CNC Machining Data Repository - Geometry, NC Code & High-Frequency Energy Consumption Data for Aluminum and Plastic Machining

In the field of manufacturing, high-quality datasets are essential for optimizing production processes, improving energy efficiency, and developing predictive maintenance strategies. This repository introduces a comprehensive CNC machining data repository that includes three key data categories: (1) product geometry data, (2) NC code data, and (3) high frequency energy consumption data. This dataset is particularly valuable for researchers and engineers working in manufacturing analytics, energy-efficient machining, and machine learning applications in smart manufacturing. Potential use cases include optimizing machining parameters for energy reduction, predicting tool wear based on power consumption patterns, and enhancing digital twin models with real-world machining data. By making this dataset publicly available, we aim to support the development of data-driven solutions in modern manufacturing and facilitate benchmarking efforts across different machining strategies.

在制造领域，高质量数据集对于优化生产流程、提升能源利用效率以及制定预测性维护策略而言至关重要。本开源仓库提供了一套完备的计算机数字控制（CNC）加工数据集，涵盖三大核心数据类别：(1) 产品几何数据，(2) 数控代码（NC code）数据，(3) 高频能耗数据。该数据集对于从事制造数据分析、节能加工以及智能制造领域机器学习应用的研究人员与工程师而言具有极高的应用价值。其潜在应用场景包括：优化加工参数以降低能耗、基于能耗模式预测刀具磨损，以及结合真实加工数据完善数字孪生（Digital Twin）模型。通过公开该数据集，我们旨在助力现代制造业中数据驱动型解决方案的研发，并推动不同加工策略间的基准测试工作。