Nowadays, industrial systems are more and more larger with many components which are connected in a complex structure. The systems usually ask for a high investment cost (expensive components) and many preparation tasks for maintenance. With these system, a maintenance policy should take into account the complexity of system structures and give priority to saving the setup costs. Therefore, an intelligent grouping maintenance strategy for complex structure systems is developed in this paper. Under this strategy, a group of components is decided to Preventively Maintained (PM) at each τ (basic time interval) due to component Mean Remaining Lifetime (MRL) and component Birnbaum's measure of structural importance (I B) to save preventive setup costs. Moreover, the complex structures allow to economize corrective setup costs by grouping some CM actions with the PM actions at τ. The CM grouping is performed by leaving some failed units in idle state until the next PM period. This action can economize corrective setup costs, but it also leads a change of the system structure during the system operation. Therefore, in this paper, a simulation method using Monte Carlo Simulation is developed to analyze the changes of system structure during the system operation and calculate the average maintenance cost. A numerical example of a 6 components system is finally introduced to illustrate the use and the advantages of the proposed strategy when compared to existing methods.