Promoting Decision-Making in Industrial Flotation Process by Collaborating Multiple Flotation Cells

The occurrence of abnormal operating conditions in industrial flotation processes adversely influences flotation concentrate yields and quality. It is imperative to prioritize the maintenance of normal operating conditions within the flotation process for process optimization. Considering the influence of the operation variable adjustment of different flotation cells on the final production indicators and the difficulty of establishing an adequate mathematical model, an intelligent collaborative decision-making plan based on multiple flotation cells is proposed in this study. First, multimodal data from industrial flotation sites are collected to emulate the comprehensive perceptual capabilities exhibited by human operators. Then, based on the concept of collaborative optimization, an intelligent collaborative decision-making plan for adjusting operating parameters is proposed. Finally, a series of experiments are conducted using actual industrial data. The results demonstrate the efficacy of the proposed intelligent collaborative decision-making plan in enhancing abnormal operation conditions, thereby establishing its promising potential for practical implementation in the industrial flotation process.