Digital twin-based smart assembly process design and application framework for complex products and its case study

With rapid advances in new generation information technologies, digital twin (DT), and cyber-physical system, smart assembly has become a core focus for intelligent manufacturing in the fourth industrial evolution. Deep integration between information and physical worlds is a key phase to develop smart assembly process design that bridge the gap between product assembly design and manufacturing. This paper presents a digital twin reference model for smart assembly process design, and proposes an application framework for DT-based smart assembly with three layers. Product assembly station components are detailed in the physical space layer; two main modules, communication connection and data processing, are introduced in the interaction layer; and we discuss working mechanisms of assembly process planning, simulation, predication, and control management in the virtual space layer in detail. A case study shows the proposed approach application for an experimental simplified satellite assembly case using the DT-based assembly application system (DT-AAS) to verify the proposed application framework and method effectiveness.     

基于LabVIEW和MATLAB的数字孪生供热系统平台的设计与仿真

数字孪生技术充分利用物理结构、传感器更新、设备运行历史等数据通过集成多领域、多物理量、多可能性的模拟过程，在虚拟空间中进行镜像，以此表达相对应的实物装置的整个生命周期过程。从智慧供热的发展历史来看，依托现代工业系统理念，提出了基于"数字孪生"的智能供热系统结构。首先介绍了数字孪生的基本结构，给出了数字孪生的构建方式基于虚拟仪器Labview的大数据采集、处理、归档、仿真；然后以采集的数据为基础，得到供热系统的孪生模型，叙述了数字孪生技术解决的关键问题；最后，通过Labview仿真平台调用Matlab中神经网络智能算法，得到基于大数据采集以及经过智能算法优化后的参数，同时系统将参数反馈给物理实体设备，从而完成孪生模型的仿真、优化、反馈过程。通过热网系统优化仿真案例验证了Labview和Matlab混合编程在建立的孪生供热平台上、应用的有效性。     

数字孪生: 跨界赋能于多领域智能的新应用

随着大数据、5G、人工智能、CPS、云计算、物联网技术的发展与交叉融合, 使得世界朝着数字化、智能化方向发展. 数字孪生是以物理实体为原型建立多维虚拟模型, 通过安装在物理本体上的传感器实时反馈数据, 并结合以往的历史数据和人工智能技术, 最后利用软件分析并呈现. 由于数字孪生技术能与多个先进理念, 如: 工业4.0、航空航天、智慧城市、智慧医疗等良好的融合并应用, 这使其成为多个行业的热门研究方向与主要驱动技术, 在各行各业都有很大的发展空间. 本文首先阐述了数字孪生技术的基本概念, 梳理了数字孪生技术的发展脉络, 进一步理清了数字孪生技术与CPS技术之间的关系, 并介绍了数字孪生技术的研究现状. 其次, 介绍了数字孪生的关键技术即多维多尺度建模, 孪生数据管理和虚拟呈现. 最后, 探讨了数字孪生技术在智慧工厂领域、智慧城市领域、孪生医疗领域、航空航天领域的应用发展和方向, 并从方案、特点、关键技术等角度介绍了本研究团队在智慧工厂领域对原稳加热炉设备的数字孪生应用案例.     

A digital twin to train deep reinforcement learning agent for smart manufacturing plants: Environment,interfaces and intelligence

Filling the gaps between virtual and physical systems will open new doors in Smart Manufacturing. This work proposes a data-driven approach to utilize digital transformation methods to automate smart manufacturing systems. This is fundamentally enabled by using a digital twin to represent manufacturing cells, simulate system behaviors, predict process faults, and adaptively control manipulated variables. First, the manufacturing cell is accommodated to environments such as computer-aided applications, industrial Product Lifecycle Management solutions, and control platforms for automation systems. Second, a network of interfaces between the environments is designed and implemented to enable communication between the digital world and physical manufacturing plant, so that near-synchronous controls can be achieved. Third, capabilities of some members in the family of Deep Reinforcement Learning (DRL) are discussed with manufacturing features within the context of Smart Manufacturing. Trained results for Deep Q Learning algorithms are finally presented in this work as a case study to incorporate DRL-based artificial intelligence to the industrial control process. As a result, developed control methodology, named Digital Engine, is expected to acquire process knowledges, schedule manufacturing tasks, identify optimal actions, and demonstrate control robustness. The authors show that integrating a smart agent into the industrial platforms further expands the usage of the system-level digital twin, where intelligent control algorithms are trained and verified upfront before deployed to the physical world for implementation. Moreover, DRL approach to automated manufacturing control problems under facile optimization environments will be a novel combination between data science and manufacturing industries.     

