Optimization of preventive maintenance period based on AFSA

A reasonable and precise preventive maintenance period can effectively reduce the repair frequency and the cost of equipment maintenance. The serious breakdown and slow convergence often appear when using ASO (Ant Colony Optimization) and PSO (Particle Swarm Optimization) in optimization problem. Regarding these problem, a preventive maintenance period optimization model was established concerning with the concept of age reduction factor and optimized by AFSA (Artificial Fish School Algorithm). Based on the optimization and solution using AFSA, this paper focus on the change of a system´s total benefit which is along with the changing rate of preventive maintenance times, and finally the results can effectively help a decision-maker to determine when the system should be replaced.