TY - GEN
T1 - A method for maintenance decision based on condition monitoring
AU - Zhinong, Jiang
AU - Yuehua, Lai
AU - Jinjie, Zhang
AU - Xiaojian, Yi
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/27
Y1 - 2018/8/27
N2 - Condition based maintenance (CBM) is a kind of realtime efficient maintenance decision, which is desired to solve the question about "lack of maintenance" and "excess of maintenance". Through CBM, the maintenance cost can be reduced and the risk of catastrophic failure can be minimized to make the equipment running with maximum effectiveness. Based on the data of condition monitoring, combined with the factors such as maintenance times, degradation of equipment, human factors, working conditions and environment, a Weibull Proportional Hazards Model (WPHM) was established. With the goal of average maintenance cost and the constraint of availability, the genetic algorithm is adopted to optimize the threshold to guide the maintenance decision. Finally, maintenance advice is provided under certain confidence level. Combined with the monitoring data of diesel engine, the WPHM was established after estimation of parameters. And the corresponding maintenance decision is analyzed by the proposed method. The proposed method is of great significance for other repairable systems about CBM.
AB - Condition based maintenance (CBM) is a kind of realtime efficient maintenance decision, which is desired to solve the question about "lack of maintenance" and "excess of maintenance". Through CBM, the maintenance cost can be reduced and the risk of catastrophic failure can be minimized to make the equipment running with maximum effectiveness. Based on the data of condition monitoring, combined with the factors such as maintenance times, degradation of equipment, human factors, working conditions and environment, a Weibull Proportional Hazards Model (WPHM) was established. With the goal of average maintenance cost and the constraint of availability, the genetic algorithm is adopted to optimize the threshold to guide the maintenance decision. Finally, maintenance advice is provided under certain confidence level. Combined with the monitoring data of diesel engine, the WPHM was established after estimation of parameters. And the corresponding maintenance decision is analyzed by the proposed method. The proposed method is of great significance for other repairable systems about CBM.
KW - WPHM
KW - condition monitoring
KW - genetic algorithm
KW - maintenance decision
KW - maximum likelihood estimation
UR - https://www.scopus.com/pages/publications/85062822267
U2 - 10.1109/ICPHM.2018.8448396
DO - 10.1109/ICPHM.2018.8448396
M3 - Conference contribution
AN - SCOPUS:85062822267
T3 - 2018 IEEE International Conference on Prognostics and Health Management, ICPHM 2018
BT - 2018 IEEE International Conference on Prognostics and Health Management, ICPHM 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Prognostics and Health Management, ICPHM 2018
Y2 - 11 June 2018 through 13 June 2018
ER -