刀具寿命数据预测

通过采集机床的进给速度、主轴转速，以及获取刀具材料、工件材料、刀具镀层等数据以及刀具实际使用时长，来分析影响刀具寿命的关键因素，从而为刀具的选型和使用提供数据支持。通过采集机床的进给速度、主轴转速，以及获取刀具材料、工件材料、刀具镀层以及刀具寿命数据来训练预测刀具寿命的数学模型（神经网络模型），从而可以根据几个前置数据来预测刀具寿命。Two core applications are supported by this dataset: First, by collecting machine tool parameters including feed rate, spindle speed, alongside data on cutting tool materials, workpiece materials, tool coatings, and the actual service duration of tools, it is employed to analyze the key factors influencing tool service life, thus providing data support for tool selection and on-site application. Second, datasets containing the aforementioned machine tool parameters along with recorded tool service life data are used to train mathematical models (specifically neural network models) for predicting tool service life, enabling the prediction of tool service life based on provided input parameters.

搜集汇总

数据集介绍

特点

该数据集包含105条刀具寿命相关数据，涵盖刀片材料、加工参数等关键字段，用于分析刀具寿命影响因素并训练预测模型，适用于制造业刀具选型和使用优化。