This work focuses in the design and control of a plant used in the clarification stage of the sugar cane juice refining process. An innovative approach to the simultaneous design and control problem is presented, which considers the state controllability (based on practical controllability metrics) and the output controllability (based on dynamical performance indices) using as example the sulphitation tower. This statement translates into a non linear optimization problem where constraints are imposed over the plant operating conditions, the state controllability metrics and some closed loop performance indices while the investment, operating and control costs are minimized. The optimization problem was solved successfully using genetic algorithms.