• Korean Journal of Construction Engineering and Management
• /
• v.9 no.6
• /
• pp.257-267
• /
• 2008

In order to encourage construction practitioners to acknowledge failures and disseminate the information, the failure information must be documented and accumulated with a well-structured format, which contains not only the fact and result but also the circumstance and cause of the failure. In the Korean construction industry, many failures are not explained clearly and often not even reported publicly, partly because due to the lack of understanding positive aspects of failures, which can improve construction practices as a result of learning from failures. The purpose of this study is to develop a web-based construction failure information system using the case-based reasoning techniques, which can systematically accumulate, manage, and share the valuable failure information using a structured failure cases database. It can be utilized for planning proactive solutions on future failures by searching the very similar past failure cases.

• Proceedings of the KSR Conference
• /
• 2009.05a
• /
• pp.495-504
• /
• 2009

As the Reliability Centered Maintenance(RCM) is being studied, maintenance tasks can be performed effectively through the Risk Priority Number(RPN) evaluation about the components in the system. The RPN is usually calculated through arithmetical operations of three values, Severity, Occurrence, and Detection for each facility. This RPN provides information that includes risk level of the facility and the priority order of maintenance tasks for facility. However, if there is no sufficient historical failure data, it is difficult to calculate the RPN. In this case, historical failure data from other sources can be used and apply this data to korean railway system. In this paper, it is proposed that a new methodology to model the failure rate as a fuzzy membership function. This method is based on failure data from other sources by means of the fuzzy theory and the expert opinion system. And considering assessment tendency of each expert, distortions that happened when the failure rate of facilities is estimated were minimized. This results determine Occurrence values of facilities. Taking advantage of this result., the RPN can be calculated with Severity and Detection of facilities by using the fuzzy operation. The proposed method is applied the rail-way power substation.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.19 no.11
• /
• pp.94-101
• /
• 2020

In the age of industry 4.0, artificial intelligence is being widely used to realize machinery condition monitoring. Due to their excellent performance and the ability to handle large volumes of data, machine learning techniques have been applied to realize the fault diagnosis of different equipment. In this study, we performed the failure mode effect analysis (FMEA) of an aluminum electrolytic capacitor by using deep learning and big data. Several tests were performed to identify the main failure mode of the aluminum electrolytic capacitor, and it was noted that the capacitance reduced significantly over time due to overheating. To reflect the capacitance degradation behavior over time, we employed the Vanilla long short-term memory (LSTM) neural network architecture. The LSTM neural network has been demonstrated to achieve excellent long-term predictions. The prediction results and metrics of the LSTM and Vanilla LSTM models were examined and compared. The Vanilla LSTM outperformed the conventional LSTM in terms of the computational resources and time required to predict the capacitance degradation.

• Journal of the Korean Society for Advanced Composite Structures
• /
• v.3 no.2
• /
• pp.11-18
• /
• 2012

This study proposes flexural failure design criteria of continuous slabs enhanced by a hybrid system of fiber reinforced polymer (FRP) and ultra high performance concrete (UHPC). The proposed hybrid retrofit system is designed to be placed at the top surface of the slabs for flexural strengthening of the sections in both positive and negative moment zones. The enhancing mechanisms of the proposed system for both positive and negative moment regions are presented. The neutral axis of the enhanced sections in positive moment zone at flexural failure is enforced to be in UHPC overlay for preventing the compression in FRP. From this condition, a relationship between design parameters of FRP and UHPC is established. Although the capacity of the proposed retrofit system to enhance flexural strength and ductility is confirmed through experiments of one-way RC slabs having two continuous spans, the retrofitted slabs failed in shear. To prevent this shear failure, a design criteria of flexural failure is proposed.

