• IE interfaces
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• v.19 no.1
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• pp.19-25
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• 2006

In the development process, the objective of a reliability growth program is to track the increase in system reliability, and determine as early as possible whether or not the system reliability is growing at a sufficient rate to meet the required goal and allocate available resources accordingly. Implementation of this kind of program will provide very useful information on concept selection, product/process reliability, and cost effectiveness without too much time, money and engineering effort being spent on the development of failure suspect parts. The purpose of this research is to present a practical method for efficiently monitoring a reliability growth test process using AMSAA(Army Materiel Systems Analysis Activity) reliability growth model. The presented growth management is a viable method for identifying failure modes, incorporating design changes and monitoring reliability progress on an on-going basis during the early stages of a product development program.

• Journal of Applied Reliability
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• v.14 no.4
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• pp.225-229
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• 2014

A one-shot device is defined as a product, system, weapon, or equipment that can be used only once. After use, the device is destroyed or must undergo extensive rebuild. Determining the reliability of a one-shot device poses a unique challenge to the manufacturers and users due to the destructive nature and costs of the testing. This paper presents a reliability growth prediction for a one-shot system. It is assumed that 1) test duration is discrete(i.e. trials or rounds); 2) trials are statistically independent; 3) the number of failures for a given system configuration is distributed according to a binomial distribution; and 4) the cumulative expected number of failures through any sequence of configurations is given by AMSAA model. When the system development is represented by three configurations and the number of trials and failures during configurations are given, the AMSAA model parameters and reliability at configuration 3 are estimated by using a reliability growth analysis software. Further, if the reliability growth predictions do not meet the target reliability, the sample size of an additional test is determined for achieving the target reliability.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.10
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• pp.747-752
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• 2019

By using the failure information and the cumulative test execution time obtained by performing the reliability growth test, it is possible to estimate the parameter of the reliability growth model, and the Mean Time Between Failure (MTBF) of the product can be predicted through the parameter estimation. However the failure information could be acquired periodically or the number of sample data of the obtained failure information could be small. Because there are various constraints such as the cost and time of test or the characteristics of the product. This may cause the error of the parameter estimation of the reliability growth model to increase. In this study, the Bayesian method is applied to estimating the parameters of the reliability growth model when the number of sample data for the fault information is small. Simulation results show that the estimation accuracy of Bayesian method is more accurate than that of Maximum Likelihood Estimation (MLE) respectively in estimation the parameters of the reliability growth model.

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.157-163
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• 2005

신뢰성성장시험관리는 제품개발프로그램의 초기단계에서 고장모드를 확인하고, 이를 개선 또는 제거하기 위해 설계를 변경하고, 그 결과 진행되는 신뢰성이 향상되는 변화를 추적할 수 있는 실용적인 방법이다. 본 연구의 목적은 AMSAA(Army Materiel Systems Analysis Activity)모델을 이용하여 신뢰성 성장을 계획하고 평가할 수 있는 실용적인 방법을 제시하는데 있다. 시험-개선 과정을 통하여 성장하는 신뢰성 수준의 변화에 대한 추적과 예측 가이드라인을 제시함으로써 현장에서 활용할 수 있는 방법을 보여준다.