Control method for predicting product forming quality based on MES system and AI

Abstract

The invention relates to the technical field of product manufacturing, in particular to a control method for predicting product forming quality based on an MES system and AI, and the method comprises the following steps: S1, obtaining real-time data in a product forming process from the MES system, the real-time data including but not limited to parameters of pressure, temperature, speed, time, material characteristics, material batches and mold states; s2, preprocessing the acquired real-time data, and removing noise and abnormal values; s3, inputting the preprocessed data into a pre-trained AI prediction model, wherein the AI prediction model comprises any one of a convolutional neural network (CNN) and a recurrent neural network (RNN); s4, calculating a probability value P of unqualified product molding by using an AI prediction model; s5, when the calculated disqualification probability value P exceeds a preset threshold value T, sending an early warning signal to the MES system; and S6, the MES system adjusts related parameters in the product forming process according to the early warning signal so as to reduce the generation probability of unqualified products.

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