Selective maintenance optimization for multi-state systems

In many military and industrial environments, systems are required to perform a sequence of missions with finite breaks between missions. During the breaks, it may be impossible to perform all desirable maintenance activities prior to the beginning of the next mission. What maintenance activities should be performed during the limited amount of time is a problem deserving studies. This kind of problem is called a selective maintenance problem. In this paper, we consider a parallel-series system with M subsystems connected in series wherein each subsystem consists of N/sub i/ identical components connected in parallel. Each component and the system may be in K+1 possible states, i.e., 0, 1, 2, a, K. When the system comes into the maintenance depot from the previous mission, the states of the components and the system can be determined. An optimization model is presented for minimization of total maintenance cost subject to system state probability requirements for the next mission. The shortest path method is used to solve the integer nonlinear programming problem.