This paper deals with the modeling and multi-objective optimization of an industrial phosphoric acid process. The objective is to determine the operating conditions which minimize the chemical losses of phosphate and maximize the productivity of the digestion tank. To achieve these objectives, a process model, based on mass, charge, and energy balances along with thermodynamic equilibrium equations is developed. Experimental measurements concerning sulfur and phosphorus based systems are carried out and other measurements concerning fluorine, silicon and calcium sulfates based systems are collected from the literature. The results show that the predictions are in very good agreement with the measurements. The developed model is then used in a multi-objective optimization problem of an industrial manufacturing process to determine the set of optimal operating conditions. The optimization problem is solved by means of epsilon-constraint method and the optimal solutions are ranked using the multi-attribute utility theory. The best solutions are compared to industrial measurements based on surrogate modeling and are found to be consistent with the current operating conditions. Their implementation would significantly improve the current process performances.

本文涉及工业磷酸过程的建模和多目标优化。目标是确定使磷酸盐的化学损失最小化和消化罐生产率最大化的操作条件。为了实现这些目标，开发了基于质量、电荷和能量平衡以及热力学平衡方程的过程模型。对基于硫和磷的系统进行了实验测量，并从文献中收集了有关基于氟、硅和硫酸钙的系统的其他测量结果。结果表明，预测与测量非常吻合。然后将开发的模型用于工业制造过程的多目标优化问题，以确定一组最佳操作条件。采用epsilon-constraint方法求解优化问题，利用多属性效用理论对最优解进行排序。将最佳解决方案与基于代理建模的工业测量进行比较，发现与当前的操作条件一致。它们的实施将显着改善当前的过程性能。将最佳解决方案与基于代理建模的工业测量进行比较，发现与当前的操作条件一致。它们的实施将显着提高当前的工艺性能。将最佳解决方案与基于替代模型的工业测量进行比较，发现与当前的操作条件一致。它们的实施将显着提高当前的工艺性能。