基于DT的售后设备预测性维护协同模式研究_李晓.pdf

1、第 28 卷 第 1 期2023 年 2 月工业工程与管理Industrial Engineering and ManagementVol.28 No.1Feb.2023基于DT的售后设备预测性维护协同模式研究李晓，陈雨晨*，阮渊鹏，王雷，劳晓云（杭州电子科技大学 管理学院，浙江 杭州 310018）摘要:设备制造商为了满足设备用户对快速故障诊断和维护的需求，需要对设备进行实时监测、预测和远程指导。以数字孪生五维模型为基础，提出基于数字孪生的协同维护七维模型和维护服务协同模式。该模式下设备制造商和设备用户可实时获得对设备的监测信息，使得制造商能向用户提供更有效、及时的服务和支持。最后以某瓶装水

2、封盖过程为例，构建设备隐式半马尔可夫模型，对设备当前运行状态的持续时间进行测算，得到与下一次劣化或故障状态的时间间隔，起到预测效果。构建了数字孪生服务平台框架和维护知识数据库，验证了所提出的协同维护模式的可行性。关键词:数字孪生；预测性维护；协同维护；隐式半马尔可夫模型；售后设备中图分类号:C 931 文献标识码:AResearch on Collaborative Model of Predictive Maintenance for After-sales Equipment Based on DTLI Xiao，CHEN Yuchen*，RUAN Yuanpeng，WANG Lei，LA

3、O Xiaoyun（School of Management，Hangzhou Dianzi University，Hangzhou，Zhejiang 310018，China）Abstract:In response to the demands of users for prompt fault diagnosis and maintenance，equipment manufacturers require more advanced maintenance technologies for real-time monitoring，prediction，and remote guida

4、nce.Based on the existing five-dimensional digital twin model，a seven-dimensional model of collaborative maintenance and a collaborative maintenance model were proposed based on the digital twin virtual representation.In these models，equipment manufacturers and users could obtain real-time monitorin

5、g information of equipment.This enabled manufacturers to provide more effective and timely service and support to customers.Finally，by using a bottled water capping process as an example and utilizing the hidden semi-Markov model of equipment，the duration of the current operational state for capping

6、 equipment were predicted.The time interval with the next degradation or fault state was obtained，which has the prediction effect.A digital twin service platform framework and a maintenance knowledge database were constructed to verify the feasibility of the collaborative maintenance model.Key words:digital twin;predictive maintenance;collaborative maintenance;hidden semi-Markov model;after-sales equipment文章编号：1007-5429（2023）01-0067-14DOI：10.19495/ki.1007-5429.2023.01.009收稿日期：2021-05-07基金项目：