Uncertainty in the input parameters to an engineering system may not only degrade the system’s performance, but may also cause failure or infeasibility. This paper presents a new sensitivity analysis based approach called Design Improvement by Sensitivity Analysis (DISA). DISA analyzes the interval parameter uncertainty of a system and, using multi-objective optimization, determines an optimal combination of design improvements required to enhance performance and ensure feasibility. This is accomplished by providing a designer with options for both uncertainty reduction and, more importantly, slight design adjustments. The approach can provide improvements to a design of interest that will ensure a minimal amount of variation in the objective functions of the system while also ensuring the engineering feasibility of the system. A two stage sequential framework is used in order to effectively employ metamodeling techniques to approximate the analysis function of an engineering system and greatly increase the computational efficiency of the approach. This new approach has been applied to two engineering examples of varying difficulty to demonstrate its applicability and effectiveness.