The article discusses a new method called Local Latin hypercube refinement (LoLHR) for improving the efficiency of designing reliable and robust systems. This method helps reduce the number of samples needed for accurate results in complex systems. By using LoLHR with surrogate models like Gaussian process and support vector regression, better outcomes were achieved compared to other strategies. This approach can be applied to various types of systems to enhance design optimization.