Cost is the most important factor in engineering systems, thus cost reduction and producing components with a reasonable cost are mandatory for manufacturing engineers. Effective maintenance influences the total cost of manufacturing systems, and its efficiency depends on spare parts management. Therefore, maintenance and spare parts should be jointly managed and significant characters such as ordering, repair and replacement times, shortage, cost, quality, and storage condition of spare parts have to be considered. In this paper, intelligent manufacturing systems with the multi-component structure are considered, that three types of maintenance policies (condition-based maintenance, corrective maintenance, and preventive maintenance) simultaneously support these systems. A joint optimization method based on GA-PS and Monte Carlo simulation is proposed to achieve minimum cost and maximum availability. Also, the influence of spare parts degradation in storage to evaluate system performance is considered. A framework is proposed for this; it can successfully consider the manufacturing machines, maintenance policies and spare parts inventory to obtain the optimal system with the maximum availability and the minimum cost. Also, the results demonstrate that different factors impress the system, and these parameters must be jointly considered. The ordering and replacement times, storing conditions and suppliers' situation are the main factors considered to obtain an optimal system. Manuscript profile