This paper presents a new approach to integrate process design and control. Robust stability and performance measures based on Lyapunov theory and structured singular value analysis (SSV) are used to estimate bounds on process worst-case variability, process feasibility, and process stability. In this approach, the simultaneous design and control problem is posed as a nonlinear constrained optimization problem. The proposed methodology is illustrated using the design of a mixing tank process. The resulting design was compared to the design using a dynamic optimization approach. The expected computational burden required by this method for the design of large-scale processes is also estimated.