Operating performance assessment for industrial process with hybrid qualitative and quantitative information using modified fuzzy probabilistic rough set
Xiaoyu Zou, Fuli Wang, Yuqing Chang, Jie Pan · 2020
Since satisfactory operating performance helps guarantee high comprehensive economic benefit under normal working condition for industrial processes, it is crucial to conduct accurate performance assessment on the degree of optimality for modern industry. Process online assessment judges how well the process is working. However, the coexistence of the qualitative and quantitative information renders the conventional performance assessment approaches inappropriate. To solve the above problem, a modified version of fuzzy probabilistic rough set (FPRS) is proposed for performance assessment in this research. The modified FPRS is employed to establish a valid online assessment strategy of operating performance for complicated industrial processes with the coexistence of both the qualitative and quantitative information. The proposed technique is finally validated by a gold hydrometallurgy process.