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.     

Review of digital twin about concepts,technologies, and industrial applications

Various kinds of engineering software and digitalized equipment are widely applied through the lifecycle of industrial products. As a result, massive data of different types are being produced. However, these data are hysteretic and isolated from each other, leading to low efficiency and low utilization of these valuable data. Simulation based on theoretical and static model has been a conventional and powerful tool for the verification, validation, and optimization of a system in its early planning stage, but no attention is paid to the simulation application during system run-time. With the development of new-generation information and digitalization technologies, more data can be collected, and it is time to find a way for the deep application of all these data. As a result, the concept of digital twin has aroused much concern and is developing rapidly. Dispute and discussions around concepts, paradigms, frameworks, applications, and technologies of digital twin are on the rise both in academic and industrial communities. After a complete search of several databases and careful selection according to the proposed criteria, 240 academic publications about digital twin are identified and classified. This paper conducts a comprehensive and in-depth review of these literatures to analyze digital twin from the perspective of concepts, technologies, and industrial applications. Research status, evolution of the concept, key enabling technologies of three aspects, and fifteen kinds of industrial applications in respective lifecycle phase are demonstrated in detail. Based on this, observations and future work recommendations for digital twin research are presented in the form of different lifecycle phases.     

Crusta: A new virtual globe for real-time visualization of sub-meter digital topography at planetary scales

Virtual globes are becoming ubiquitous in the visualization of planetary bodies and Earth specifically. While many of the current virtual globes have proven to be quite useful for remote geologic investigation, they were never designed for the purpose of serving as virtual geologic instruments. Their shortcomings have become more obvious as earth scientists struggle to visualize recently released digital elevation models of very high spatial resolution (0.5-1 m²/sample) and extent (>2000 km²). We developed Crusta as an alternative virtual globe that allows users to easily visualize their custom imagery and more importantly their custom topography. Crusta represents the globe as a 30-sided polyhedron to avoid distortion of the display, in particular the singularities at the poles characteristic of other projections. This polyhedron defines 30 “base patches,” each being a four-sided region that can be subdivided to an arbitrarily fine grid on the surface of the globe to accommodate input data of arbitrary resolution, from global (BlueMarble) to local (tripod LiDAR), all in the same visualization. We designed Crusta to be dynamic with the shading of the terrain surface computed on-the-fly when a user manipulates his point-of-view. In a similarly interactive fashion the globe's surface can be exaggerated vertically. The combination of the two effects greatly improves the perception of shape. A convenient pre-processing tool based on the GDAL library facilitates importing a number of data formats into the Crusta-specific multi-scale hierarchies that enable interactive visualization on a range of platforms from laptops to immersive geowalls and caves. The main scientific user community for Crusta is earth scientists, and their needs have been driving the development.     

Secure sharing of big digital twin data for smart manufacturing based on blockchain

With the rapid development of digital twin technology, a large amount of digital twin data named as big digital twin data (BDTD), is generated in the lifecycle of equipment, which is supposed to be used in digital twin enabled applications. However, in the implementation of these applications, data sharing problem which is caused by the lack of data security as well as trust among stakeholders of equipment, limits data using value. It is a novel way to introduce blockchain technology into digital twin to solve the problem. However, current methods cannot fulfill the requirements of exponential growth and timely sharing of BDTD. Therefore, a blockchain-based framework for secure sharing of BDTD is proposed to solve the problems. Cloud storage is integrated into the framework, with which, BDTD is encrypted and stored in Cloud, while the hash of BDTD and transaction records are stored in blockchain. Some rules of generating new block are designed to improve the processing speed of blockchain. An algorithm for optimal sampling rate selection is presented to maximize total social benefits of the participants of BDTD sharing. Simulation results show that the algorithm is better than traditional method for maximizing the total social benefits. Furthermore, a protype system is developed and evaluated based on Fabric test network. Evaluation results show that BDTD can be shared securely multiple times per second through the framework, which demonstrates the feasibility of the framework in supporting timely sharing of BDTD.     

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.     

