@article{ART002958121},
author={Seungwon Baik and KIM WUKKI and Lee, Namrye and Yi, Haeyen and Jeong, Yongjun and Ahn, Nam-su},
title={Monte Carlo simulation-based defect ratio estimation approach for a chemical materials stockpile reliability program},
journal={Journal of Advances in Military Studies},
issn={2635-5531},
year={2023},
volume={6},
number={1},
pages={1-17},
doi={10.37944/jams.v6i1.179}
TY - JOUR
AU - Seungwon Baik
AU - KIM WUKKI
AU - Lee, Namrye
AU - Yi, Haeyen
AU - Jeong, Yongjun
AU - Ahn, Nam-su
TI - Monte Carlo simulation-based defect ratio estimation approach for a chemical materials stockpile reliability program
JO - Journal of Advances in Military Studies
PY - 2023
VL - 6
IS - 1
PB - Institute of Defense Acquisition Program
SP - 1
EP - 17
SN - 2635-5531
AB - A chemical material stockpile reliability program (CSRP) that determines the usability, safety, reliability, and performance of chemical equipment and materials is developed to determine the storage or disposal of chemical material stockpile (Storage Chemical Equipment and Material Reliability Evaluation Instruction, 2019). However, current inspection for current CSRP depend on test and evaluation of criteria for level of importance, and so the number of samples and acceptance quality limit (AQL) are presented based on the lot size. All the processes are conducted under KS Q ISO 2859-1, and the defect rate of the entire lot of CSRP items is generally assumed to be a distribution that is similar to a binomial distribution. However, the pass-fail test for CSRP items is based on approximately 10 test items, and the factors that cause defects in these items are also heterogeneous. We propose a new methodology for estimating the defect rates of CSRP items based on Monte Carlo simulations, which are widely used in various academic fields. In addition, we show the future applicability of the methodology by applying it to the K1 gas mask case and revealing the results of the defect rate estimation. We also present future work, including the need for a standard sample of CSRP items.
KW - chemical materials stockpile reliability program;KS Q ISO 2859-1;Monte Carlo simulation;Weibull distribution;binomial distribution
DO - 10.37944/jams.v6i1.179
ER -
Seungwon Baik, KIM WUKKI, Lee, Namrye, Yi, Haeyen, Jeong, Yongjun and Ahn, Nam-su. (2023). Monte Carlo simulation-based defect ratio estimation approach for a chemical materials stockpile reliability program. Journal of Advances in Military Studies, 6(1), 1-17.
Seungwon Baik, KIM WUKKI, Lee, Namrye, Yi, Haeyen, Jeong, Yongjun and Ahn, Nam-su. 2023, "Monte Carlo simulation-based defect ratio estimation approach for a chemical materials stockpile reliability program", Journal of Advances in Military Studies, vol.6, no.1 pp.1-17. Available from: doi:10.37944/jams.v6i1.179
Seungwon Baik, KIM WUKKI, Lee, Namrye, Yi, Haeyen, Jeong, Yongjun, Ahn, Nam-su "Monte Carlo simulation-based defect ratio estimation approach for a chemical materials stockpile reliability program" Journal of Advances in Military Studies 6.1 pp.1-17 (2023) : 1.
Seungwon Baik, KIM WUKKI, Lee, Namrye, Yi, Haeyen, Jeong, Yongjun, Ahn, Nam-su. Monte Carlo simulation-based defect ratio estimation approach for a chemical materials stockpile reliability program. 2023; 6(1), 1-17. Available from: doi:10.37944/jams.v6i1.179
Seungwon Baik, KIM WUKKI, Lee, Namrye, Yi, Haeyen, Jeong, Yongjun and Ahn, Nam-su. "Monte Carlo simulation-based defect ratio estimation approach for a chemical materials stockpile reliability program" Journal of Advances in Military Studies 6, no.1 (2023) : 1-17.doi: 10.37944/jams.v6i1.179
Seungwon Baik; KIM WUKKI; Lee, Namrye; Yi, Haeyen; Jeong, Yongjun; Ahn, Nam-su. Monte Carlo simulation-based defect ratio estimation approach for a chemical materials stockpile reliability program. Journal of Advances in Military Studies, 6(1), 1-17. doi: 10.37944/jams.v6i1.179
Seungwon Baik; KIM WUKKI; Lee, Namrye; Yi, Haeyen; Jeong, Yongjun; Ahn, Nam-su. Monte Carlo simulation-based defect ratio estimation approach for a chemical materials stockpile reliability program. Journal of Advances in Military Studies. 2023; 6(1) 1-17. doi: 10.37944/jams.v6i1.179
Seungwon Baik, KIM WUKKI, Lee, Namrye, Yi, Haeyen, Jeong, Yongjun, Ahn, Nam-su. Monte Carlo simulation-based defect ratio estimation approach for a chemical materials stockpile reliability program. 2023; 6(1), 1-17. Available from: doi:10.37944/jams.v6i1.179
Seungwon Baik, KIM WUKKI, Lee, Namrye, Yi, Haeyen, Jeong, Yongjun and Ahn, Nam-su. "Monte Carlo simulation-based defect ratio estimation approach for a chemical materials stockpile reliability program" Journal of Advances in Military Studies 6, no.1 (2023) : 1-17.doi: 10.37944/jams.v6i1.179
