• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.649-664
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• 2017

Purpose: This paper introduces the technology of prognostics for Industry 4.0 and presents its application procedure for fitness-for-service assessment of natural gas pipelines according to ISO 13374 framework. Methods: Combining data-driven approach with pipe failure models, we present a hybrid scheme for the gas pipeline prognostics. The probability of pipe failure is obtained by using the PCORRC burst pressure model and First Order Second Moment (FOSM) method. A fuzzy inference system is also employed to accommodate uncertainty due to corrosion growth and defect occurrence. Results: With a modified field dataset, the probability of failure on the pipeline is calculated. Then, its residual useful life (RUL) is predicted according to ISO 16708 standard. As a result, the fitness-for-service of the test pipeline is well-confirmed. Conclusion: The framework described in ISO 13374 is applicable to the RUL prediction and the fitness-for-service assessment for gas pipelines. Therefore, the technology of prognostics is helpful for safe and efficient management of gas pipelines in Industry 4.0.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.295-300
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• 2007

Probabilistic Risk Assessment considering statistically random variables is performed for the preliminary design of a Arch Bridge. Component reliabilities of girders have been evaluated using the response surfaces of the design variables at the selected critical sections based on the maximum shear and negative moment locations. Response Surface Method (RSM) is successfully applied for reliability analyses for this relatively small probability of failure of the complex structure, which is hard to be obtained by Monte-Carlo Simulations or by First Order Second Moment Method that can not easily calculate the derivative terms of implicit limit state functions. For the analysis of system reliability, parallel resistance system composed of girders is changed into parallel series connection system. The upper and lower probabilities of failure for the structural system have been evaluated and compared with the suggested prediction method for the combination of failure modes. The suggested prediction method for the combination of failure modes reveals the unexpected combinations of element failures in significant]y reduced time and efforts compared with the previous permutation method or system reliability analysis method.

• Journal of Korean Biological Nursing Science
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• v.19 no.4
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• pp.227-240
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• 2017

Purpose: The purpose of this review was to identify the current status of nursing studies on heart failure (HF) patients in South Korea and to suggest future study direction. Methods: A literature review of databases such as KoreaMed, KERIS and nursing and allied health journal were searched with key terms 'heart failure' and 'nursing' for the period from January 2000 to February 2017. A total of 35 studies including 28 articles and 7 theses met the inclusion criteria. Results: Twenty-seven out of 35 studies were observational studies on outpatients and most of the studies did not mention the ejection fraction and New York Heart Association functional classification class (NYHA class) in the inclusion criteria. Self-care and health-related quality of life as psychological factors, and physical activity as a biological factor, were used as main variables. However, we found it difficult to understand how much score indicates better quality of life because of an inconsistent and wide score. In quality assessment, 8 intervention studies had no serious flaws. Conclusion: Further studies should consider more biological and social factors influencing HF. The quality assessment with respect to nursing intervention studies in HF showed that randomized and double-blind trials are needed.

• Geomechanics and Engineering
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• v.24 no.3
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• pp.281-293
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• 2021

Uncertainties in geomechanical input parameters which mainly related to inappropriate data acquisition and estimation due to lack of sufficient calibration information, have led wellbore instability not yet to be fully understood or addressed. This paper demonstrates a workflow of employing Quantitative Risk Assessment technique, considering these uncertainties in terms of rock properties, pore pressure and in-situ stresses to makes it possible to survey not just the likelihood of accomplishing a desired level of wellbore stability at a specific mud pressure, but also the influence of the uncertainty in each input parameter on the wellbore stability. This probabilistic methodology in conjunction with Monte Carlo numerical modeling techniques was applied to a case study of a well. The response surfaces analysis provides a measure of the effects of uncertainties in each input parameter on the predicted mud pressure from three widely used failure criteria, thereby provides a key measurement for data acquisition in the future wells to reduce the uncertainty. The results pointed out that the mud pressure is tremendously sensitive to UCS and SHmax which emphasize the significance of reliable determinations of these two parameters for safe drilling. On the other hand, the predicted safe mud window from Mogi-Coulomb is the widest while the Hoek-Brown is the narrowest and comparing the anticipated collapse failures from the failure criteria and breakouts observations from caliper data, indicates that Hoek-Brown overestimate the minimum mud weight to avoid breakouts while Mogi-Coulomb criterion give better forecast according to real observations.

