Dataset and MATLAB analysis scripts for surface roughness and tool wear study in C45 steel turning

Experimental dataset and MATLAB analysis scripts supporting the study: Surface Roughness Prediction and Tool Wear Analysis in Steel Turning Using Machine Learning and Bayesian Optimisation. Includes: (1) DOE measurements (N=40, Rz and Ra), (2) time-series Rz data (424 measurements at 6 cutting speeds), (3) flank wear VB data (42 measurements), and (4) complete MATLAB pipeline (S0-S7) for DOE analysis, ML modelling, Bayesian optimisation, and tool wear analysis.本数据集与配套MATLAB分析脚本支撑下述研究：采用机器学习（Machine Learning，ML）与贝叶斯优化的钢车削表面粗糙度预测及刀具磨损分析。包含以下内容：（1）实验设计（Design of Experiments，DOE）测量数据（样本量N=40，涵盖微观不平度十点高度Rz与轮廓算术平均偏差Ra）；（2）时序Rz数据（6种切削速度下共计424组测量值）；（3）后刀面磨损VB数据（共计42组测量值）；（4）用于实验设计分析、机器学习建模、贝叶斯优化及刀具磨损分析的完整MATLAB工作流（S0至S7阶段）。