面向智能矿山与新工科的数字孪生技术研究

将数字孪生与人工智能(AI)技术相结合,提出了基于数字孪生+AI的智能矿山建设新思路。探索了智能矿山技术发展路径,研究了数字孪生技术的特征、应用领域及发展趋势,指出数字孪生是数字化矿山发展的必然趋势。提出了基于数字孪生+AI的智能矿山理论架构,构建了矿山数字孪生模型,模型自下而上分别为矿山全要素物理实体、矿山信息物理融合层、矿山数字孪生模型、矿山孪生数据交互层、矿山应用智能服务层,据此实现智能矿山的泛在感知、协同控制和智能决策与优化。从应用实际需求出发,探讨了智能矿山模型构建技术、智能开采数字孪生体技术、矿山智能控制技术、矿山设备故障预测、基于数字孪生的人机交互等关键技术。通过研究数字孪生在智能矿山中的应用,为AI技术在智能矿山应用落地提供思路,为未来智能矿山新工科建设提供理论借鉴。     

Data-driven cyber-physical system framework for connected resistance spot welding weldability certification

A cyber-physical system is one of the integral parts of the development endeavor of the smart manufacturing domain and the Industry 4.0 wave. With the advances in data analytics, smart manufacturing is gradually transforming the global manufacturing landscape. In the Resistance Spot Welding (RSW) domain, the focus has been more on the physical systems, compared to the virtual systems. The cyber-physical system facilitates the integrated analysis of the design and manufacturing processes by converging the physical and virtual stages to improve product quality in real-time. However, a cyber-physical system integrated RSW weldability certification is still an unmet need. This research is to realize a real-time data-driven cyber-physical system framework with integrated analytics and parameter optimization capabilities for connected RSW weldability certification. The framework is based on the conceptualization of the layers of the cyber-physical system and can incorporate the design and machine changes. It integrates data from the analytics lifecycle phases, starting from the data collection operation, to the predictive analytics operation, and to the visualization of the design. This integrated framework aims to support decision-makers to understand product design and its manufacturing implications. In addition to data analytics, the proposed framework implements a closed-loop machine parameter optimization considering the target product design. The framework visualizes the target product assembly with predicted response parameters along with displaying the process parameters and material design parameters simultaneously. This layer should help the designers in their decision-making process and the engineers to gain knowledge about the manufacturing processes. A case study on the basis of a real industrial case and data is presented in detail to illustrate the application of the envisioned cyber-physical systems framework.     

A systematic review of digital twin about physical entities,virtual models,twin data,and applications

The digital twin is a crucial technology for realizing smart manufacturing and industrial digital transformation, which has received extensive attention and research from industry and academia. After 20 years of development, the application area of digital twins has been pervasive. Due to the diversity of application areas, various reference models and research methods have been presented for the components of the digital twin. Therefore, this paper provides systematic research of current studies on the basic components of the digital twin. This paper analyzed 117 articles from 2017 to 2022. By clarifying the relationship between the digital twin and the cyber-physical system, it first clarified the definition, characteristics, and application areas of the digital twin. On this basis, the research methodology of the core components of the digital twin (physical entities, virtual models, and twin data) is analyzed. At the same time, the application areas of digital twins are analyzed and delineated, and the application potential of the digital twin is explored. Finally, the research results and future research recommendations are presented.     

A digital twin emulator of a modular production system using a data-driven hybrid modeling and simulation approach

Virtual commissioning is a key technology in Industry 4.0 that can address issues faced by engineers during early design phases. The process of virtual commissioning involves the creation of a Digital Twin—a dynamic, virtual representation of a corresponding physical system. The digital twin model can be used for testing and verifying the control system in a simulated virtual environment to achieve rapid set-up and optimization prior to physical commissioning. Additionally, the modular production control systems, can be integrated and tested during or prior to the construction of the physical system. This paper describes the implementation of a digital twin emulator of an automated mechatronic modular production system that is linked with the running programmable logic controllers and allow for exchanging near real-time information with the physical system. The development and deployment of the digital twin emulator involves a novel hybrid simulation- and data-driven modeling approach that combines Discrete Event Simulation and Agent Based Modeling paradigms. The Digital Twin Emulator can support design decisions, test what-if system configurations, verify and validate the actual behavior of the complete system off-line, test realistic reactions, and provide statistics on the system’s performance.

