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-based industrial cloud robotics: Framework,control approach and implementation

Industrial cloud robotics (ICR) integrates cloud computing with industrial robots (IRs). The capabilities of industrial robots can be encapsulated as cloud services and used for ubiquitous manufacturing. Currently, the digital models for process simulation, path simulation, etc. are encapsulated as cloud services. The digital models in the cloud may not reflect the real state of the physical robotic manufacturing systems due to inaccurate or delayed condition update and therefore result in inaccurate simulation and robotic control. Digital twin can be used to realize fine sensing control of the physical manufacturing systems by a combination of high-fidelity digital model and sensory data. In this paper, we propose a framework of digital twin-based industrial cloud robotics (DTICR) for industrial robotic control and its key methodologies. The DTICR is divided into physical IR, digital IR, robotic control services, and digital twin data. First, the robotic control capabilities are encapsulated as Robot Control as-a-Service (RCaaS) based on manufacturing features and feature-level robotic capability model. Then the available RCaaSs are ranked and parsed. After manufacturing process simulation with digital IR models, RCaaSs are mapped to physical robots for robotic control. The digital IR models are connected to the physical robots and updated by sensory data. A case is implemented to demonstrate the workflow of DTICR. The results show that DTICR is capable to synchronize and merge digital IRs and physical IRs effectively. The bidirectional interaction between digital IRs and physical IRs enables fine sensing control of IRs. The proposed DTICR is also flexible and extensible by using ontology models.     

面向飞行器结构健康管理的数字孪生及应用研究综述

数字孪生一词起源于美国国防部对飞行器机体数字孪生的研究,目前已经成为全球制造业的前沿热点领域.解析了数字孪生的概念及其中的结构健康管理元素,提出了包含生命周期维、仿真精度维、智能程度维的数字孪生成熟度模型;梳理了面向结构健康管理的数字孪生关键技术,特别是4项关键的数字工程技术能力,包括多尺度建模、多物理特性建模、模型与...     

Implementation path and reference framework for Industrial Internet Platform (IIP) in product service system using industrial practice investigation method

With the development of intelligent sensing, edge computing, fog computing, cloud computing, parallel computing, smart grid, big data, block chain, 5G, cyber-physical systems, digital twins, machine learning and other technologies, the industrial internet has undergone control network stage, sensor network stage, internet stage, Internet of Things (IoT) stage, Industrial Internet of Things (IIoT) stage, and Industrial Internet (II) stage, etc. In the existing research, scholars focus on a local dot, such as: technology, function, elements and application based on industrial internet. However, there is a lack of an overall framework to study the top-level planning of Industrial Internet Platform (IIP) from a systematic perspective. On the other hand, there are few studies on the detailed path and steps for implementing IIP in a specific enterprise in a specific industry. The objective of this paper is to study a reference framework and industrial implementation path for IIP in product service system using industrial practice investigation method, which meets the needs of industry on the basis of existing theory and industrial practice, and to provide reference for government and industry planning, design, implementation and promotion of IIP. In addition, the proposed reference framework and industrial implementation for IIP in product service system can enhance the core value of the enterprise and increase benefits.     

面向数字孪生流域的云网融合架构研究

数字孪生流域建设是智慧水利建设的重要标志,是推动流域水利高质量发展的必然要求。为了应对当前数字孪生流域建设过程中面临的流域物联感知能力、通信传输网络资源、模型算法仿真计算水平等方面的不足而产生的挑战,本文结合云网融合的云网协同、按需互联、敏捷智能的服务能力特性,基于云网融合层次化的设计思想,把流域云和网充分融合,有效调度并应用计算、通信、存储等基础设施资源,提出了面向数字孪生流域的云网融合逻辑架构,梳理并阐述了水利感知网云网融合服务实现、水利信息网云网融合服务实现、数字孪生平台算力服务实现等可应用于数字孪生流域建设的云网融合服务架构,总结分析了面向数字孪生流域的云网融合关键技术。研究对充分发挥新一代信息技术对数字孪生流域建设的支撑驱动作用具有重要参考意义。     

