• Plant Journal
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• v.12 no.2
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• pp.31-35
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• 2016

A method of failure data management for Reliability-Centered Maintenance was shown for a boiler feedwater pump of a power plant. The major part of it is an analysis of failure mode, failure cause, and failure effects, which is the main component of a failure data base like OREDA(Offshore Reliability Data). Case study shows main element of the preventive maintenance planning such as the maintenance period can be statistically determined from the failure data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1541-1544
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• 2003

In this study, embodying reliability block diagram based on the web and reliability analysis technology are developed. RBD(reliability Block Diagram) represents the functional relation between elements in any product. Among relations between elements. there are serial, parallel, bridge, and stand by, etc. Advantages of developed system are integrated datum about reliability (NPRD, EPRD, MIL-HDBK 217F, NSWC. OREDA. Bellcore, and domestic institutes & companies datum). graphic user interface for convenience, and the various service analyzes the failure history data of parts.

• Journal of the Korean Institute of Gas
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• v.21 no.4
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• pp.16-20
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• 2017

Current maintenance system are unable to suggest solid basis of maintenance for roating and static equipment. When a filure occurs, replacement or repair without proper process of failure cause analysis would often result in even greater risk. Therefore in this study, a procedure of Reliability Centred Maintenance is develped in order to perform maintenance in preventive mainer (PM), and to effectively manage risk of any equipment based on failure types and respective rates of failure. Ultimately an equipment with higher risk will be monitored which will lead to effectively prevent and manage any major accident.

• Journal of the Korean Society of Safety
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• v.23 no.2
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• pp.37-44
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• 2008

The safety assessment for facility industry is now being periodically performed. For the purpose of scientific safety management, QRA(Quantitative Risk Assessment) is also being performed, and reliability data of the facilities is essential to perform the assessment. Generally, the existing safety assessment is performed by using the values announced in other industry processes, which result in the drop of reliability. In order to solve this problem, there is an urgent need to establish reliability database for the facilities. The most appropriate method is to perform a direct reliability analysis towards the facilities undergoing safety assessment. In this study, in compliance with the assessment method and procedure of OREDA-2002 handbook, the facility reliability data are collected, which include the calendar time and operational time in terms of different facility items, the number of failures in terms of different failure mode, the mean, standard deviation, lower limit and upper limit of failure rate, and the failure rate. And the data process method for this special occasion is also proposed when the number of failure is 0.

• Journal of Hydrogen and New Energy
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• v.26 no.2
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• pp.192-198
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• 2015

Fault Tree Analysis to predict the lifetime in the design process of LNG compressor is considered. Fault Trees for P & ID of the compressor are created. Individual components that comprise the compressor are configured with the basic event. The failure rates in the PDS and OREDA are applied. As results, the system failure rate and the reliability over time are obtained. Further, the power transmission and the shaft seal system is confirmed to confidentially importantly contribute to the overall lifetime of the system. These techniques will help to improve the reliability of design of large scale machinery such as a plant.

• Journal of the Korean Society of Safety
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• v.39 no.3
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• pp.75-83
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• 2024

Accurately assessing and managing risks in any endeavor is crucial. Risk assessment in engineering translates the abstract concept of risk into actionable strategies for systematic risk management. However, risk validation is met with significant skepticism, particularly concerning the uncertainty of probability. This study aims to address the aforementioned uncertainty in a multitude of ways. Firstly, instead of relying on deterministic probability, it acknowledges uncertainty and presents a probabilistic interval. Secondly, considering the uncertainty interval highlighted in OREDA, it delineates the bounds of the probabilistic interval. Lastly, it investigates how much explanatory power deterministic probability has within the defined probabilistic interval. By utilizing fault tree analysis (FTA) and integrating confidence intervals, a probabilistic risk assessment was conducted to scrutinize the explanatory power of deterministic probability. In this context, explanatory power signifies the proportion of probability within the probabilistic risk assessment interval that lies below the deterministic probability. Research results reveal that at a 90% confidence interval, the explanatory power of deterministic probability decreases to 73%. Additionally, it was confirmed that explanatory power reached 100% only with a probability application 36.9 times higher.