• Proceedings of the KSR Conference
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• 2005.11a
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• pp.258-263
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• 2005

The purpose of this research is to present a practical method for efficiently monitoring a reliability growth process using AMSAA(Army Materiel Systems Analysis Activity) reliability growth model. The presented method is viable 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. According to the Application Guide for EN 50126(RAM part for Rolling Stock), reliability growth monitoring is essential part of the main tasks of design phase in RAM growth monitoring. Implementation of reliability growth management 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.

• Journal of Applied Reliability
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• v.13 no.3
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• pp.175-190
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• 2013

This study considers reliability growth management as the excellent method for construction equipment development with the effect on decreasing COPQ(Cost of Poor Quality Cost) of new products. MIL-HDBK-189A(1981) and RADC-TR-84-20(1984) standards provide a general concept of reliability growth management including to reliability growth test, models and FRACAS(Failure Reporting and Corrective Action System). There is no study how to apply reliability growth management to construction equipment(or machine) development. This paper propose the method to apply it to construction equipment development process from the reliability target setting for developing products to launching them at market. It is expecially showing how to set target reliability for new developing equipment and the development risk to reach the reliability target in detail.

• Journal of Applied Reliability
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• v.18 no.1
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• pp.1-7
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• 2018

Purpose: Maintaining appropriate operational availability (Ao) is a key element of combat victory, but estimates vary according to estimation methods. The purpose of this study is to improve the accuracy of estimating operational availability by tracing the changes of the weapon system's failure rate, repair rate, and the level of logistic support. Methods: In order to track the change in the operating availability, the MDT (mean down time) is modeled by adding the repair time and the ALDT (administration and logistic delay time) to the service time. Results: Using the field data of the weapon system A operated by the ROKAF, the failure rate follows a non-homogeneous Poisson process that changes with time, and it is modeled considering the changing repair rate and the logistic support time. Conclusion: The accuracy of the analytical results was verified by comparing the actual operating data with the estimated availability. The results of this study can be used to track and evaluate the availability in a realistic situation where the failure rate and maintenance rate continuously change in operating environment.

• Journal of the military operations research society of Korea
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• v.28 no.2
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• pp.70-84
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• 2002

This paper deals with the attrition rate of major facility such as a particular building that is one of the most important target in the war time. In order to estimate the attrition rate, we use JAWS, WinJMEM which are programed by JTCG/ME of AMSAA and spreadsheet package which is able to assist the limitation of those programs and calculate all the procedure of this computation. This method uses the effectiveness index(El) which indicates the numerical measure of the effectiveness of a given weapon of a given target. The range error probable(REP) and the deflection error probable(DEP) in the ground plane also should be used. Those mean the measure of delivery accuracy of the weapon system. In this paper, it is improved that the El can be obtained from the regression analysis using the weight of the warhead explosive as the independent variable. It implies that we are able to obtain the El and the conditional probability of damage of the enemy weapon. After that, the single-sortie probability of damage can be computed using WinJMEM or another assistant program such as the spreadsheet package which shows the result immediately.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.2
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• pp.241-248
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• 2019

In this paper, we aim to check the reliability growth of multiple launch rocket components by the life evaluation. We apply the Crow-AMSAA model to the sets of test data obtained from the development phase. The result of the data analysis shows that the reliability of some components needs to be improved. In order to improve their reliability, we analyze the failure mechanism and change their designs. The verification of the reliability growth for those components is done by analyzing the data sets obtained by the accelerated life tests. As a result, we show that the MTBF of those components is increased and also their reliabilities improved.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.87-96
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• 2020

In this paper we proposed the test design method of reliability growth management. First, we presented the process for establishing the reliability growth management test design considering the number of failures and the termination test time. Reliability growth analysis of continuous system was performed in accordance with the test design process presented. In case the reliability test result is not met with the reliability target value after more than three failures occurred, the required test times were analyzed that 1,725 hrs for one corrective action, 1,950 hrs for two corrective actions. If the number of failures is less than three, design a reliability demonstration test according to confidence level 80% and 90% was performed using RGA 11 Software. As a result, it is possible to establish the reliability growth management test design with sufficient use of available resources. The results of this study can be used when establishing a test design for assessment of reliability growth management of all continuous systems.