Reliability and maintainability optimization using Discrete-Event Simulation and Genetic Algorithms

This research addresses reliability and maintainability optimization problem to maximize the system life cycle profit. In this research, the mathematical model was developed for calculating the system profit considering associated failure and maintenance cost. Discrete-Event Simulation (DES) was applied to evaluate the component availability and maintenance cost under different scenarios. Corrective maintenance, periodic preventive maintenance, and component degradation are considered in the simulation models. Genetic Algorithms (GA) is combined with DES to search for the optimal solution of reliability and maintainability design to maximize the overall profit. DES and GA are programmed in MATLAB. Design of Experiments is performed to analyze the impact of parameters on the optimization performance, and identify their appropriate levels. Case studies are used to evaluate the performance of the proposed approach. The experimental results indicate that optimal reliability and maintainability design found by the proposed approach can significantly increase the system life cycle profit.