A note on variance reduction methods in monte carlo applications to systems engineering and reliability

Monte Carlo analysis of the time behavior of complex modern systems is rapidly becoming a commonplace tool in the design and life cycle control. This is due to the inherent complexity of such systems both in terms of their multiple dimensions and interactive stochastic behavior. Predictions of system characteristics such as reliability, availability, spare parts requirements, maintenance scheduling etc. are essential at the earliest stages of design in order to achieve optimal system performance at the lowest possible cost. The applications of Monte Carlo methods to this field are the only effective approach. Within this area the estimation of rare events (with significant consequences) is a most difficult problem. Variance Reduction Methods (VRM) are, therefore, important.