Digital twin and real-time data feedback driven forging production optimization method and system

Abstract

This application provides a method and system for optimizing forging production driven by digital twins and real-time data feedback, belonging to the field of process optimization technology. The method includes: parsing the contextual data chain of related parameters based on forging production target optimization parameters; constructing a digital twin space and establishing a real-time data interaction path; updating the digital twin space using the real-time data interaction path; acquiring pre-processed product variables; simulating the production process and processing parameters through the digital twin space; and outputting a forging production process optimization strategy that achieves the optimization target, used for deploying the production process of pre-processed products. This application solves the technical problem in the prior art where the lack of simulation and optimization of process parameters before processing makes it difficult to detect and adjust process problems in a timely manner during processing, further affecting production efficiency. By using digital twins for full-process production pre-simulation, optimization before production is achieved, reducing product defect rates and improving production efficiency.

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