Computational analysis of occupant safety has become an efficient tool to reduce the development time for a new product. Multi-body computer models (e.g. Madymo models) that simulate vehicle interior, restraint system and occupants in various crash modes have been widely used in the occupant safety area. To ensure public safety, many injury numbers, such as head injury criteria, chest acceleration, chest deflection, femur loads, neck load, and neck moment, are monitored. Deterministic optimization methods have been employed to meet various safety requirements. However, with the further emphasis on product quality and consistency of product performance, variations in modeling, simulation, and manufacturing, need to be considered. There are many difficulties involved in the optimization under uncertainty for occupant restraint systems, such as (1) highly nonlinear and noisy nature of occupant injury numbers; (2) large number of constraints; and (3) computational intensity to obtain the statistic information of injury numbers by the traditional Monte Carlo method. This paper proposes an integrated robust design method for occupant restraint system design, which takes advantages of design of experiments, variable screening, metamodeling, and genetic algorithm. An occupant restraint system design is used as an example to demonstrate the method; however, the proposed approach is generic and can be applied to other occupant restraint system design problems.