摘要
随着公司设备复杂性和多样性的提升,传统报修模式在应对故障处理和决策支持方面暴露出诸多局限性。为提升报修管理的智能化水平,该研究提出一种基于数据挖掘的智能报修决策支持系统。该系统使用互联网技术及数据处理通过收集和分析大量历史报修数据与实时设备运行数据,利用分类、聚类、关联规则等数据挖掘技术,自动化地进行故障预测、任务调度及维修资源优化分配。
With the increasing complexity and diversity of company equipment,the traditional repair mode has exposed many limitations in dealing with fault handling and decision support.In order to improve the intelligent level of repair management,this paper proposes an intelligent repair decision support system based on data mining.The system uses Internet technology and data processing to collect and analyze a large number of historical repair data and real-time equipment operation data,and uses data mining technologies such as classification,clustering and association rules to automate fault prediction,task scheduling and optimal allocation of maintenance resources.
出处
《科技创新与应用》
2025年第13期33-37,共5页
Technology Innovation and Application
基金
武汉品道建筑园林工程有限公司2024科研项目(2024JSZN5KJ-YL2-001)。
关键词
数据挖掘
自动化
人工智能
智能报修决策支持系统
报修数据
data mining
automation
artificial intelligence
intelligent repair decision support system
repair data
