Smart data analysis for optimized manufacturing of powder coatings on corotating twin screw extruders

This paper addresses smart data mining techniques for analyzing the processing of selected powder coatings on co-rotating twin screw extruders. The influences of different machinery and process parameters on optical quality criteria such as degree of gloss and color are analyzed. Experiments were performed on laboratory and production scale corotating twin screw extruders using different screw configurations. Decision trees are developed in order to analyze the process and to determine the essential influencing factors on the formation of the degree of gloss. For further analysis of the process and to enable optimal up-scale from laboratory to production scale analytic equations are evolved by using symbolic regression based on heuristic optimization algorithms.