In this work, a new methodology to conduct simultaneous design and control of large-scale systems is presented. The proposed method uses a structured singular value norm calculation (mu) to estimate the worst-case disturbance profile. This profile is then used to simulate the closed-loop nonlinear dynamic process model for obtaining the worst-case output variability and to test the process feasibility constraints. Thus, the proposed method referred to as the hybrid worst-case approach (HWA) methodology combines the analytical mu calculation of the worst-case disturbance and dynamic simulations using the mechanistic closed-loop process model to calculate variability. To test the proposed HWA method the integration of design and control of the reactor section of the Tennessee Eastman process was analyzed. This case study was also used to compare the proposed HWA method to other previously reported methodologies. Although the results obtained by the present HWA method for the case study are slightly conservative, the computational demand required by the present method is found to be I order of magnitude smaller than that required by a dynamic optimization-based methodology.