在建大型水利工程数字孪生平台实践与思考

为整体提升在建水利工程智慧化管理能力，通过数字孪生平台建设，赋能建设期工程施工管理、运行期业务应用。在已建信息化系统的基础上，结合数字孪生水利工程建设要求和目标，构建引江济淮工程数字孪生平台总体架构。围绕数据底板、模型平台、知识平台 3 个方面，搭建真实、全面、准确的水利及水运多领域数据底板，为工程数字化映射、智能化应用提供准确的数据资源；搭建感知、预测、调度、控制、评价功能的模型平台，覆盖中长期、短期、实时多尺度调度需求，以及常规、应急多目标调度场景；搭建以方案库和专家经验库为主的知识平台，将静态、动态知识共同融入“四预”全流程；按照工程建设、运行调度、工程维护等管理业务需求，建设水资源调度、航运调度、工程安全监控等业务系统，为更加合理、有序地推进数字孪生水利工程后续建设提供思路。     

A generic approach of integrating 3D models into virtual manufacturing

Various 3D modeling software has been developed for design and manufacturing.Most of the commercially available software uses native file formats,which may not be able to be read or understood by other software.This paper deals with the development of a generic approach of a 3D model conversion program for virtual manufacturing(VM),using a lexical analyzer generator Lex and the Open Graphic Library(OpenGL).The program is able to convert 3D mesh data between four universal file formats,i.e.,Stereolithography(STL),Virtual Reality Modeling Language(VRML),eXtensible Markup Language(XML),and Object(OBJ).Simple assembly functions can be applied to the imported models.The quaternion angle is used for object rotation to overcome the problem of gimbal lock or a loss of one degree of rotational freedom.The program has been validated by importing the neutral format models into the program,applying the transformation,saving the new models with a new coordinate system,and lastly exporting into other commercial software.The results showed that the program is able to render and re-arrange accurately the geometry data from the different universal file formats and that it can be used in VM.Therefore,the output models from a VM system can be transferred or imported to another VM system in a universal file format.     

Impact of multimodal feedback on simulated ergonomic measurements in a virtual environment: A case study with manufacturing workers

The purpose of this study was to evaluate the impact of multimodal feedback on ergonomic measurements in a virtual environment (VE) for a typical simulated drilling task. In total, sixty male manufacturing industry workers were divided into five groups. One group performed the working task in a real environment (RE), and ergonomic measurements for this group were used as the baseline for evaluation. The other four groups performed the same task in a virtual environment with different feedback treatments (visual with or without auditory and/or tactile feedback). Five indices – task completion time, maximum force capacity reduction, body part discomfort, rated perceived exertion, and rated task difficulty – were used to evaluate the measurements of each of the four treatments in VE in comparison to the baseline group in RE. The results indicate that the five indices for each of the four treatment groups were significantly higher than those of the RE group. Moreover, the indices of the visual‐only group were significantly higher than those of the other three groups with auditory and/or tactile feedback treatments. The findings of this study can provide a guideline for ergonomic evaluations of work designs in VE and for establishing a virtual reality simulation system. © 2011 Wiley Periodicals, Inc.     

Applications of virtual reality in maintenance during the industrial product lifecycle: A systematic review

As a state-of-the-art computer technology, virtual reality (VR) is considered to play an important role in helping manufacturing companies stay competitive in the international market. However, despite the achievements made in the field of VR, it is still an emerging technology that lacks deeper exploration and development in industrial application scenarios, especially in the coming fourth industrial revolution (Industry 4.0). This paper aims to systematically investigate the applications of VR in industrial maintenance to discover evidence of its values, limitations, and future directions so that VR can be guided to better serve manufacturing enterprises in remaining competitive in the coming Industry 4.0. A systematic literature review (SLR) methodology is adopted to review primary studies on this topic, by which 86 studies are ultimately included. The results show that VR has proved its value in benefiting maintenance issues through the product lifecycle. However, VR is still not an indispensable element for the lifecycle management of products regarding maintenance-related issues. Several key findings are concluded based on the analysis of the 86 studies. This review is valuable for researchers who are interested in the application of VR technology in maintainability design, maintenance training or maintenance task assistance.     

A review of digital twin in product design and development

In the era of digitalization, there are many emerging technologies, such as the Internet of Things (IoT), Digital Twin (DT), Cloud Computing and Artificial Intelligence (AI), which are quickly developped and used in product design and development. Among those technologies, DT is one promising technology which has been widely used in different industries, especially manufacturing, to monitor the performance, optimize the progresses, simulate the results and predict the potential errors. DT also plays various roles within the whole product lifecycle from design, manufacturing, delivery, use and end-of-life. With the growing demands of individualized products and implementation of Industry 4.0, DT can provide an effective solution for future product design, development and innovation. This paper aims to figure out the current states of DT research focusing on product design and development through summarizing typical industrial cases. Challenges and potential applications of DT in product design and development are also discussed to inspire future studies.     

