摘要
针对设备部件延寿预测问题,首先,提出了上下限两种异常畸变指标,并给出灰色多指标延寿畸变预测模型的架构图和延寿预测示意图。其次,运用灰色系统方法分别构建了两阶段灰色预测模型,在第一阶段构建了灰色上下限畸变预测模型,得到下一次发生畸变的日期;在第二阶段构建了GM(1,1)模型,对设备部件延寿以及上下限指标的异常值进行预测。同时,对模型的预测精度进行检验和分析,并根据模型的预测结果确定了设备部件延寿的时间。最后,以半导体制造业设备靶材延寿为实际应用案例,验证了该模型的有效性和可行性,为合理制定部件的最优维护更换时间以及对降低企业运维成本具有重要指导意义。
Aiming at the problem of life extension prediction of equipment components,two abnormal distortion indexes of upper and lower limits are put forward firstly.And framework diagram and life extension prediction diagram of grey multi index life extension distortion prediction model are given.Secondly,the grey system method is used to build a two-stage grey prediction model.In the first stage,the grey upper and lower limit distortion prediction model is constructed to obtain the date of the next distortion;In the second stage,GM(1,1)model is built to predict the life extension of equipment components and the abnormal values of upper and lower limit indicators.At the same time,the prediction accuracy of the model was tested and analyzed,and the life extension time of equipment components was determined according to the prediction results of the model.Finally,the effectiveness and feasibility of the model are verified by taking the semiconductor manufacturing equipment target life extension as an actual application case,which has important guiding significance for reasonable formulation of the optimal maintenance and replacement time of components and for reducing the operation and maintenance costs of enterprises.
作者
李强
刘思峰
LI Qiang;LIU Sifeng(College of Economic and Management,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;Institute for Grey System Studies,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2023年第2期597-605,共9页
Systems Engineering and Electronics
基金
国家自然科学基金(72071111,71671091)资助课题。
关键词
设备延寿
剩余寿命
灰色畸变预测
半导体靶材
equipment life extension
residual life
grey distortion prediction
semicoductor target material
