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Prediction maintenance integrated decision-making approach supported by digital twin-driven cooperative awareness and interconnection framework
Journal of Manufacturing Systems ( IF 12.2 ) Pub Date : 2020-08-01 , DOI: 10.1016/j.jmsy.2020.08.001
Shanghua Mi , Yixiong Feng , Hao Zheng , Yong Wang , Yicong Gao , Jianrong Tan

Abstract Predictive maintenance is one of the important technical means to guarantee and improve the normal industrial production. The existing bottlenecks for popularization and application are analyzed. In order to solve these problems, a cooperative awareness and interconnection framework across multiple organizations for total factors that affect prediction maintenance decision-making is discussed. Initially, the structure and operation mechanism of this framework are proposed. It is designed to support the sharing of data, knowledge and resources. As a key supporting technology, the digital twin is also integrated into it to improve the accuracy of fault diagnosis and prediction and support making a maintenance plan with higher accuracy and reliability. Then, under this framework, an integrated mathematical programming model is established with considering the parameter uncertainty and an NSGA-II hybrid algorithm is utilized to solve it. Moreover, an adjustment strategy for a maintenance plan is discussed in response to the dynamic characteristics of the actual maintenance environment. Finally, a case, prediction maintenance decision-making for bearings in grinding rolls of the large vertical mill, is studied. Analysis results verify the advantage of the integrated solving mechanism based on the proposed framework. The framework and integrated decision-making approach can guide the implementation of predictive maintenance with higher accuracy and reliability for industrial enterprises.

中文翻译:

数字孪生驱动的协同感知与互联框架支持的预测维护综合决策方法

摘要 预测性维修是保障和提高工业生产正常进行的重要技术手段之一。分析了推广应用存在的瓶颈。为了解决这些问题,针对影响预测维护决策的总因素,讨论了跨多个组织的协作意识和互连框架。初步提出了该框架的结构和运行机制。它旨在支持数据、知识和资源的共享。作为关键支撑技术,还集成了数字孪生技术,提高了故障诊断和预测的准确性,支持制定更准确、更可靠的维修计划。那么,在这个框架下,建立了考虑参数不确定性的综合数学规划模型,并采用NSGA-II混合算法进行求解。此外,针对实际维修环境的动态特性,讨论了维修计划的调整策略。最后,以大型立磨磨辊轴承预测维修决策为例进行了研究。分析结果验证了基于所提出框架的集成求解机制的优势。该框架和综合决策方法可以指导工业企业实施更准确、更可靠的预测性维护。针对实际维修环境的动态特性,讨论了维修计划的调整策略。最后,以大型立磨磨辊轴承预测维修决策为例进行了研究。分析结果验证了基于所提出框架的集成求解机制的优势。该框架和综合决策方法可以指导工业企业实施更准确、更可靠的预测性维护。针对实际维修环境的动态特性,讨论了维修计划的调整策略。最后,以大型立磨磨辊轴承预测维修决策为例进行了研究。分析结果验证了基于所提出框架的集成求解机制的优势。该框架和综合决策方法可以指导工业企业实施更准确、更可靠的预测性维护。分析结果验证了基于所提出框架的集成求解机制的优势。该框架和综合决策方法可以指导工业企业实施更准确、更可靠的预测性维护。分析结果验证了基于所提出框架的集成求解机制的优势。该框架和综合决策方法可以指导工业企业实施更准确、更可靠的预测性维护。
更新日期:2020-08-01
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