数字孪生驱动的机床预测性再制造新模式研究

New predictive remanufacturing model of machine tool driven by digital twins

在分析机床再制造产业面临的挑战与现有“事后”型再制造模式不足的基础上,提出数字孪生驱动的机床预测性再制造新模式。将故障预测与健康管理(PHM)融入再制造,提出并详细阐述了数字孪生驱动的机床预测性再制造新模式的关键技术体系与实现框架,包括机床数字孪生体构建、机床运行状态监测与诊断、机床故障预测与健康管理、机床再制造时机决策、机床再设计与再制造等。通过上述体系架构及关键技术实施,构建了一种多状态监测与诊断、数字孪生全过程驱动、再制造时机智能判断的在役机床“事前”预测性再制造运行机制,可有效减少突发性故障及停工损失并保障企业的制造能力。

Based on the analysis of the challenges faced by the industry of machine tool remanufacturing and the issues of the existing breakdown remanufacturing model,a new predictive remanufacturing model of machine tool driven by digital twins was proposed.Integrating the theory of Prognostics and Health Management(PHM)into remanufacturing,the key technology system and implementation framework of the predictive remanufacturing model of machine tool driven by digital twins were proposed,including the construction of digital twins of machine tools,the monitoring and diagnosis of operation conditions of machine tool,the prognostics and health management of machine tool,the timing decision-making of machine tool remanufacturing,machine tool redesign and remanufacturing,etc.Through the implementation of the above system architecture and key technologies,a failure-before remanufacturing operation mechanism based on multi-state monitoring and diagnosis,full-process drive of digital twins,and intelligent judgment of remanufacturing timing was built for in-service machine tools,which could effectively reduce the sudden failures and downtime losses and guarantee the company s manufacturing capacity.