Online Fuzzy Assessment of Operating Performance and Cause Identification of Nonoptimal Grades for Industrial Processes

To pursue optimal comprehensive economic benefit, the process operating performance assessment on optimality becomes more and more critical for industrial processes. In this article, a novel method for online fuzzy assessment of the process operating performance and cause identification of nonoptimal performance grades is proposed. The contributions of this paper are summarized as follows: a new performance grade classification and identification method for modeling data is proposed; then, the assessment models for different performance grades are established through extracting the process variable correlation characteristics, which effectively avoids redundant information and provides the reference standards for online assessment; in addition, besides the deterministic assessment results, such as optimal, suboptimal, etc., the performance grade conversion is also evaluated; when the process operating performance is nonoptimal, the responsible variables are identified based on the variable contributions. Finally, the feasibility and efficiency of the proposed method is illustrated with a case of gold hydrometallurgical process.