Modeling and simulation for product design process

Descriptive simulation finds the performance measure of a system, given a particular value for the input parameters. Inverse simulation reverses this and attempts to find the controllable input parameters required to achieve a particular performance measure. This paper proposes using a 'stochastic approximation' to estimate the necessary design parameters within a range of desired accuracy. The proposed solution algorithm is based on Newton's methods using a single-run simulation to minimize a loss function that measures the deviation from a target value. The properties of the solution algorithm and the validity of the estimates are examined by applying them to a reliability system with a known analytical solution.