• Journal of Korean Society for Quality Management
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• v.31 no.1
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• pp.11-20
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• 2003

In the development of a complex systems, the early prototypes generally have reliability problems, and, consequently these systems are subjected to a reliability growth program to find problems and take corrective action. A variety of models have been proposed to account for the reliability growth phenomena. Clear guidelines need to be established to assist the reliability engineers for model selection. In this paper, some of more well-known growth models are surveyed and classified. These models are classified based upon distinguishing model features. A procedure for model selection is introduced which is based on this classification.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.49-57
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• 2018

The main objective of this paper is come up with methodology approach for FPGA-based system in verification and validation lifecycle regarding software reliability using system engineering approach. The steps of both reverse engineering and re-engineering are carried out to implement an FPGA-based of safety critical system in Nuclear Power Plant. The reverse engineering methodology is applied to elicit the requirements of the system as well as gain understanding of the current life cycle and V&V activities of FPGA based-system. The re-engineering method is carried out to get a new methodology approach of software reliability, particularly Software Reliability Growth Model. For measure the software reliability of a given FPGA-based system, the following steps are executed as; requirements definition and measurement, evaluation of candidate reliability model, and the validation of the selected system. As conclusion, a new methodology approach for software reliability measurement using software reliability growth model is developed.

• International Journal of Reliability and Applications
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• v.4 no.3
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• pp.131-139
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• 2003

There is a new trend of incorporating software coverage metrics into software modelling. This paper proposes and empirically evaluates a software reliability growth model, which relates reliability to coverage. The proposed model is derived by modifying the assumptions on which Veevers and Marshall model is based.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.2
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• pp.157-173
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• 1993

Reliability growth modeling can be a requirement when bidding on large military hardware systems. Under current reliability warranty legislature, the reliability growth model can be later translated into necessary reliability performance which must be demonstrated over an extended period of usage. In this paper the modeling situation is concerned with determining the number of spares needed to support a projected reliability growth both at the fightine and in a depot inventory. The model differs from existing models for logistics planning in that we allow for the phenomena of reliability growth. The model can also be used to determine central depot staffing requirements based upon a specified system utilization.

• Journal of Korean Society for Quality Management
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• v.44 no.3
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• pp.565-574
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• 2016

Purpose: In this study, A reliability assurance model (or reliability program) is proposed to evaluate the reliability of an armed vehicle. The reliability assurance is performed through the reliability-centered activities in the K-000(armed vehicle) of D-Company Methods: By reflecting the current situations of korea defense industry, a reliability assurance model is built up based on the benchmarking results of world leading companies' best practices in same fields. So The reliability growth model is applied the Crow-AMSAA model Results: This research analysis the K-000(armed vehicle) of D-Company using the DT and OT failure data. and application case study by growth model of armed vehicles Conclusion: This research is result of application case study by growth model of armed vehicles.

• Journal of Korean Society for Quality Management
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• v.34 no.3
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• pp.73-78
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• 2006

In this paper, we propose a software reliability growth model based on the testing domain in the software system, which is isolated by the executed test cases in software testing. In particular, our model assumes an imperfect debugging environment in which new faults are introduced in the fault-correction process, and is formulated as a nonhomogeneous Poisson process(NHPP). Further, it is applied to fault-detection data, the results of software reliability assessment are shown, and comparison of goodness-of-fit with the existing software reliability growth model is performed.

• Journal of Applied Reliability
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• v.14 no.2
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• pp.129-136
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• 2014

Reliability test is focusing to detect the unexpected reliability failure and solve them for the high quality of products. The test data should be used to assess and project the current level of interesting product reliability and so it is very important to have the accurately assessing methodology with test data. There are two type of trend for test data as constant and changing one during testing and this paper shows the difference in the assessing results of these two cases. There is less information how to define the existence of reliability growth rate changing and calculate the parameters of the reliability growth models to make an accurate assessment with such condition, so i established the process and mathematical model to calculate the parameters at such condition to make reliability growth curve with high Goodness of Fit. I validated the new method with the data made from Monte Carlo Simulation and case from Demko (1993). Even the assessed result with the new methodology may be different with the case by case because of very diversity in test condition and testing product quality, but the process and method founded in this research can be applied to any case using Duane and AMSAA model for their test data assessment. I also present the evaluation method to see the effectiveness with new one which is a conventional knowledge and not popular to use, so it is possible to compare the results with the newly presented and conventional method for better business decision.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.329-335
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• 2019

Reliability growth analysis was conducted for a guided weapons system. In the development phase, reliability management activities were continuously carried out by identifying failure modes and causes and analyzing faults found during the testing. The missile system consists of an all-up-round missile and a launcher, and the analysis was carried out according to the test results of each system. The test results for the all-up-round missile were obtained with discrete data, which were success and failure as a one-shot-device. The test results for the launcher were obtained with continuous data by operating the equipment continuously in the test. For each test result, the reliability growth model was applied to the Standard Gompertz model and the Crow-Extended model. The models were used to identify the growth analysis results of the test so far. It was also possible to predict the reliability growth results by assuming the future test results. The study results could be useful in achieving the desired reliability goal and in determining the number of tests. Then, the planned test will be confirmed and the growth analysis of the missile system will continuously be conducted.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.761-769
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• 2002

Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed. The testing time on the right is truncated in this model. The instantaneous failure rate, mean-value function, error detection rate, reliability of the software, estimation of parameters and the simple applications of this model are discussed .

• The KIPS Transactions:PartD
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• v.10D no.5
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• pp.829-836
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• 2003

Software Reliability Growth Model that have been studied variously. But measurement of correct parameter of this model is not easy. Specially, estimation of correct model about failure data must be establish and estimation of parameter can consist exactly. To get correct testing, we calculate the normal score and describe the normal probability plot. Use the normal probability plot, we estimate the distribution for failure data. In this paper, we estimate the software reliability growth model for through the normal probability plot. In this research, we applies software reliability growth model through distribution characteristics of failure data. If we see plot, we determine the software reliability growth model, we can make sure superior in model's performance estimation.