Availability Optimization Decision Support Design System for Different Repairable n-Stage Mixed Systems

This study attempts to propose an availability optimization decision support design system for repairable n-stage mixed systems, in which different combinations of subsystems, such as parallel, standby, and k-out-of-q, are connected series configuration. The enumeration method, tabu search, simulated annealing, non-equilibrium the modified redundancy allocation heuristic combined with a genetic algorithm will be proposed solve problem further determine appropriate configuration design. Several cases conducted by following procedural flow reach optimal allocations component amount, repair rates, failure rates all subsystems minimize total cost under several constraints systems. Simulated results display that can definitely take advantage designs, including parallel-series system, standby k-out-of-q save lot meet high level requirement compared single system. Additionally, methods also show obviously same less cost, contrast presuming identical deteriorating probability both operating components components. performance comparisons five four configurations analyzed comprehensively. It concluded performances on criteria costs configurations, not only superior other methods, but CPU running time configurations.