融合GA优化算法的数字孪生模型在石油旋转机械诊断中的应用

为根据模态信号频率水平确定石油旋转机械当前故障行为所属类别,实现对机械设备故障行为的准确诊断,针对融合GA优化算法的数字孪生模型在石油旋转机械诊断中的应用展开研究。定义GA算法优化规则,并在此基础上,建立数字孪生模型,再联合相关故障行为数据,完成对石油旋转机械运行数据的聚类运算,实现基于数字孪生模型的石油旋转机械运行数据聚类处理。计算运行数据损失情况,通过模态分解描述性样本的方式,将核心诊断信息重新耦合在一起,联合求解所得的超参数指标,定义具体的数据样本集中训练模式,实现对石油旋转机械的诊断。实验结果表明,上述诊断方法的应用,对于每一类故障行为模态信号频率的诊断都属于该信号的标准频率数值区段之内,符合100%精准诊断机械故障行为的应用需求,在准确诊断石油旋转机械故障行为方面的可行性能力较为突出。     

Visualizing and analyzing dynamic meteorological data with virtual globes: A case study of tropical cyclones

Visualization is an important component of the evaluation of meteorological models, forecasting research, and other applications. With advances in computing power, the volume of meteorological data generated by geoscience and climate researchers has been steadily increasing. The emerging technique of virtual globes has been regarded as an ideal platform for visualizing larger geospatial data over the Internet. To visualize and analyze meteorological data with the new virtual globes, this paper proposes a systematic meteorological data visualization (MDV) framework in World Wind, an open-source virtual globe. The key technologies, including a hierarchical octree-based multiresolution data organization, data scheduling, level of detail (LOD) and rendering are described in detail. The framework is then applied to a practical tropical cyclone simulation, including flow vectors, particle tracking, cross-sectional analysis, streamlines, pathway animation, and volume rendering. The results show that virtual globes are effective tools for meteorological data visualization and analysis.     

Flexible multivariate marginal models for analyzing multivariate longitudinal data,with applications in R

Most of the available multivariate statistical models dictate on fitting different parameters for the covariate effects on each multiple responses. This might be unnecessary and inefficient for some cases. In this article, we propose a modelling framework for multivariate marginal models to analyze multivariate longitudinal data which provides flexible model building strategies. We show that the model handles several response families such as binomial, count and continuous. We illustrate the model on the Kenya Morbidity data set. A simulation study is conducted to examine the parameter estimates. An R package mmm2 is proposed to fit the model.     

A digital mock-up visualization system capable of processing giga-scale CAD models

In the automotive, aerospace and naval industries, digital mock-up tools are always used for assembly examination, layout examination and interference checking. Generally, a digital mock-up is assembled from giga-scale CAD models. Because of limitations of computer hardware resources, a digital mock-up represented by traditional planar facets is too large to load into a computer’s memory for rendering. This article proposes a new geometric compression representation to represent given CAD models with curved triangular patches. Based on the compression representation, our digital mock-up visualization system can import several giga-scale CAD models into a computer’s memory simultaneously. A high performance rendering strategy to display the curved triangular patches is also presented. In the rendering strategy, a dynamic subdivision algorithm is introduced which is different from conventional LOD techniques in order to reduce memory consumption. In addition, an algorithm to convert CAD models to the curved triangular patches is introduced.     

A digital twin in transportation: Real-time synergy of traffic data streams and simulation for virtualizing motorway dynamics

