<![CDATA[This research introduces an innovative algorithm for G-code modification using Fuzzy Logic Control (FLC) to optimize Computer Numerical Control (CNC) machining parameters without relying on additional hardware or sensors. The study develops a computational framework that processes G-code blocks with an average speed of 0.3ms while maintaining a minimal memory footprint of 1.2MB. Implementation results demonstrate an 18% reduction in total machining time, with the feed rate optimized from 1000 mm/min to 1180 mm/min for linear cutting and spindle speed enhanced from 3000 RPM to 3450 RPM, while maintaining conservative parameters for critical plunge cutting operations. The system achieved a 23% increase in tool life through intelligent parameter modulation. Testing on titanium alloy workpieces showed consistent performance with zero machining interruptions during parameter modification, marking a five-fold improvement in processing speed compared to existing sensor-based systems. This hardware-independent approach enables rapid deployment in existing CNC systems through simple software updates, offering a cost-effective solution for machining optimization. The research establishes a foundation for intelligent G-code generation that adapts to material properties and cutting conditions while maintaining operational safety and efficiency.]]>
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