• Journal of the Korean Society of Safety
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• v.21 no.1 s.73
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• pp.6-14
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• 2006

The development of automatic production systems have required intelligent diagnostic and monitoring functions to overcome system failure and reduce production loss by the failure. In order to perform accurate operations of the intelligent system, implication about total system failure and fault analysis due to each mechanical component failures are required. Also solutions for repair and maintenance can be suggested from these analysis results. As an essential component of a mechanical system, a bearing system is investigated to define the failure behavior. The bearing failure is caused by lubricant system failure, metallurgical deficiency, mechanical condition(vibration, overloading, misalignment) and environmental effects. This study described slab transfer equipment fault train due to stress variation and metallurgical deficiency from lubricant failure by using FTA.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.196-197
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• 2006

Preventive maintenance can avail the generation utilities 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, RCM (Reliability -Centered Maintenance) analytical method is adopted using real historical failure data in Korean power plants. Therefore, the reliability -based Probability model for predicting the failures of components in the power plant is also established, and application to FMECA(Failure Mode Effects and Critical Analysis) consideration of failure probability, Based on the weighting ranking of generating equipments which status to be probability estimation by FMECA. The FMECA is an engineering analysis and a core activity performed by reliability engineers to review the effects of probable failure modes of generating equipments and assemblies of the power system on system performance. The results of this paper show that application of FMECA with stochastic approach to the preventive maintenance can efficiently avail decreasing the cost on maintenance and hence improve the total benefit.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.194-201
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• 2012

Because the difference between products and services are getting less and less, service and manufacturing companies' efforts are increasingly focused on utilizing services to satisfy customers' needs under today's competitive market environment. The value of services depends on service reliability that is identified by satisfaction derived from the relationship between customer needs and service providers. In this paper, we extend concepts from the fault tree analysis for reliability analysis of tangible systems to services. We use an event-based process model to facilitate service design and represent the relationships between functions and failures in a service. The objective of this research is to propose a method for evaluating service reliability based on service processes using service blueprint and FTA. We can identify the failure mode of service in a service delivery process with a service blueprint. The fuzzy membership function is used to characterize the probability of failure based on linguistic terms. FTA is employed to estimate the reliability of service delivery processes with risk factors that are represented as potential failure causes. To demonstrate implementation of the proposed method, we use a case study involving a typical automotive service operation.

• International Journal of Reliability and Applications
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• v.12 no.1
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• pp.1-14
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• 2011

This paper discusses the stochastic analysis and the statistical inference of a quadratic failure rate semi-Markov reliability model. Maximum likelihood procedure will be used to obtain the estimators of the parameters included in this reliability model. Based on the assumption that the lifetime and repair time of the system units are random variables with quadratic failure rate, the reliability function of this system is obtained. Also, the distribution of the first passage time of this system is derived. Many important special cases are discussed.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.162-168
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• 2009

FMEA(Failure Mode and Effect Analysis) is a failure analysis method for the system to identify the potential failure modes, and their effects and causes to reduce or mitigate the critical effects of the system. FMEA for railway was introduced with reliability of railway system, and this was used for identifying and analysing the possible hazards qualitatively to meet the requirements in early stage of business. In general, the overall failure data of system could be managed from design stage by FMEA, and also the countermeasures to prevent many predicted failures could be established by identification of failure modes and assement of failure effects by FMEA. Using these advantages of FMEA, the effectiveness of reliability improvement could be expected if FMEA is applied continuously in operation stage. It is essential that railway vehicles are maintained with high level of safety and reliability not to happen any failures in operation. This paper is proposed the proper FMEA for maintenance of railway vehicles compared with existing FMEA.

