Online process operating performance assessment and nonoptimal cause identification for industrial processes

Although industrial processes are usually operated at the optimal point in the early stage of the production, the operating performance may deteriorate with time due to process disturbances. In order to pursue optimal comprehensive economic benefit (CEB), online process operating performance assessment on optimality has become a key issue. However, a little work has been published in this research area. In this paper, a new online operating performance assessment and nonoptimal cause identification method for industrial process are proposed. The contributions of this paper can be summarized as follows: a novel performance-similarity-based online operating performance assessment method is proposed; total projection to latent structures (T-PLS) is applied to the area of process performance assessment for the first time; the online assessment results include not only the deterministic performance grades, but also the performance grade conversions which were not covered in the existing assessment method; when the assessment result is nonoptimal, a novel automatic nonoptimal cause identification strategy is developed based on variable contributions, which is meaningful for guiding the further production adjustment. Finally, the feasibility and efficiency of the proposed method are illustrated with a case of gold hydrometallurgical process.