Digital twins for automotive development: Two wheelers application

Shortening product lifecycles and increasing customer demands are forcing manufacturers to increase the efficiency and effectiveness of their product development process to stay competitive in an increasingly global setting. The effectiveness of current day product development is hampered by the availability of real-world data that allows the deduction of comprehensive customer requirements. Key to solving this is a tight connection between the manufacturer and the vehicle in-use. Founded by technological advances put forward by Industry 4.0, the digital twin provides the tools needed to strengthen this connection. Driven by the difficulties automotive manufacturers face in generating insights in customer usage of the vehicle, the present work develops a general digital twin framework for the automotive industry, characterizing the digital twin as a holistic representation of a physical vehicle with the appropriate fidelity throughout its lifecycle. Further highlighting that this holistic portrayal requires models which depict the human interaction with the vehicle. To illustrate this, a digital twin model capable of capturing human interaction with automotive products, more specifically motorcycles, is presented. Data generated by this digital twin model provides a data-based foundation for the development of customer requirements, increasing the effectiveness of next-generation vehicle development.     

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.     

端边云协同的PID整定智能系统

本文在分析智能制造对PID整定的新需求及PID整定面临的挑战难题的基础上,将自动化的建模、控制与优化和人工智能的深度学习与强化学习深度融合与协同,提出了自适应与自主的PID整定的智能优化方法,包括端边云协同的PID控制过程数字孪生模型和强化学习与数字孪生模型相结合的PID整定算法.将工业互联网的端边云协同技术与PLC控制系统相结合,研制了PID整定智能系统,并在重大耗能设备—电熔镁炉成功应用.该系统安全、可靠与优化运行,取得显著的节能减排效果.最后,提出了控制系统智能化研究方向需要进一步深入研究的内容.     

A design method for an intelligent manufacturing and service system for rehabilitation assistive devices and special groups

The maturity of Industrial 4.0 technologies (smart wearable sensors, Internet of things [IoT], cloud computing, etc.) has facilitated the iteration and digitization of rehabilitation assistive devices (RADs) and the innovative development of intelligent manufacturing systems of RADs, expanding the value-added component of smart healthcare services. The intelligent manufacturing service mode, based on the concept of the product life cycle, completes the multi-source data production process analysis and the optimization of manufacturing, operation, and maintenance through intelligent industrial Internet of things and other means and improves the product life cycle management and operation mechanism. The smart product-service system (PSS) realizes the value-added of products by providing users with personalized products and value-added services, service efficiency, and sustainable development and gradually forms an Internet-product-service ecosystem. However, research on the PSS of RADs for special populations is relatively limited. Thus, this paper provides an overview of an IoT-based production model for RADs and a smart PSS-based development method of multimodal healthcare value-added services for special people. Taking the hand rehabilitation training devices for autistic children as a case, this paper verifies the effectiveness and availability of the proposed method. Compared with the traditional framework, the method used in this paper primarily helps evaluate rehabilitation efficacy, personalizes schemes for patients, provides auxiliary intelligent manufacturing service data and digital rehabilitation data for RAD manufacturers, and optimizes the product iteration development procedures by combining user-centered product interaction, multimodal evaluation, and value-added design. This study incorporates the iterative design of RADs into the process of smart PSS to provide some guidance to the RADs design manufacturers.     

