Reducing the impact of lot-to-lot raw material variability through optimization of operating conditions is key when the lots are already purchased, and available in inventory. The objective of this paper is to provide a framework to optimize operating conditions to maximize profitability while aiming at achieving product quality targets each time a new lot of raw material is fed to a continuous process. The proposed approach consists of solving an optimization problem in the latent space of a sequential multi-block partial least square model (SMB-PLS). Model updating and closed-loop operation are considered to overcome parametric disturbances. The approach is illustrated using a simulated grinding-flotation plant for a sequence of ore lots with variable properties. The case study shows that optimizing operating conditions with the proposed approach allows increasing biannual gain between 1.5 and 2% compared to nominal operation. This represents between 59 and 75% of the true achievable gain.

当批次已购买并有库存时，通过优化操作条件来减少批次间原材料差异的影响是关键。本文的目的是提供一个框架来优化操作条件，以最大限度地提高利润，同时旨在每次将新一批原材料送入连续流程时实现产品质量目标。所提出的方法包括解决顺序多块偏最小二乘模型 (SMB-PLS) 潜在空间中的优化问题。考虑模型更新和闭环操作来克服参数扰动。该方法通过模拟研磨浮选厂对一系列具有可变特性的矿石批次进行说明。案例研究表明，与标称运行相比，使用所提出的方法优化运行条件可以使每年两次的增益增加 1.5% 至 2%。这代表了真实可实现增益的 59% 到 75%。