The introduction of digital twins is expected to fundamentally change the technology in transportation systems, as they appear to be a compelling concept for monitoring the entire life cycle of the transport system. The advent of widespread information technology, particularly the availability of real-time traffic data, provides the foundation for supplementing predominated (offline) microscopic simulation approaches with actual data to create a detailed real-time digital representation of the physical traffic. However, the use of actual traffic data in real-time motorway analysis has not yet been explored. The reason is that there are no supporting models and the applicability of real-time data in the context of microscopic simulations has yet to be recognized. Thus, this article focuses on microscopic motorway simulation with real-time data integration during system run-time. As a result, we propose a novel paradigm in motorway traffic modeling and demonstrate it using the continuously synchronized digital twin model of the Geneva motorway (DT-GM). We analyze the application of the microscopic simulator SUMO in modeling and simulating on-the-fly synchronized digital replicas of real traffic by leveraging fine-grained actual traffic data streams from motorway traffic counters as input to DT-GM. Thus, the detailed methodological process of developing DT-GM is presented, highlighting the calibration features of SUMO that enable (dynamic) continuous calibration of running simulation scenarios. By doing so, the actual traffic data are directly fused into the running DT-GM every minute so that DT-GM is continuously calibrated as the physical equivalent changes. Accordingly, DT-GM raises a technology dimension in motorway traffic simulation to the next level by enabling simulation-based control optimization during system run-time that was previously unattainable. It, thus, forms the foundation for further evolution of real-time predictive analytics as support for safety–critical decisions in traffic management. Simulation results provide a solid basis for the future real-time analysis of an extended Swiss motorway network.     

Self-efficacy and anxiety of digital natives in face of compulsory computer-mediated tasks: A study about digital capabilities and limitations

Digital limitations (or, conversely, digital capabilities) are a new way to frame the digital divide discourse in three dimensions: access, cognition and behavior. Digital limitations address an individual's barriers to properly access the information and communication technologies (ICTs), as well as his/her cognitive disabilities and negative behaviors towards ICT use effectiveness. In a survey with 174 undergraduate students in a traditional state university in underdeveloped Northeastern Brazil who compulsorily use an institutional ICT-based academic system, we investigated the factorial structure and the relationship of two constructs that pertain to the cognitive dimension of digital limitations – computer self-efficacy and anxiety. Our findings address the negative correlation between the two constructs and the unanticipated proposition that both low and high levels of self-efficacy and anxiety do not signal per se the presence of cognitive digital limitations or capabilities.     

A review on charging behavior of electric vehicles: data, model, and control

The adoption and usage of electric vehicles (EVs) have emerged recently due to the increasing concerns on the greenhouse gas issues and energy revolution. As a part of the smart grid, EVs can provide valuable ancillary services beyond consumers of electricity. However, EVs are gradually considered as nonnegligible loads due to their increasing penetration, which may result in negative effects such as voltage deviations, lines saturation, and power losses. Relationship and interaction among EVs, charging stations, and micro grid have to be considered in the next generation of smart grid. Therefore, the topic of smart charging has been the focus of many works where a wide range of control methods have been developed. As one of the bases of simulation, the EV charging behavior and characteristics have also become the focus of many studies. In this work, we review the charging behavior of EVs from the aspects of data, model, and control. We provide the links for most of the data sets reviewed in this work, based on which interested researchers can easily access these data for further investigation.     

The benefit of being physically present: A survey of experimental works comparing copresent robots,telepresent robots and virtual agents

The effects of physical embodiment and physical presence were explored through a survey of 33 experimental works comparing how people interacted with physical robots and virtual agents. A qualitative assessment of the direction of quantitative effects demonstrated that robots were more persuasive and perceived more positively when physically present in a user׳s environment than when digitally-displayed on a screen either as a video feed of the same robot or as a virtual character analog; robots also led to better user performance when they were collocated as opposed to shown via video on a screen. However, participants did not respond differently to physical robots and virtual agents when both were displayed digitally on a screen – suggesting that physical presence, rather than physical embodiment, characterizes people׳s responses to social robots. Implications for understanding psychological response to physical and virtual agents and for methodological design are discussed.     

State of the art in big data applications in microgrid: A review

The prospering Big data era is emerging in the power grid. Multiple world-wide studies are emphasizing the big data applications in the microgrid due to the huge amount of produced data. Big data analytics can impact the design and applications towards safer, better, more profitable, and effective power grid. This paper presents the recognition and challenges of the big data and the microgrid. The construction of big data analytics is introduced. The data sources, big data opportunities, and enhancement areas in the microgrid like stability improvement, asset management, renewable energy prediction, and decision-making support are summarized. Diverse case studies are presented including different planning, operation control, decision making, load forecasting, data attacks detection, and maintenance aspects of the microgrid. Finally, the open challenges of big data in the microgrid are discussed.