Energy efficiency identification and surface roughness prediction using cutting force signal for computer numerical controlled machine systems

• Published in: Scientific reports Vol. 14; no. 1; pp. 19004 - 17
• Main Authors: Feng, Chunhua, Li, Meng, Guo, Haohao, Qiu, Binbin, Zhang, Jingyang
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 16.08.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 704/172; 704/172/4081; Algorithms; CEEMDAN; Energy consumption; Energy efficiency; Energy efficiency identification; Energy utilization; Humanities and Social Sciences; multidisciplinary; PCA-Fast ICA; Prediction models; Science; Science (multidisciplinary); Surface roughness; Sustainable production; PCA-Fast ICA; Surface roughness; Energy efficiency identification; CEEMDAN

The energy efficiency identification of machining process plays an indispensable part in achieving energy-efficient manufacturing and improving energy utilization as well as productivity and surface quality. However, there is a great difficulty to track energy efficiency in real-time based on one ki...