Mobile phone middle frame CNC machining optimization method based on artificial intelligence

Through real-time scanning and dynamic adjustment of tool feed speed and cutting depth parameters, the sudden change in cutting force and chip discharge problems caused by uneven material hardness are solved, and high-precision and efficient intelligent processing are achieved.

CN120491552AActive Publication Date: 2025-08-15GUANGDONG ZHAOMING ELECTRONICS GRP CO LTD
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Patent Information

Application Number
CN202510963567.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-14
Publication Date
2025-08-15
Estimated Expiration
2045-07-14

AI Technical Summary

Technical Problem

Under the condition of uneven distribution of material hardness, the prior art is difficult to effectively deal with the problems of sudden cutting force and chip discharge difficulties, which affects the consistency of processing accuracy and surface quality.

Method used

The hardness distribution map is obtained through the sensor array to scan the surface of the workpiece in real time, establish a cutting force monitoring reference, identify fluctuation abnormal areas, dynamically adjust tool feed speed and cutting depth parameters, and optimize cutting path and chip discharge efficiency.

Benefits of technology

It improves machining accuracy and efficiency, reduces tool wear, realizes intelligent machining process control, and improves the processing quality and production efficiency of complex workpieces.

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Abstract

The invention provides a mobile phone middle frame CNC machining optimization method based on artificial intelligence. The mobile phone middle frame CNC machining optimization method comprises the steps that the surface of a mobile phone middle frame workpiece is scanned in real time, initial data of material hardness distribution are obtained, a hardness distribution mapping graph is formed, and a hardness change region division result is obtained; the hardness grade distribution and the cutting force sudden change amplitude of the cutting force sudden change specific position are recognized, adjustment parameters of the cutter feeding speed are obtained through calculation according to the hardness grade distribution and the cutting force sudden change amplitude, and a speed adjustment instruction is generated according to the adjustment parameters; and dynamically matching the cutting depth parameters according to the speed adjusting instruction, determining target cutting depth configuration, and matching the cutting path deviation monitoring value, the vibration amplitude index and the machining precision deviation value in real time through the target cutting depth configuration.
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