Automated Optimization of Concentrator Plant Process Configuration and Feed Ore Blends

Knowing in advance a concentrator plant feed ore types can enable to adjust and optimize the feed ore blend according to the available fresh ores and stockpiles. In additions to that, operational configuration and key setpoints of a plant may be adjusted according to the known incoming feed ore requirements. For this, plant metallurgical digital twin simulation model aids in predicting performance of a concentrator for any given feed blend and plant operating modes. This paper presents an automated method for simultaneously adjusting an ore blend and plant configuration to maximize operating profit. The optimizer utilizes a concentrator plant first-principle digital twin model, based on known ore characteristics and equipment operation. The proposed optimizer can be used in day-to-day process operation to automatically suggest optimized results for both metallurgical and economical KPIs. A case simulation study of a copper concentrator with five ore types, several settings for processing circuit and equipment is presented. Here, for a fixed feed blend the plant configuration optimization resulted additional 1.7 % increment in operating profit, while simultaneously optimizing both feed blend and plant configuration showed even more remarkable potential for economic benefits.