Industrial Internet Platform (IIP) enabled Smart Product Lifecycle-Service System (SPLSS) for manufacturing model transformation: From an industrial practice survey

Nowadays, the focus of enterprises is gradually expanding from product manufacturing system to Product service system (PSS). In the existing research, scholars mainly focus on the in-depth study of a certain method or technology, and the research on traditional PSS is relatively mature. In addition, it is a tendency that transform towards SPLSS with the characteristics of industrial internet platform (IIP) and sustainable operation theory. Based on this, this paper explores the research path from traditional product service system (PSS) to smart product service system (SPSS), and then to smart product lifecycle service system (SPLSS), which can endow the products with intelligent perception, intelligent analysis and intelligent decision-making capabilities based on Industrial Internet Platform (IIP). A reference model of IIP enabled SPLSS for industrial services based on system engineering method and theory from a very detailed practical investigation is proposed. Moreover, on the basis of this model, its three dimensional subsystems are expanded, including: supporting environment subsystem, evolution path subsystem, and added value subsystem. The study can provide a reference for the enterprise's manufacturing strategy and manufacturing path. It will promote the transformation and upgrading of enterprise manufacturing model to improve service efficiency and reduce operating costs, and then realize the value-added of products and services.     

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,...     

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.     

航天产品性能样机建模与仿真综合集成平台

为了提高航天产品性能样机建模与仿真协同工作水平,针对性能样机全生命周期协同建模与仿真过程中管理系统综合集成性差的问题,构建基于云计算平台的性能样机综合集成协同建设与仿真平台。重点研究性能样机协同建模与仿真平台数据库建模与设计、复杂航天产品性能样机综合集成建模与仿真平台框架、性能样机协同建模与仿真平台基础框架、性能样机制造云服务平台架构和系统物理平台架构。应用结果表明,所构建的平台较好地解决了性能样机全生命周期统一建模与仿真以及不同人员、不同工具、不同算法、不同描述语言下的耦合建模、联合仿真问题。      

A digital twin-enhanced system for engineering product family design and optimization

Engineering product family design and optimization in complex environments has been a major bottleneck in today’s industrial transformation towards smart manufacturing. Digital twin (DT), as a core part of cyber-physical system (CPS), can provide decision support to enhance engineering product lifecycle management workflows via remote monitoring and control, high-fidelity simulation, and solution generation functionalities. Although many studies have proven DT to be highly suited for industry needs, little has been reported on the product family design and optimization capabilities specifically with context awareness, which could be leaving many enterprises ambivalent on its adoption. To fill this gap, a reusable and transparent DT capable of situational recognition and self-correction is essentially required. This paper develops a generic DT architecture reference model to enable the context-aware product family design optimization process in a cost-effective manner. A case study featuring asset re-/configuration within a dynamic environment is further described to demonstrate its in-context decision-aiding capabilities. The authors hope this study can provide valuable insights to both academia and industry in improving their engineering product family management process.     

Feature-based modeling for industrial processes in the context of digital twins: A case study of HVOF process

Industrial process modeling is currently undergoing a fundamental transformation, leading towards interconnected close-loop twins of models, i.e., the parametrically-controlled real-world physics model, and its corresponding digitalized virtual system model. Between these models, a highly time-sensitive mutual validation mechanism and a coherent and consistent control strategy are applied, which demand complex virtual-and-real world model-based information mapping and synchronization. Thus, this research proposes a semantic conceptual framework for industrial process modeling in the context of digital twins. Based on a hierarchical structure of digital twins, this framework modularizes the modeling process in terms of the semantic information modules of physics in the real-world phenomena, and clarifies inter-module associations and near-real-time data transmission coupled with virtual analysis in CAE environment so that the time-sensitive phenomenon information objects distributed on virtually-separated sub-level physics models can be supported for representing the real-world process comprehensively. Advanced feature concept is adopted to construct the digital models as the basic compositions of any virtual industrial process. The related feature definitions are extended in this work so that the common characteristics in the concept of digital twins could be generically and concisely represented. To validate the modeling method, the digital model of a prototyped High-velocity Oxygen-fuel (HVOF) coating process system was constructed as the case study. The data from the nozzle trajectory, the flame, and the in-flight particle behavior, and the transient thermal performance of the coating layer and substrate were synchronously incorporated for simulating the transient phenomena of the substrate component temperature and coating thickness distribution on the substrate surface. The final simulation result validates that the feature-based digital model is able to comprehensively reflect the real-world scenario on the virtual side. To illustrate how the developed model provides meaningful feedback to the real-world control, a general digital twin setup of the model is given at the end of the case study.     