     

A framework and method for Human-Robot cooperative safe control based on digital twin

Human-robot collaboration (HRC) combines the robot’s mechanical properties and predictability with human experience, logical thinking, and strain capabilities to alleviate production efficiency. However, ensuring the safety of the HRC process in-real time has become an urgent issue. Digital twin extends functions of virtual models in the design phase of the physical counterpart in the production phase through virtual-real interactive feedback, data fusion analysis, advanced computational features, etc. This paper proposes an HRC safety control framework and corresponding method based on the digital twin. In the design phase, virtual simulation and virtual reality technology are integrated to construct virtual twins of various HRC scenarios for testing and analyzing potential safety hazards. In the production phase, the safety distance between humans and robots of the HRC scene is monitored and calculated by an iterative algorithm according to machine vision and a convolutional neural network. Finally, the virtual twin is driven based on real-scene data, real-time online visual monitoring, and optimization of the HRC’s overall process. A case study using ABB-IRB1600 is presented to verify the feasibility of the proposed approach.     

北大港水库数字孪生建设方案与要点探讨

为提升北大港水库工程管理现代化与智慧化水平，结合北大港水库“数字河库”建设现状和水库扩容工程规划，提出北大港水库数字孪生建设方案，搭建数字孪生工程建设总体框架与主要内容，丰富 L2 和 L3 级数据底板， 构建模型库和知识库，实现建设期和运维期的智能应用建设。对安全监测数据底板、工程安全模型等数字孪生建设难点，以及实现“四大安全”与全过程、全要素管理等进行探讨。实现北大港水库流域防洪调度、水资源管理与调配，以及其他各项业务管理的数字化、网络化、智能化水平提升，有效推进水库运营管理数字化转型和智能化升级。     

DT-II:Digital twin enhanced Industrial Internet reference framework towards smart manufacturing

In this paper, the interplay and relationship between digital twin and Industrial Internet are discussed at first. The sensing/transmission network capability, which is one of the main characteristics of Industrial Internet, can be a carrier for providing digital twin with a means of data acquisition and transmission. Conversely, with the capability of high-fidelity virtual modeling and simulation computing/analysis, digital twin evolving from lifecycle management for a single product to application in production/manufacturing in the shop-floor/enterprise, can further greatly enhance the simulation computing and analysis of Industrial Internet. This paper proposes a digital twin enhanced Industrial Internet (DT-II) reference framework towards smart manufacturing. To further illustrate the reference framework, the implementation and operation mechanism of DT-II is discussed from three perspectives, including product lifecycle level, intra-enterprise level and inter-enterprise level. Finally, steam turbine is taken as an example to illustrate the application scenes from above three perspectives under the circumstance of DT-II. The differences between with and without DT-II for design and development of steam turbine are also presented.     

Unified modeling for digital twin of a knowledge-based system design

While Model-Based Systems Engineering (MBSE) improves the ambiguity problem of the conventional document-based way, it brings management complexity. Faced with the complexity, one of the core issues that companies care about is how to effectively evaluate, predict, and manage it in the early system design stage. The inaccuracy of contemporary complexity measurement approaches still exits due to the inconsistency between the actual design process in physical space and the theoretical simulation in virtual space. Digital Twin (DT) provides a promising way to alleviate the problem by bridging the physical space and virtual space. Aiming to integrate DT with MBSE for the system design complexity analysis and prediction, based on previous work, an integration framework named System Design Digital Twin in 5 Dimensions was introduced from a knowledge perspective. The framework provides services for design complexity measurement, effort estimation, and change propagation prediction. Then, to represent the system design digital twin in a unified way, a modeling profile is constructed through SysML stereotypes. The modeling profile includes System design digital model in virtual space profile, system services profile, relationships profile and digital twin data profile. Finally, the system design of a cube-satellite space mission demonstrates the proposed unfiled modeling approach.     

How to model and implement connections between physical and virtual models for digital twin application

Digital twin (DT) is a virtual mirror (representation) of a physical world or a system along its lifecycle. As for a complex discrete manufacturing system (DMS), it is a digital model for emulating or reproducing the functions or actions of a real manufacturing system by giving the system simulation information or directly driven by a real system with proper connections between the DT model and the real-world system. It is a key building block for smart factory and manufacturing under the Industry 4.0 paradigm. The key research question is how to effectively create a DT model during the design stage of a complex manufacturing system and to make it usable throughout the system’s lifecycle such as the production stage. Given that there are some existing discussions on DT framework development, this paper focuses on the modeling methods for rapidly creating a virtual model and the connection implementation mechanism between a physical world production system at a workshop level and its mirrored virtual model. To reach above goals, in this paper, the discrete event system (DES) modeling theory is applied to the three-dimension DT model. First, for formally representing a manufacturing system and creating its virtual model, seven basic elements: controller, executor, processor, buffer, flowing entity, virtual service node and logistics path of a DMS have been identified and the concept of the logistics path network and the service cell is introduced to uniformly describe a manufacturing system. Second, for implementing interconnection and interaction, a new interconnection and data interaction mechanism between the physical system and its virtual model for through-life applications has been designed. With them, each service cell consists of seven elements and encapsulates input/output information and control logic. All the discrete cells are constructed and mapped onto different production-process-oriented digital manufacturing modules by integrating logical, geometric and data models. As a result, the virtual-physical connection is realized to form a DT model. The proposed virtual modeling method and the associated connection mechanism have been applied to a real-world workshop DT to demonstrate its practicality and usefulness.     

