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AI-Driven Intelligent Grinding Automation for Precision Motorcycle Camshaft Manufacturing
Shih-Chen Shi a, Jun-Han Lin b and Guan-Yu Chen b
aProfessor, Department of Mechanical Engineering, National Cheng Kung University, 70101 Tainan, Taiwan
bStudent, Department of Mechanical Engineering, National Cheng Kung University, 70101 Tainan, Taiwan
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Abstract:
Precision and efficiency are essential in modern manufacturing, yet motorcycle camshaft production still faces labor shortages and inconsistent manual machining challenges. In this study, an AI-driven intelligent grinding automation system was developed to enhance machining accuracy and productivity. The system integrated real-time monitoring, data acquisition, and adaptive parameter control to replace manual adjustments. Key machining parameters were optimized using the Taguchi method and polynomial regression modeling, while a simulated machining environment with image recognition enabled real-time prediction and correction. Experimental results showed a 95% qualification rate at a surface roughness below 2.4 μm, a 38% reduction in processing time, and an increase in daily output from 128 to 235 units. These findings demonstrate that the proposed system provides a scalable and efficient approach to precision camshaft manufacturing and represents a significant advancement toward intelligent, data-driven production in the Industry 4.0 era.
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Keywords: AI-driven automation, Intelligent grinding system, Taguchi optimization, Real-time monitoring and control, Precision camshaft manufacturing.
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©
2026
CSME , ISSN 0257-9731
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