• Earthquakes and Structures
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• v.14 no.5
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• pp.425-436
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• 2018

The design of seismically isolated structures considering the stochastic nature of excitations, base isolators' design parameters, and superstructure properties requires robust reliability analysis methods to calculate the failure probability of the entire system. Here, by applying artificial neural networks, we proposed a robust technique to accelerate the estimation of failure probability of equipped isolated structures. A three-story isolated building with susceptible facilities is considered as the analytical model to evaluate our technique. First, we employed a sensitivity analysis method to identify the critical sources of uncertainty. Next, we calculated the probability of failure for a particular set of random variables, performing Monte Carlo simulations based on the dynamic nonlinear time-history analysis. Finally, using a set of designed neural networks as a surrogate model for the structural analysis, we assessed once again the probability of the failure. Comparing the obtained results demonstrates that the surrogate model can attain precise estimations of the probability of failure. Moreover, our proposed approach significantly increases the computational efficiency corresponding to the dynamic time-history analysis of the structure.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.4
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• pp.27-33
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• 2013

In this study, the FMEA and FTA for reliability analysis of hybrid rocket motor are performed, that was designed in the Hybrid Rocket Propulsion Laboratory of Korea Aerospace University. In order to carry out these analyses the structure of the hybrid rocket motor is hierarchically divided into 36 parts down to the component level and FMEA is carried out with 72 failure modes. Reliability is assessed based on the FMEA, and the results are used in the FTA to evaluate the overall system reliability. In the FMEA, the relationship between the cause and failure modes, effects and their risk priorities are evaluated qualitatively. 27 failure modes are chosen as those with the critical severity that should be improved with priority. As a result of the FMEA / FTA study, a series of design or material changes are made for the improvement of reliability.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.04a
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• pp.102-109
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• 2001

In order to take account of the statistical properties of probability variables used in the structural analysis, the conventional approach using the safety factor based on past experience usually estimated the safety of a structure. The real structures could only be analyzed with the error in estimation of loads, material characters and the dimensions of the members. But the errors should be considered systematically in the structural analysis. Structural safety could not precisely be appraised by the traditional structural design concept. Recently, new approach based on the probability concept has been applied to the assessment of structural safety using the reliability concept. Thus, the computer program by the Probabilistic FEM is developed by incorporating the probabilistic concept into the conventional FEM method. This paper estimated for the reliability of a plane stress structure by Advanced First-Order Second Moment method using von Mises, Tresca and Mohr-Coulomb failure criterions. The reliability index and failure probability of attained by the Monte Carlo Simulation method with the von Mises criterion were same as PFEM, but the Monte Carlo Simulation were very time-consuming. The variance of member thickness and load could influence the reliability and failure probability most sensitively among the design variables from the results of the parameter analysis. And proper failure criterion must be used to design safely.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.1
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• pp.101-115
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• 2013

This paper examines the application of structural reliability analysis to submarine pressure hulls to clarify the merits of probabilistic approach in respect thereof. Ultimate strength prediction methods which take the inelastic behavior of ring-stiffened cylindrical shells and hemi-spherical shells into account are reviewed. The modeling uncertainties in terms of bias and coefficient of variation for failure prediction methods in current design guidelines are defined by evaluating the compiled experimental data. A simple ultimate strength formulation for ring-stiffened cylinders taking into account the interaction between local and global failure modes and an ultimate strength formula for hemispherical shells which have better accuracy and reliability than current design codes are taken as basis for reliability analysis. The effects of randomness of geometrical and material properties on failure are assessed by a prelimnary study on reference models. By evaluation of sensitivity factors important variables are determined and comparesons are made with conclusions of previous reliability studies.

• International Journal of Reliability and Applications
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• v.15 no.1
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• pp.51-64
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• 2014

This paper develops a warranty cost model for complex systems with imperfect repair within a warranty period by addressing a practical case that the first inter-failure interval is longer than any other inter-failure intervals. The product is in its best condition before the first failure if repair is imperfect. After the imperfect repair, other inter-failure intervals which are explained by renewal processes, are stochastically smaller than the first inter-failure interval. Based on this idea, we suggest the failure-interval-failure-criterion model. In this model, we consider two random variables, X and Y where X represents failure intervals and Y represents failure criterion. We also obtain the distribution of the number of failures and conduct the warranty cost analysis. We investigate different types of warranty cost models, reliabilities and other measures for various systems including series-parallel configurations. Several numerical examples are discussed to demonstrate the applicability of the methodologies derived in the paper.