| Rice is generally harvested at high moisture level and it needs to be dried for long term storage.; A systematic optimisation approach was used to determine the optimal design and operating conditions of the drying process. The process was formulated as an MINLP (Mixed-Integer Non-linear Programming) problem consisting of a vector of binary and continuous variables. Our work focused on determining the optimal drying-cooling-tempering sequence.; Since moisture removal is a critical aspect it was partitioned into three major units: drying, cooling, and tempering units, each of which is represented by a model. Head rice or quality yields during drying, cooling, storing and milling were modelled separately. Energy consumption and economic models are also presented. The predicted performance of each model was analyzed over a wide range of operating conditions.; A simplified superstructure flowsheet comprising a possible 6,561 alternative structures was postulated. It was found that the location of the optimum was not sensitive to model parameter uncertainty. Therefore, these simplified models are adequate for synthesis of optimal flowsheet.; The optimal MINLP results provide the optimum flowsheet structure and operating conditions of each objective function including: minimise of production time, minimise number of the operating units, maximise head rice yield, minimise energy consumption, minimise operating cost and maximise the profit. It was found that the choice of objective function has a significant effect on the optimal solution. The production time, number of the operating units are simple to determine for the optimum solutions while head rice yield, the operating cost, and the profit are more complex. The selection of objective function is of great importance and should be clearly defined. The solution of the problem also depends on the initial starting values since many local optima were found. However the MINLP approach was found to be an efficient tool for developing an integrated rice process flowsheet.; Our results show that a 1% savings in energy results in a {dollar}135 million dollars per year increase in profit, whereas a 1% increase in head rice yield results in {dollar}722 million dollars per year increase in profit. We were able to demonstrate that a 22% reduction in energy consumption was possible along with a 2.4% increase in head rice yield. These savings, if applied to the world-wide rice industry, translate into a 74.4% increase in profit or {dollar}3.44 billion dollars/year world-wide. (Abstract shortened by UMI.)... |
