A knowledge management system for series-parallel availability optimization and design

System availability is an important subject in the design field of industrial system as the system structure becomes more complicated. While improving the system’s reliability, the cost is also on the upswing. The availability is increased by a redundancy system. Redundancy Allocation Problem (RAP) of a series-parallel system is traditionally resolved by experienced system designers. We proposed a genetic algorithm based optimization model to improve the design efficiency. The objective is to determine the most economical policy of components’ mean-time-between-failure (MTBF) and mean time-to-repair (MTTR). We also developed a knowledge-based interactive decision support system to assist the designers set up and to store component parameters during the intact design process of repairable series-parallel system.