Joint multi-objective optimization method for emergency maintenance and condition-based maintenance: Subsea control system as a case study

•A performance prediction model is established based on the competitive failure mechanism.•A hierarchical multi-objective particle swarm optimization model is established based on the priority of objectives.•A joint multi-objective optimization method for emergency maintenance and condition-based maintenance is established. In practical engineering, the engineering system is normally affected by random shocks to different degrees in addition to normal degradation. Random shocks cause dramatic changes for the system performance. In order to improve the resistant ability of the engineering system against random shocks and avoid the further deterioration of system performance, a joint multi-objective optimization method for emergency maintenance (EM) and condition-based maintenance (CBM) throughout the service life cycle is proposed. A cumulative degradation prediction model under the competitive failure mechanism is established through integrating normal degradation processes with random shock processes. The performance loss ratio and maintenance cost in the overall service life cycle are taken as multiple optimization objectives. Joint optimization for EM and CBM is realized according to the multi-objective particle swarm optimization algorithm and the priority of optimization objectives. The joint maintenance optimization for a subsea production control system is examined to validate the application of the proposed method. The maintenance cost is optimized under the premise of minimizing performance loss.