these dominant failure modes. The safety of Web frame is asscssed and compared by performing the deterministic and probabilistic analysis.