Failure of practical engineering systems could be induced by several correlated failure modes, and consequently reliability analysis are conducted with multiple distributed failure regions in the system random input space. Problems with distributed failure regions create a great challenge for existing reliability analysis approaches due to the discontinuity of the system performance function between these regions. This paper presents a new enhanced Monte Carlo simulation (EMCS) approach for reliability analysis and design considering distributed failure regions. The ordinary Kriging method is adopted to construct surrogate model for the performance function so that Monte Carlo simulation (MCS) can be used to estimate the reliability. A maximum failure potential based sampling scheme is developed to iteratively search failure samples and update the Kriging model. Two case studies are used to demonstrate the efficacy of the proposed methodology.