TY - JOUR
T1 - Reliability Evaluation and Optimization for Phased Mission Systems with Cascading Effects
AU - Ma, Chenyang
AU - Zhang, Shuai
AU - Zhou, Mi
AU - Si, Shubin
AU - Cai, Zhiqiang
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2021/2/2
Y1 - 2021/2/2
N2 - The phased mission system (PMS) has been widely used in aerospace, data transmission, internet of things, which perform the entire mission with non-overlapping, consecutive and multiple phases of operation. The challenge for the PMS reliability evaluation is to consider both the dynamic of each component across phases and the functional dependence (FDEP) among components. In some cases, the component can fail individually or resulting from the cascading effect (CE) caused by internal FDEP among components. So, this paper presents the reliability evaluation method for PMSs with the CE based on recursive algorithm. Then, to find the best components' allocation scheme with the maximized system reliability and the minimized manufacturing cost, the non-dominated sorting genetic algorithm (NSGA-II) is employed to solve the combinatorial optimization problem. Finally, the numerical example illustrates the effectiveness of proposed method and obtains solutions of the optimization model.
AB - The phased mission system (PMS) has been widely used in aerospace, data transmission, internet of things, which perform the entire mission with non-overlapping, consecutive and multiple phases of operation. The challenge for the PMS reliability evaluation is to consider both the dynamic of each component across phases and the functional dependence (FDEP) among components. In some cases, the component can fail individually or resulting from the cascading effect (CE) caused by internal FDEP among components. So, this paper presents the reliability evaluation method for PMSs with the CE based on recursive algorithm. Then, to find the best components' allocation scheme with the maximized system reliability and the minimized manufacturing cost, the non-dominated sorting genetic algorithm (NSGA-II) is employed to solve the combinatorial optimization problem. Finally, the numerical example illustrates the effectiveness of proposed method and obtains solutions of the optimization model.
UR - http://www.scopus.com/inward/record.url?scp=85101601657&partnerID=8YFLogxK
U2 - 10.1088/1757-899X/1043/2/022045
DO - 10.1088/1757-899X/1043/2/022045
M3 - 会议文章
AN - SCOPUS:85101601657
SN - 1757-8981
VL - 1043
JO - IOP Conference Series: Materials Science and Engineering
JF - IOP Conference Series: Materials Science and Engineering
IS - 2
M1 - 022045
T2 - 10th International Conference on Quality, Reliability, Risk, Maintenance,and Safety Engineering, QR2MSE 2020
Y2 - 8 October 2020 through 11 October 2020
ER -