基于性能退化预测的数控机床预防维修方法

Preventive Maintenance Method of CNC Machine Tools Based on Performance Degradation Prediction

为解决数控机床传统维修方法存在的“欠维护”或“过维护”弊端,提出了一种基于系统性能退化预测的预防维修方法,利用统计过程控制技术分析产品质量数据,实现机床工作状态的预测。建立了关键零部件的Wiener退化模型来预测寿命分布,从而可结合剩余寿命和收益确定最优预防维修策略。以某汽车活塞生产线上的数控机床异常数据为例,验证了所提方法的有效性。

In order to solve the disadvantages of “under maintenance” or “over maintenance” in traditional maintenance methods of CNC machine tools, a preventive maintenance method was proposed based on the prediction of system performance degradation. The SPC technology was used to analyze the product quality data and realize the prediction of the working states for the machine tools. The Wiener degradation model of a key component was established to predict the life distribution, so that the optimal preventive maintenance strategy might be determined by residual life and revenues. Taking the abnormal data of CNC machine tools in an automobile piston production line as an example, the validity of proposed method was verified.