Process operating performance optimality assessment and non-optimal cause identification under uncertainties

Abstract

In his research, a modified Dynamic Causal Diagram (DCD) based process operating performance optimality assessment and non-optimal cause identification method is proposed to handle the online assessment of the complicated chemical processes, where certainties and uncertainties coexist. In addition, the multi-source information usage problem of the traditional DCD is addressed. In the online application, a newly developed scheme is developed, which distinguishes stable performance grade and grades switch transition. For the non-optimal performances, a contribution based root cause identification method is developed, on the framework of the constructed DCD. Finally, the operating performance of a gold hydrometallurgy process is assessed by both the traditional DCD and the modified DCD. The superiority on accuracy and robustness of the modified DCD is demonstrated, and the responsible events for non-optimality is successfully isolated by the proposed contribution based non-optimal cause identification technique.