[数据驱动的智能服务]数据驱动的复杂产品智能服务技术与应用

随着传感器、数据采集装置和其他具备感知能力的模块在复杂产品服务运行阶段的应用，复杂产品运维系统的数字化和智能化程度越来越高，具有实时、多源、异构、海量等特性的数据成为提高复杂产品系统可靠和低成本运行的决策依据，数字孪生技术提供了一种有效途径。介绍了数据驱动的复杂产品智能服务研究进展；分析了数据驱动的智能服务基本特征与框架模型；提出了数据驱动的复杂产品智能服务方法，主要包括面向服务的复杂产品建模与仿真方法、数据驱动的服务需求获取与精准分析预测方法、基于数字孪生的设备故障识别与动态性能预测方法、数据驱动的装备视情维修与备件库存联合多目标决策优化方法、基于数字孪生的复杂产品辅助维修技术、多要素协同的复杂装备能效精准分析预测方法、基于数据挖掘的复杂产品运行优化控制方法等；给出了智能服务系统的应用案例。所提出的框架和方法可为现代制造服务的智能化转型升级提供参考。

Technology and Application of Data-driven Intelligent Services for Complex Products

With the applications of sensors, data acquisition devices and other modules with sensing ability in the service operation stages of complex products, the operation and maintenance system of complex products was becoming more and more digital and intelligent. Data with real-time, multi-source, heterogeneous, and massive characteristics were become the basis of decision making to improve the reliability and low cost operation for complex product systems, especially the DT technology provided an effective way. Thus, the research progress of data-driven intelligent service for complex products was introduced. The characteristics and framework mode of data-driven intelligent services were analyzed herein, and data-driven intelligent service approaches for complex products were proposed, which included service-oriented complex product modeling and simulation methods, accurate analysis and prediction method for data-driven service demand acquisition, equipment fault identification and dynamic performance prediction based on DT, data-driven multi-objective decision-making optimization method for equipment condition-based maintenance and spare parts inventory, assisted maintenance technology for complex products based on DT, precise analysis and prediction method for energy efficiency of complex equipment based on multi-element cooperation, and optimal control method for complex product operation based on data mining. The application case of intelligent service system was given. The proposed framework and approach may provide reference for the intelligent transformation and upgrading of modern manufacturing services.