Physics-guided synthetic dataset for CNC turning of Ti-6Al-4V alloy

This dataset contains synthetic data generated to support the construction, evaluation, and performance analysis of a CNC milling machine based on a modified open-source platform. The data were created to complement experimental analyses and to enable reproducibility, benchmarking, and methodological validation in scenarios where extensive physical testing may be limited by cost, time, or hardware availability. The synthetic dataset represents operational and performance-related variables commonly associated with CNC milling systems, such as positioning behavior, operational stability, and machine performance trends. The generation process was guided by realistic machining constraints and system behavior, ensuring coherence with practical CNC operation while preserving flexibility for simulation, modeling, and comparative studies. This dataset is intended for use in manufacturing research, CNC machine development, automation studies, performance modeling, and educational purposes. It can support tasks such as performance analysis, sensitivity studies, algorithm testing, and validation of control or optimization strategies applied to open-source CNC platforms. All data are provided in a structured and accessible format, facilitating reuse and integration into analytical workflows, numerical simulations, and machine learning pipelines. The dataset is particularly suitable for researchers interested in low-cost CNC development, open-source manufacturing systems, and synthetic data applications in advanced manufacturing research.