Conceptual digital twin modeling based on an integrated five-dimensional framework and TRIZ function model

Digital twin represents a fusion of the informational and physical domains, to bridge the material and virtual worlds. Existing methods of digital twin modeling are mainly based on modular representation, which limits guidance of the modeling process. Such methods do not consider the components or operational rules of the digital twin in detail, thereby preventing designers from applying these methods in their fields. With the increasing application of digital twin to various engineering fields, an effective method of modeling a multi-dimensional digital twin at the conceptual level is required. To such an end, this paper presents a method for the conceptual modeling of a digital twin based on a five-dimensional digital twin framework to represent the complex relationship between digital twin objects and their attributes. The proposed method was used to model the digital twin of an intelligent vehicle at the concept level.     

智能制造下产品数字孪生体全生命周期研究

针对信息物理融合系统在智能制造领域中的应用新范式,提出了产品数字孪生体全生命周期的理论框架.数字孪生的出现为信息物理融合理念的实现提供可行的思路和途径.从数字孪生概念的发展背景出发,分别从物理对象和物理对象的发展过程分析数字孪生和数字孪生体的定义,在此基础上进一步分析了数字孪生体全生命周期的内涵和特征.数字孪生体全生命...     

Digital twin for cutting tool: Modeling,application and service strategy

Developments in the internet technology, internet of things, cloud computing, big data, and artificial intelligence in recent years have brought significant advancements in manufacturing, among which manufacturing digitalization contributes greatly to the ever-increasing productivity. A cutting tool driven by the digital twin can provide modern solution to these ever-growing needs of digitalization. In this paper, the digital twin driven-data flow framework at every state of the cutting tool life cycle is proposed in order to ensure the possibility for continuous improvement of process and tool. The detailed digital twin-driven services are discussed, and there are two service modes for manufacturers to meet customer needs. Furthermore, a virtual cutting tool test platform fused with physical tool wear data and virtue tool wear data, which provides a promising guidance for the development of intelligence manufacturing in future. The development prospects and challenges of data analysis, fusion, mining, and service are also discussed.     

数字孪生与生产线仿真技术研究

随着新一代信息技术与制造技术的深度融合,仿真技术正向着信息系统与物理系统深度融合和高效协同的方向发展,应运而生的数字孪生技术成为近年来的新兴研究热点.为探索采用新一代信息技术促进离散制造行业数字化转型升级,从仿真技术的发展脉络和应用场景入手,引入基于数字孪生技术开展生产线仿真分析的研究,介绍了数字孪生技术的概念和内涵,...     

基于数字孪生的雕刻机人机交互系统设计

针对雕刻机应用过程中的实时监测困难,数据呈现单一,成本较高等问题,设计了一套基于数字孪生的雕刻机人机交互系统;首先使用SolidWorks软件设计与实际雕刻机高度匹配的三维孪生模型,随后根据实际系统的运动学模型建立Simulink仿真并编写控制算法控制三维孪生模型的运动,完成虚拟调试功能,最后将三维孪生模型与雕刻机结合,使模型根据实际雕刻机运行得到的实时数据完成设备状态监测功能;实验结果表明,文章所设计的雕刻机人机交互系统具有较高的实时性和精确度,能够保证良好的交互性与虚实结合性,有效提高监控效率,降低故障发生率,在工业现场具有广泛的应用价值.     

数字孪生驱动的火箭控制系统故障诊断研究综述

在第四次工业革命中,智能制造成为各国工业发展的重点方向,数字孪生技术作为一项新兴技术,能够有效实现物理信息的融合;将其应用于火箭控制系统的故障诊断和健康管理,能够进一步提高故障诊断的事前准确性,提升火箭发射的可靠性;本文对数字孪生技术在航天领域的研究现状进行归纳整理;首先梳理了NASA的数字孪生目标,国内领域按照设计、生产、支持服务阶段对数字孪生应用进行分类;其次,按照故障树、专家系统、神经网络、数据驱动的方法阐述控制系统故障诊断的研究现状;在介绍数字孪生驱动的健康管理方法的基础上,提出数字孪生驱动的火箭控制系统的故障诊断方法;详细介绍其基本组成框架,分析关键技术及应用难点,并提出数字孪生健康管理平台的基本流程;该方法预期实现火箭控制系统的事前诊断和维修策略的制定