• Journal of the Korean Society of Systems Engineering
• /
• v.10 no.1
• /
• pp.43-48
• /
• 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.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.6
• /
• pp.3685-3691
• /
• 2015

We developed the platform safety step system for the passenger to avoid misstep accident and secure the pedestrian safety. In this study, we classify platform safety step system into hierarchy system and predict the failure rate of each part and calculate the failure rate & MTBF(Mean Time Between Failure) of each module(sub-system) by means of RBD(Reliability Block Diagram) & FTA(Fault Tree Analysis). Finally, we will propose the reliability analysis results for RAMS analysis of platform safety step system.

• Earthquakes and Structures
• /
• v.16 no.5
• /
• pp.513-522
• /
• 2019

A long-span transmission tower-line system is indispensable for long-distance electricity transmission across a large river or valley; hence, the failure of this system, especially the collapse of the supporting towers, has serious impacts on power grids. To ensure the safety and reliability of transmission systems, this study experimentally and numerically investigates the collapse failure of a 220 kV long-span transmission tower-line system subjected to severe earthquakes. A 1:20 scale model of a transmission tower-line system is constructed in this research, and shaking table tests are carried out. Furthermore, numerical studies are conducted in ABAQUS by using the Tian-Ma-Qu material model, the results of which are compared with the experimental findings. Good agreement is found between the experimental and numerical results, showing that the numerical simulation based on the Tian-Ma-Qu material model is able to predict the weak points and collapse process of the long-span transmission tower-line system. The failure of diagonal members at weak points constitutes the collapse-inducing factor, and the ultimate capacity and weakest segment vary with different seismic wave excitations. This research can further enrich the database for the seismic performance of long-span transmission tower-line systems.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2001.10a
• /
• pp.329-336
• /
• 2001

The numbers of geogrid-reinforced walls are widely used in Korea. This papers present the results of two failure case histories of geogrid-reinforced segmental retaining walls. The geological background of the construction sites, detailed construction sequences, and the amount of rainfall were examined. The failure of these reinforced walls are caused by the improper drainage system and foundation treatment, too sharpened curvature of corner work, and too high height of wall.

• Journal of the Korean Geotechnical Society
• /
• v.31 no.2
• /
• pp.13-25
• /
• 2015

With the increasing usages of micropile, several researchers have been studying the bearing characteristics of micropile or micropile-raft system. But most cases of research were focused on the bearing capacity of micropile-raft system on sand layer. And it was not considered that the bearing capacity of micropile-raft system was affected by the failure mode of soil and pile installation conditions. Thereby this study conducted the numerical analysis to estimate the bearing capacity of micropile-raft system on sand or silt layer with different shear failure mode. It was found that the bearing capacity of micropile-raft system installed in positive or negative angle was larger than that of the system installed in vertical angle, in the case of the sand layer undergoing the general shear failure. In the case of silt layer undergoing the punching shear failure, the bearing capacity of micropile-raft system installed only in negative angle was larger than that installed in vertical or positive angle. And the bearing capacity of foundation system in positive angle was similar to the vertical micropile-raft system.

• Journal of the Korean Society for Precision Engineering
• /
• v.27 no.5
• /
• pp.36-47
• /
• 2010

The Korean Railroad Research Institute (KRRI) has developed the rubber tired AGT system (Model: K-AGT) between 1999 and 2005. The K-AGT is a light rail transit system does not require a driver and generally operates on an elevated railroad for transporting passengers. Accidents caused by driverless vehicles can severely affect social confidence, safety and economy therefore, it is very important to minimize the occurrences of such faults, and to accurately perform detailed maintenance tasks and thoroughly investigate the cause of any repeated failures. This research develops the web-based Preventive Maintenance (PM) system for the KAGT train system. The framework of the PM system is based on performing a reliability analysis and a failure mode effects analyses (FMEA) procedure on all the sub-systems in the K-AGT system. Out of the devices that have a low reliability, the high failure ranked devices are included high in the list for performing the overall maintenance plans. Through registration of historical failure data, the reliability indexes can be updated. Such a process is repeated continuously and can achieve very accurate predictions for device operational life times and failure rates. Therefore, this research describes the development of the overall PM system consists of a reliability analysis module, a failure mode effect analysis module, and maintenance request module.