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A systematic approach to the optimisation of rice processing operations.

机译:一种优化稻米加工操作的系统方法。

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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.)
机译:大米通常收获时水分含量很高,需要干燥才能长期保存。使用系统的优化方法来确定干燥过程的最佳设计和操作条件。该过程被公式化为MINLP(混合整数非线性规划)问题,该问题由二进制和连续变量的向量组成。我们的工作重点是确定最佳的干燥,冷却,回火顺序。由于除湿是至关重要的方面,因此将其分为三个主要单元:干燥,冷却和回火单元,每个单元都由一个模型表示。分别模拟干燥,冷却,储存和研磨过程中的糙米或优质单产。还介绍了能源消耗和经济模型。在广泛的操作条件下分析了每种模型的预测性能。提出了一个简化的上部结构流程图,其中包括可能的6,561种替代结构。发现最佳位置对模型参数不确定性不敏感。因此,这些简化的模型足以合成最佳流程图。最佳MINLP结果为每个目标功能提供了最佳的流程图结构和操作条件,包括:缩短生产时间,最小化操作单元数量,最大化糙米产量,最小化能源消耗,最小化运营成本和利润最大化。发现目标函数的选择对最优解有很大影响。生产时间,操作单元数很容易确定最佳解决方案,而稻米的产量,操作成本和利润则更为复杂。目标函数的选择非常重要,应明确定义。问题的解决方案还取决于初始起始值,因为找到了许多局部最优解。但是,发现MINLP方法是开发综合稻米加工流程图的有效工具。我们的结果表明,能源节省1%可使利润每年增加1.35亿美元,而稻米产量增加1%可使利润每年增加7.22亿美元。我们能够证明,将能源消耗降低22%以及将稻米产量提高2.4%是可能的。如果将这些节省应用于全球大米行业,则可以使全世界的利润增加74.4%,即每年34.4亿美元。 (摘要由UMI缩短。)

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