Plate processing dynamic scheduling method based on digital twinning and real-time optimization

By constructing a digital twin workshop model and a real-time multi-objective optimization scheduling algorithm, the problem of insufficient energy consumption assessment in traditional dynamic scheduling of sheet metal processing was solved, realizing energy consumption optimization and time efficiency balance during production disturbances, and reducing production costs.

CN121836282APending Publication Date: 2026-04-10GUANGXI FUSUI FANGZHOU WOOD IND CO LTD
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Patent Information

Application Number
CN202610191181.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-02-10
Publication Date
2026-04-10

AI Technical Summary

Technical Problem

Traditional dynamic scheduling methods for sheet metal processing lack the ability to effectively perceive and predict real-time energy consumption during production. This can lead to high-energy-consuming equipment load combinations or process sequences during equipment rescheduling, increasing production costs and contradicting the concept of green manufacturing.

Method used

A dynamic scheduling method for sheet metal processing based on digital twins and real-time optimization is constructed. The energy consumption of processing equipment is perceived and predicted in real time through a digital twin workshop model. Combined with a real-time multi-objective optimization scheduling algorithm, a Pareto optimal scheduling scheme is generated to optimize the overall energy consumption of the workshop.

Benefits of technology

It enables rapid response to production disruptions while optimizing workshop energy consumption, reducing production costs, and improving the scientific nature and response speed of production scheduling.

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Abstract

The invention relates to a plate processing dynamic scheduling method based on digital twinning and real-time optimization, and belongs to the technical field of intelligent manufacturing and production scheduling. The problems that energy waste and production cost increase are possibly caused when disturbance rescheduling is dealt with because production energy consumption is ignored in existing plate processing dynamic scheduling are solved. A digital twin workshop model comprising a physical workshop layer, a virtual workshop layer and a workshop service system layer is constructed, a real-time energy consumption prediction sub-model is integrated for processing equipment in the virtual workshop layer, equipment operation state data are collected and synchronized in real time, the energy consumption prediction sub-model is used for calculating instantaneous estimated power and workshop real-time total power, and the real-time total power of the workshop is calculated. And a dynamic scheduling trigger condition is determined based on the equipment alarm, the newly added task instruction and the real-time total power information. The method is mainly used for achieving dynamic optimization scheduling considering production efficiency and energy consumption when disturbance occurs in the plate machining process.
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