Affiliation:
1. Institute of Manufacturing Engineering
Abstract
Abstract
Existing research on coated tools does not predict data while exploring the changing rules. As well as the traditional cutting process parameters neither guarantees the surface quality of the 30CrMnSiNi2A nor attains high material removal rate (MRR). Accurate control and prediction of workpiece three-dimensional surface roughness (Sq) and specific cutting energy consumption (SCEC) are of vital significance to improve quality, reduce cost and improve efficiency. Here, according to the new SCEC calculation model and the influence of measuring position on Sq, the SCEC and Sq values are accurately obtained. Then, based on the idea of fitting formula, the influence of cutting parameters on SCEC and Sq in high-speed dry (HSD) milling of 30CrMnSiNi2A steel is analyzed according to CVD and PVD coated inserts. Finally, the SCEC and Sq prediction models considering coating type, cutting speed, feed per tooth and cutting width are established by using the XGBoost algorithm. The R2 values of SCEC and Sq are 0.92465 and 0.91527, respectively, indicating that the model has a good prediction effect on experimental data. The feasibility of HSD milling of 30CrMnSiNi2A steel with CVD and PVD coated inserts is verified by analyzing SCEC, Sq and cutting temperature, which provides experimental basis for high efficiency and high precision machining of 30CrMnSiNi2A steel.
Publisher
Research Square Platform LLC
Cited by
1 articles.
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1. Optimization techniques for energy efficiency in machining processes—a review;The International Journal of Advanced Manufacturing Technology;2023-02-02