• Journal of Korean Society for Quality Management
• /
• v.44 no.3
• /
• pp.565-574
• /
• 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
• /
• v.45 no.4
• /
• pp.981-994
• /
• 2017

Purpose: In this study, the reliability growth management procedures for armed vehicle is suggested and an illustrative case study of launcher system is given. Methods: Crow-AMSAA model is adopted to manage reliability growth of armed vehicle using failure data acquired from development test phase to field operation phase. Between the development test phase and the production phase, the suggested reliability growth procedures for armed vehicle entails accelerated life test of the selected module whose design is changed to improve its reliability for assuring the target system reliability. And it can be verified through estimating the system reliability based on the failure data of field operation phase. Results: It is shown that the proposed reliability growth management procedures are effective for armed vehicle based on the case study of launcher system. After estimating the reliability of launcher system at every development test, some items are selected to change their designs for improving reliability. Accelerated life test is performed to prove the reliability improvement and finally it is verified through the field operation. Conclusion: The reliability growth management procedures for armed vehicle is suggested and the case study of launcher system shows it can be effective for managing the reliability growth of the armed vehicle.

• Journal of Applied Reliability
• /
• v.15 no.2
• /
• pp.90-100
• /
• 2015

Reliability growth rate (or reliability growth curve slope) have the two cases of trend as a constant or changing one during the reliability growth testing. The changing case is very common situation. The reasons of reliability growth rate changing are that the failures to follow the NHPP (None-Homogeneous Poisson Process), and the solutions implemented during test to break out other problems or not to take out all of the root cause permanently. If the changing were big, the "Goodness of Fit (GOF)" of reliability growth curve to test data would be very low and then reduce the accuracy of assessing result with test data. In this research, we are using Duane model and AMSAA model for assessing test data and projecting the reliability level of complex and repairable system as like construction equipment and vehicle. In case of no changing in reliability growth rate, it is reasonable for reliability engineer to implement the original Duane model (1964) and Crow-AMSAA model (1975) for the assessment and projection activity. However, in case of reliability growth rate changing, it is necessary to find the method to increase the "GOF" of reliability growth curves to test data. To increase GOF of reliability growth curves, it is necessary to find the proper parameter calculation method of interesting reliability growth models that are applicable to the situation of reliability growth rate changing. Since the Duane and AMSAA models have a characteristic to get more strong influence from the initial test (or failure) data than the latest one, the both models have a limitation to contain the latest test data information that is more important and better to assess test data in view of accuracy, especially when the reliability growth rate changing. The main objective of this research is to find the parameter calculation method to reflect the latest test data in the case of reliability growth rate changing. According to my experience in vehicle and construction equipment developments over 18 years, over the 90% in the total development cases are with such changing during the developing test. The objective of this research was to develop the newly assessing method and the process for GOF level increasing in case of reliability growth rate changing that would contribute to achieve more accurate assessing and projecting result. We also developed the new evaluation method for GOF that are applicable to the both models as Duane and AMSAA, so it is possible to compare it between models and check the effectiveness of new parameter calculation methods in any interesting situation. These research results can reduce the decision error for development process and business control with the accurately assessing and projecting result.

• Journal of Applied Reliability
• /
• v.18 no.1
• /
• pp.1-7
• /
• 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 Korea Institute of Military Science and Technology
• /
• v.22 no.2
• /
• pp.241-248
• /
• 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
• /
• v.16 no.2
• /
• pp.87-96
• /
• 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.