Intelligent method with case-based reasoning for setpoints optimization and its application

Considering the difficulty in achieving optimization of the key technical indexes because of the general complexity in process industries, an intelligent setpoints optimization method for the key technical index with improved case-based reasoning is presented. The improved case retrieval adopts a k-NN(k-Nearst Neighbour) strategy based on multi-similarity algorithms, while the case reuse is executed under static and dynamic similarity thresholds. The strategies of case evaluation and revision are also described along with those of case retention and maintenance. The structure of the intelligent optimization setting model is established and the method for realizing optimization setting is discussed. According to the variations of boundary conditions and operating conditions, optimization of the key technical index is fulfilled through online adjusting the loop setpoints related to critical technical parameters. Thereby it is assured that the actual value of the key technical index is within the tolerance ranges around its target value. The proposed method has been adopted successfully applied in the ore grinding process of a large-scale minerals processing factory in China. The production process has been stabilized and the ore grinding efficiency enhanced. The proposed method has shown prominence benefit and has extensive value to similar industrial applications.