Bi-level dynamic scheduling architecture based on service unit digital twin agents

Pure reactive scheduling is one of the core technologies to solve the complex dynamic disturbance factors in real-time. The emergence of CPS, digital twin, cloud computing, big data and other new technologies based on the industrial Internet enables information acquisition and pure reactive scheduling more practical to some extent. However, how to build a new architecture to solve the problems which traditional dynamic scheduling methods cannot solve becomes a new research challenge. Therefore, this paper designs a new bi-level distributed dynamic workshop scheduling architecture, which is based on the workshop digital twin scheduling agent and multiple service unit digital twin scheduling agents.Within this architecture, scheduling a physical workshop is decomposed to the whole workshop scheduling in the first level and its service unit scheduling in the second level. On the first level, the whole workshop scheduling is executed by its virtual workshop coordination (scheduling) agent embedded with the workshop digital twin consisting of multi-service unit digital twins. On the second level, each service unit scheduling coordinated by the first level scheduling is executed in a distributed way by the corresponding service unit scheduling agent associated with its service unit digital twin. The benefits of the new architecture include (1) if a dynamic scheduling only requires a single service unit scheduling, it will then be performed in the corresponding service unit scheduling without involving other service units, which will make the scheduling locally, simply and robustly. (2) when a dynamic scheduling requires changes in multiple service units in a coordinated way, the first level scheduling will be executed and then coordinate the second level service unit scheduling accordingly. This divide-and-then-conquer strategy will make the scheduling easier and practical.The proposed architecture has been tested to illustrate its feasibility and practicality.     

A survey of feature modeling methods: Historical evolution and new development

Initially developed for geometric representation, feature modeling has been applied in product design and manufacturing with great success. With the growth of computer-aided engineering (CAE), computer-aided process planning (CAPP), computer-aided manufacturing (CAM), and other applications for product engineering, the definitions of features have been mostly application-driven. This survey briefly reviews feature modeling historical evolution first. Subsequently, various approaches to resolving the interoperability issues during product lifecycle management are reviewed. In view of the recent progress of emerging technologies, such as Internet of Things (IoT), big data, social manufacturing, and additive manufacturing (AM), the focus of this survey is on the state of the art application of features in the emerging research fields. The interactions among these trending techniques constitute the socio-cyber-physical system (SCPS)-based manufacturing which demands for feature interoperability across heterogeneous domains. Future efforts required to extend feature capability in SCPS-based manufacturing system modeling are discussed at the end of this survey.     

A multi-agent and cloud-edge orchestration framework of digital twin for distributed production control

The demands for mass individualization and networked collaborative manufacturing are increasing, bringing significant challenges to effectively organizing idle distributed manufacturing resources. To improve production efficiency and applicability in the distributed manufacturing environment, this paper proposes a multi-agent and cloud-edge orchestration framework for production control. A multi-agent system is established both at the cloud and the edge to achieve the operation mechanism of cloud-edge orchestration. By leveraging Digital Twin (DT) technology and Industrial Internet of Things (IIoT), real-time status data of the distributed manufacturing resources are collected and processed to perform the decision-making and manufacturing execution by the corresponding agent with permission. Based on the generated data of distributed shop floors and factories, the cloud production line model is established to support the optimal configuration of the distributed idle manufacturing resources by applying a systematic evaluation method and digital twin technology, which reflects the actual manufacturing scenario of the whole production process. In addition, a rescheduling decision prediction model for distributed control adjustment on the cloud is developed, which is driven by Convolutional Neural Network (CNN) combined with Bi-directional Long Short-Term Memory (BiLSTM) and attention mechanism. A self-adaptive strategy that makes the real-time exceptions results available on the cloud production line for holistic rescheduling decisions is brought to make the distributed manufacturing resources intelligent enough to address the influences of different degrees of exceptions at the edge. The applicability and efficiency of the proposed framework are verified through a design case.