• Journal of Applied Reliability
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• v.18 no.3
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• pp.193-200
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• 2018

Purpose: In this study, the life of the motor is investigated by performing the accelerated life test with the brush wear of the industrial cleaner motor as the main failure mode. Methods: The accelerating stress factor of the accelerated life test is a voltage, which can increase the number of revolutions of the motor to accelerate the brush wear due to the friction between the brush and the commutator. Also, the accelerating stress level was determined after determining the maximum allowable level of the voltage through the preliminary test. Results: The motor failure time at each accelerating stress level was predicted by regression analysis with brush wear length as performance degradation data. The main failure mode, which is brush wear, of the motor was reproduced by this test. The shape parameter of the Weibull distribution was confirmed to be the same statistically at all accelerating stress levels by the likelihood ratio test. Conclusion: The life of the motor was investigated by performing the accelerated life test with the brush wear of the industrial cleaner motor as the main failure mode. Through the accelerating test method of the cleaner motor, various life expectancy and life expectancy of the acceleration factor are predicted.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.351-353
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• 2006

Preventive maintenance can avail the generating unit to reduce cost and gain more profit in a competitive supply-side power market. so, it is necessary to perform reliability analysis on the systems in which reliability is essential. In this paper, FMECA assessment adopted using real historical failure data in Korean power plants for apply RCM analytical method. The stochastic FMECA is an engineering analysis and a core activity performed by reliability engineers to review the effects of probable failure modes of generating unit and assemblies of the power system on system performance. Optimal RCM schedule which is considered the severity level of each generating unit and failure probability from failure prediction of generating unit can be planned using proposed FMECA with IOE index.

• Journal of the Korean Ceramic Society
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• v.34 no.2
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• pp.157-162
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• 1997

Silicon Nitride samples with different microstructure were prepared by hot pressing and subsequent heat treatment under N2 gas pressure. The fracture toughness (KIC)of Si3N4 increased with the increase of grain size, but the bending strength of plain specimen($\sigma$F) decreased. The relation between fracture stress($\sigma$c) and equivalent crack length(ae) agreed well with the calculated values by process zone size failure criterion. A probabilistic failure assessment curve is proposed based on both statistical character of $\sigma$F and KIC.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.324-327
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• 2001

This paper shows an example of the Design Review and Common-Cause Failure (CCF) Modeling of mechanical Parts. Reliability should be continuously monitored during the entire period of design. Design Review is the procedure to improve the reliability for the product. We proposed the reliability assessment and design review method. CCF Model is the general dependent model considering the failure mode effects several component simultaneously. This study considers the computation of the network with dependent components. It is important that CCF model is applied for mechanical pars.

• Journal of the Korean Society for Railway
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• v.9 no.6 s.37
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• pp.725-731
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• 2006

Hot Standby sparing system detecting faults by using software, and being tolerant any faults by using Hardware Redundancy is difficult to perform quantitative reliability prediction and to detect real time faults. Therefore, this paper designs Hot Standby sparing system using hardware basis self checking logic in order to overcome this problem. It also performs failure mode analysis of Hot Standby sparing system with designed self checking logic by using FMEA (Failure Mode Effect Analysis), and identifies reliability assessment of the controller designed by quantifying the numbers of failure development by using FTA (Fault Tree Analysis)

• Nuclear Engineering and Technology
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• v.33 no.6
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• pp.596-604
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• 2001

This paper quantitatively presents the effects of important factors of the probabilistic safety assessment (PSA) of safety-critical digital systems. The result which is quantified using fault tree analysis methodology shows that these factors remarkably affect the system safety. In this paper we list the factors which should be represented by the model for PSA. Based on the PSA experience, we select three important factors which are expected to dominate the system unavailability. They are the avoidance of common cause failure, the coverage of fault tolerant mechanisms and software failure probability. We Quantitatively demonstrate the effect of these three factors. The broader usage of digital equipment in nuclear power plants gives rise to the safety problems. Even though conventional PSA methods are immature for applying to microprocessor-based digital systems, practical needs force us to apply it because the result of PSA plays an important role in proving the safety of a designed system. We expect the analysis result to provide valuable feedback to the designers of digital safety- critical systems.