摘要
There are multiple processes and corresponding parameters in steel production, and combinations of these comprise various process routes.Different steel products require distinct process routes due to variations in performance targets.Thus, how to accurately set each key process parameter in certain process routes is an ongoing conundrum, because it not only requires a wealth of expert experience but also generates additional costs from the trial productions.In this paper, a new production design system for plate steels is proposed.The proposed system consists of methodology and function development.For methodology, multi-task Elastic Net, clustering, classification, and other methods are used to design process routes.Furthermore, the results are expressed in the form of parameter confidence intervals, which are close to practical application scenarios.For function development, the steel plate process route design function is developed on the Process Intelligent Data Application System(PIDAS) intelligent big data platform.The results demonstrate the method’s practical application value.
