• Journal of the Korean Society for Precision Engineering
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• v.18 no.6
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• pp.74-79
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• 2001

In this study, a failure mode analysis of CNC machining center is described. First, the system is classified through subsystems into components using part lists and drawings. The component failure rate and failure mode analysis are performed to identify the weak components of a machining center with reliability database. The failure probabilistic function of mechanical part is analyzed by Weibull distribution. The Kolmogorov-Smirnov test is also used to verify the goodness of fit.

• Proceedings of the Korean Reliability Society Conference
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• 2000.11a
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• pp.329-333
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• 2000

Delay time analysis is a pragmatic mathematical concept readily embraced by engineers which has been developed as a means to model maintenance decision problem. This paper considers an inspection period using delay time analysis for fishing vessel equipment. We assume that delay time distribution is Weibull and inspections are perfect. In this paper, we determine the optimal inspection period which minimize the expected downtime per unit time.

• International Journal of Reliability and Applications
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• v.2 no.2
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• pp.99-105
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• 2001

Delay time analysis is a pragmatic mathematical concept readily embraced by engineers which has been developed as a means to model maintenance decision problem. This paper considers an inspection period using delay time analysis for fishing vessel equipment. We assume that delay time has a Weibull distribution. In this paper, we determine the optimal inspection period which minimize the expected downtime per unit time. Explicit solutions for the optimal inspection are presented for illustrative purposes.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.818-822
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• 2003

We propose a software-reliability growth model incoporating the amount of uniform and Weibull testing efforts during the software testing phase in this paper. The time-dependent behavior of testing effort is described by uniform and Weibull curves. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, the model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. The optimum release time is determined by considering how the initial reliability R(x|0) would be. The conditions are $R(x|0)>R_o$, $R_o>R(x|0)>R_o^d$ and $R(x|0)<R_o^d$ for uniform testing efforts. Ideal case is $R_o>R(x|0)>R_o^d$. Likewise, it is $R(x|0){\geq}R_o$, $R_o>R(x|0)>R_o^{\frac{1}{g}$ and $R(x\mid0)<R_o^{\frac{1}{g}}$ for Weibull testing efforts. Ideal case is $R_o>R(x|0)>R_o^{\frac{1}{g}}$.

• Journal of Applied Reliability
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• v.14 no.1
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• pp.45-51
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• 2014

Thermal shock tests at two stress levels were performed to see the life (cycles) of LPF ASSY (low pass filter assembly) at normal stress level. In this case Coffin-Manson relationship is generally used to describe the relationship between the temperature difference and the life, together with the Weibull distribution describing the life at each stress level. So for given data Coffin-Manson is fitted to predict the life at normal stress level. However, different types of models are appropriate for this type of test. Hence, a more appropriate model such as General log-linear model which can also incorporate the duration at the highest and lowest temperatures and acceleration time will be introduced.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.10a
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• pp.265-270
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• 1997

Helical gear system is utilized to transmit motion between parallel shafts. The axial thrust loads on the shafts are existed. On each of the support shafts, at least one of the bearings should be able to support the axial loads. The reliability and life analysis are based on the two-parameter Weibull distribution lives of the component gears and bearings. The computer calculates the system lives and dynamic capacities of the components and their system. The system life is defined as the life of the component or the helical gear system at an output torque at which the probability of survival is ninety percent.

• Journal of Power System Engineering
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• v.21 no.3
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• pp.37-44
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• 2017

In this study, failure analysis of the angular pin for molding machines to aluminum component molding was carried out. SM45C steel was used for the angular pin, it was surface hardened by the induction surface hardening heat treatment. The cross section of damaged angular pin was observed, and micro Vickers hardness value from the fractured part was measured. Brittle fracture was occurred from the fracture surface of angular pin, therefore, impact toughness value was evaluated by V-notch Charpy impact test. It was confirmed that the impact absorption energy was high when was tempered at a high temperature for a long time, and the toughness was slightly increased. Also, 2-parameter Weibull statistical analysis was investigated in order to evaluate the reliability of the measured micro Vickers hardness values and absorbed energy. The micro Vickers hardness and absorbed energy well followed a two-parameter Weibull probability distribution, respectively. The reverse design against angular pin was proposed as possible by using test results.

• Journal of Applied Reliability
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• v.17 no.4
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• pp.316-324
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• 2017

Purpose: The purpose of this study is to determine the replacement cycle applied age replacement policy by reliability analysis based on railway vehicle contactor's failure history data. Method: We performed reliability analysis based on railway vehicle contactor's failure history data. We found a suitable distribution by goodness of fit test and predicted the reliability through estimation of scale & shape parameter. Considering cost information we determined the replacement cycle that minimize the opportunity cost. Result: Suitable distribution was the Weibull and scale parameter & shape parameter are estimated by reliability analysis. The replacement cycle was predicted and MTTF, $B_6$ percentile life were suggested additionally. Conclusion: We confirmed that failure rate type of railway vehicle contactor is degradation model having a time dependent characteristic and examined the replacement cycle in our country's operating environment. We expect that this study result contribute to railway operation agency for maintenance policy decision.

• New & Renewable Energy
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• v.20 no.2
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• pp.2-16
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• 2024

Various loads induced by marine environmental conditions, such as waves, currents, and wind, are crucial for the operation and viability of offshore wind power (OWP) systems. In particular, waves have a significant impact on the stress and fatigue load of offshore structures, and highly reliable design parameters should be derived through extreme value analysis (EVA) techniques. In this study, extreme wave analyses were conducted with various Weibull distribution models to determine the reliable design parameters of an OWP system suitable for the Ulsan area. Forty-three years of long-term hindcast data generated by a numerical wave model were adopted as the analyses data, and the least-squares method was used to estimate the parameters of the distribution function for EVA. The inverse first-order reliability method was employed as the EVA technique. The obtained results were compared among themselves under the assumption that the marginal probability distributions were 2p, 3p, and exponentiated Weibull distributions.

• Journal of Applied Reliability
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• v.10 no.4
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• pp.251-263
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• 2010

Modelling for failures is important for reliability analysis since failures of products such as automobiles occur as both time and usage progress and the results from the proper analysis of the two-dimensional data can be used for establishing warranty assurance policy. Hence, in this paper general issues which concern modelling failures are discussed, and both one-dimensional approaches and two-dimensional approaches to two-dimensional data are investigated. Finally non-parametric approaches to two-dimensional data are presented as a means of exploratory data analyses.