This paper discusses the problem of integrating the process and control design steps for a chemical process. The cost function to be optimized includes capital cost, operating cost and a cost due to variability in the controlled variable. A distillation column was selected as a case study and a single input single output (SISO) controller was used. A First Order Plus Dead Time (FOPDT) model was assumed to represent the process where the dynamic parameters were estimated as functions of process design variables. A robust internal model control (IMC) controller was designed based on a nominal linear model assuming model error to account for process nonlinearity. The optimum column design and the closed loop time constant which resulted in the lowest objective function cost were determined. The proposed method was compared to the traditional one where the design and control steps are performed separately in a sequential fashion. The optimization results show that the integration of column design and control in one step leads to savings up to 42% compared to the traditional method. (C) 2004 Elsevier Ltd. All rights reserved.