• International Journal of Reliability and Applications
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• v.8 no.2
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• pp.153-173
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• 2007

Wood-plastic composites (WPC) are gaining market share in the building industry because of durability/maintenance advantages of WPC over traditional wood products and because of the removal of chromated copper arsenate (CCA) pressure-treated wood from the market. In order to ensure continued market share growth, WPC manufacturers need greater focus on reliability, quality, and cost. The reliability methods outlined in this paper can be used to improve the quality of WPC and lower manufacturing costs by reducing raw material inputs and minimizing WPC waste. Statistical methods are described for analyzing stiffness (tangent modulus of elasticity: MOE) and flexural strength (modulus of rupture: MOR) test results on sampled WPC panels. Descriptive statistics, graphs, and reliability plots from these test data are presented and interpreted. Sources of variability in the MOE and MOR of WPC are suggested. The methods outlined may directly benefit WPC manufacturers through a better understanding of strength and stiffness measures, which can lead to process improvements and, ultimately, a superior WPC product with improved reliability, thereby creating greater customer satisfaction.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.4
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• pp.334-340
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• 2015

Engine derating is often considered for reliability benefits because lower power operation reduces its failure probability. To be derated during operation, however, the engine must be initially overdesigned. The engine overdesign is cost effective only if reliability increased from derating is enough to offset the initial increase in the development cost caused from the overdesign. The purpose of this paper is to provide an analytical model to consider a trade-off between the engine overdesign and derating. We use a logistic regression model to explain reliability growth in the number of hot firing tests for a fixed power level. Using the Transcost model with the reliability growth model, we show that 10% overdesign of Titan rocket engine decreases its development cost by about 9% and 23% depending on the reliability requirement. We also point out that such a cost reduction depends on the fuel type a rocket uses.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.1-6
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• 1998

The evaluation of reliability is very important in the development process of software. There may be lack of trustfulness on the results that come from the analysis and evaluation of reliability of softwares which do not divide the test phases. At this point, this article studies how to evaluate the reliability dividing the test phases in order to settle the these problems. In doing so, I apply the fault data to be found in Unit Test, Integration Test, Validation Test and System Test to SRGM(Software Reliability Growth Model), Exponential SRGM, Delayed S-shaped SRGM and Inflection S-shaped SRGM. The result is that Inflection S-shaped is best suitable with Unit Test Delayed S-shaped is best suitable with Integration and Validation Test, and Exponential SRGM is best suitable with System test. In this respect, I can show that the results of this study on parameter estimation, difference square summation, number of fault remained is superior to the established methods.

• Convergence Security Journal
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• v.6 no.3
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• pp.117-126
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• 2006

Bayesian inference and model selection method for software reliability growth models are studied. Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. In this paper, could avoid multiple integration using Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference for general order statistics models in software reliability with diffuse prior information and model selection method are studied. For model determination and selection, explored goodness of fit (the error sum of squares), trend tests. The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution(shape 2 & scale 5) of Minitab (version 14) statistical package.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.672-675
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• 1995

Because of a sudden growth of the research of fatigue failure, recent machines or structures have been designed by damage tolerance design in many fields. Consequently, it is the most primary factor to clarity the specific character of fatique failure in the design of machines or structures considering reliability. A statistical analysis is required to analyze the outcome of an experiment or a life estimate by reason of that fatigue failure contains lots of random elements. Reliability analysis which has tukenn the place of the existing analyses in the consideration of the uncertainty of a material, is a very efficient way. Even reliability analysis, however, is not a perfect way to analyses the uncertainties of all the materials. This thesis would refer to a newly conceived data analysis that the coefficient of a system could cause the ambiguity of the relationship of an input and output.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.3
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• pp.268-274
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• 2007

In general, rocket or satellite circuit designers focus on reducing temperature of electronic devices in order to enhance electronic unit's reliability. This paper describes the quantitative analysis result of activation energy as well as device temperature effects to the system reliabilities. The quantitative analysis result shows that activation energy of device has more effects on system reliability than temperature does. And this paper suggests a strategy for enhancement of reliability during devices placement on PCB with simulation results.

• International Journal of Reliability and Applications
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• v.2 no.4
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• pp.269-280
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• 2001

The objective of this paper is to provide a model for effective implementation of costing RAM management in the design and procurement of production facility considering the system cost-performance trade-off. This research proposes a two-step approach of costing RAM design and test of system RAM for production facility. In Step 1, a static model is proposed to find an initial system configuration to meet the required performance based on system RAM and LCC and analyzes the trade-off relationships between various factors of RAM and LCC. In the second Step, we developed time and failure truncated models for system reliability test and analysis. For the computational purpose, we developed computer programs and have shown the sample results. By the sample test run, the proposed model has shown the possibilities to provide a good method to analyze system performance evaluation for both design and operational phase, This model can be applied to a wide variety of systems not only for costing RAM of the production facilities but also for the other kinds of equipment.

• Proceedings of the Safety Management and Science Conference
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• 2008.11a
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• pp.611-622
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• 2008

It is hot issue to get the competitiveness of product through reliability-growth as well as availability and safety in almost high-technology industry including military, chemistry, nuclear, telecommunication, transportation service and so on. In advanced countries, worldwide leading companies have tried to improve and develop high-reliability product as well as reliability management system(IEC60300). We investigate reliability certification systems for product and management system. Additionally, we study the feasibility on the adoption of dependability management system(IEC60300) by empirical survey on companies with product-reliability certification(R-mark) in Korea.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.19-27
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• 2014

Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the reliability model with log type mean value function (Musa-Okumoto and log power model), which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, was employed. Analysis of failure using real data set for the sake of proposing log type mean value function was employed. This analysis of failure data compared with log type mean value function. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the log type model is also efficient in terms of reliability because it (the coefficient of determination is 70% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can be able to help.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.79-89
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• 2022

To compute the mean and variance of component-based reliability software, we focused on path-based reliability analysis. System reliability depends on the transition probabilities of components within a system and reliability of the individual components as basic input parameters. The uncertainty in these parameters is estimated from the test data of the corresponding components and arises from the software architecture, failure behaviors, software growth models etc. Typically, researchers perform Monte Carlo simulations to study uncertainty. Thus, we considered a Markov chain Monte Carlo (MCMC) simulation to calculate uncertainty, as it generates random samples through sequential methods. The MCMC approach determines the input parameters from the probability distribution, and then calculates the average approximate expectations for a reliability estimation. The comparison of different techniques for uncertainty analysis helps in selecting the most suitable technique based on data requirements and reliability measures related to the number of components.