Numerous methodologies have been developed for the plant-wide control (PWC) of industrial processes. These methodologies can be classified into heuristics, optimization, mathematical, and mixed approaches. However, most of these methodologies do not involve the extensive usage of rigorous process simulators as part of the control system development Also, in recent years, the focus has shifted toward the use of mixed approaches, which builds synergies between different techniques. As part of the continuing search for more effective PWC system design methods, an integrated methodology is proposed in this paper. This eight-level framework incorporates heuristics and optimization, together with the use of simulation throughout the procedure. The main intuitive feature of this framework is the identification of key controlled variables for optimal operation; this is achieved by detailed analysis of disturbances, computation of the new optimal set points by reoptimization, and cost breakdown analysis for throughput changes. Another important feature is the use of dynamic performance measures to aid in analyzing the effects of integration. This framework is then applied to the styrene monomer plant case study presented earlier [Vasudevan et al. Ind. Eng. Chem. Res. 2009, 48, 10941-10961] to develop a viable control structure. The performance of the resulting control system is compared with the control system developed using the integrated framework of Simulation and heuristics. While both the control structures are found to be stable and robust in the face of disturbances, the control structure developed in the present work performs significantly better, in terms of steady-state profit and the dynamic economic index based on deviation from the production target.