大数据条件下卷接机组设备即时健康评价模型  

Instant Health Evaluation Model for Reel-to-reel Equipment under Big Data Conditions

作　　者：韦伟[1] 胡亮 王伟伟 张玉 WEI Wei;HU Liang;WANG Weiwei;ZHANG Yu(School of Management Science and Engineering,Anhui University of Technology,Maanshan 243000,China)

机构地区：[1]安徽工业大学管理科学与工程学院,安徽马鞍山243000

出　　处：《物流科技》2023年第9期47-50,共4页Logistics Sci-Tech

摘　　要：在自动化技术愈发成熟的背景下,卷烟工业设备功能复杂、精确度提高、设备之间的关联性增强,目前对设备的风险健康状态评估仅停留在计划性维修,难以保证设备的可靠性水平。文章结合烟厂设备的实际情况,从设备运行积累的大量数据进行挖掘,利用Apriori算法找出与工艺指标存在关联关系的参数,利用熵权法确定权重。建立设备综合健康状态评价模型,计算出综合健康指数来判断设备的健康情况。最后通过案例分析验证了此方法的可用性,为设备维修保养的决策方案提供依据。In the context of increasingly mature automation technology,the function of cigarette industry equipment is complex,the accuracy is improved,and the correlation between equipment is also enhanced.At present,the risk health status assessment of equipment only stays in the planned maintenance,which is difficult to ensure the reliability level of equipment.In this paper,combined with the actual situation of tobacco factory equipment,a large amount of data accumulated from the operation of equipment is mined,and the Apriori algorithm is used to find out the parameters associated with process indicators,and the entropy weight method is used to determine the weight.The comprehensive health status evaluation model of equipment is established,and the comprehensive health index is calculated to judge the health status of equipment.Finally,the feasibility of this method is verified by case analysis,which provides a basis for the decision-making scheme of equipment maintenance.

关 键 词：卷烟工业 健康状态评价 APRIORI算法 健康指数 

分 类 号：TP271[自动化与计算机技术—检测技术与自动化装置]