• Journal of the Korean Society of Systems Engineering
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• v.18 no.1
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• pp.46-57
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• 2022

In this paper, we proposed the DFMEA Implementation Method for safety design of Weapon System. First, we presented the process for DFMEA. And then, the case analysis of OOO missile was performed in accordance with the process presented. After defining the system requirements of OOO missile, failure definition scoring criteria was set. In order to clarify the definition of failure, the failure was classified into safety, reliability, maintainability and others. After performing the function analysis, the relationship matrix analysis was performed to identify the failure mode according to the function without omission. After clarifying the failure classification, mode of failure, cause of failure and effect were analyzed to calculate the severity, occurrence and detection values. After the action priority was judged, the recommended action according to the failure classification was identified for the determined action priority. The results of this study can be used as a relevant basis for the design reflection and resource re-allocation of stakeholders.

• Journal of The Korean Institute of Defense Technology
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• v.5 no.1
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• pp.1-6
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• 2023

The number of test samples was calculated by setting the reliability growth management test period considering the weapon system development period. The optimal reliability growth management test design condition was 80% reliability, 60% confidence level, and 6 months of test period. At this time, it was analyzed that 4 test samples were required if 0 failure occurred, and 9 test samples were required if 1 failure occurred. Using the method of determining the number of samples presented in this paper, it can be used as a basis for acquiring a budget for the number of samples for reliability growth management when switching from the exploratory development stage to the system development stage.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.30-39
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• 2024

This study introduces a novel approach for identifying potential failure risks in missile manufacturing by leveraging Quality Inspection Management (QIM) data to address the challenges presented by a dataset comprising 666 variables and data imbalances. The utilization of the SMOTE for data augmentation and Lasso Regression for dimensionality reduction, followed by the application of a Random Forest model, results in a 99.40% accuracy rate in classifying missiles with a high likelihood of failure. Such measures enable the preemptive identification of missiles at a heightened risk of failure, thereby mitigating the risk of field failures and enhancing missile life. The integration of Lasso Regression and Random Forest is employed to pinpoint critical variables and test items that significantly impact failure, with a particular emphasis on variables related to performance and connection resistance. Moreover, the research highlights the potential for broadening the scope of data-driven decision-making within quality control systems, including the refinement of maintenance strategies and the adjustment of control limits for essential test items.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.9
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• pp.663-668
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• 2022

Since the early 2000s, the United States has applied TLCSM to reduce life cycle costs while maintaining the weapons system's combat readiness. With the application of TLCSM, the ILS concept centered on the acquisition stage shifted to IPS, a concept that manages life cycle costs throughout the entire life cycle. In addition, LSAR for developing ILS has switched to LPD for developing IPS. In this study, LSAR in Korea and LPD in the United States were compared and analyzed, and policies necessary for the introduction of LPD in Korea were proposed.