The introduction of Digital Twin (DT) technology has sparked interest in virtual replication of physical assets and processes. However, to fully capitalize on DT’s potential, we need robust and scalable frontend solutions. This study proposes an innovative approach to overcome the limitations of traditional monolithic frontend frameworks by leveraging micro-frontend technologies. Our goal is to enable seamless connectivity between DTs and develop tailored presentation layers by decomposing complex systems into modular web-based DTs. Additionally, our framework tackles the challenges posed by multi-vendor elements within DTs and facilitates service and virtual environment orchestration for seamless integration and operation, enabling real-time data exchange between virtual models and physical machinery. Insights from its implementation across various applications, including training, monitoring, and control, shed light on its advantages and limitations. This research aims to revolutionize DT creation and management by introducing a scalable and adaptable framework designed to enable Web 3D for Industry and Manufacturing. By integrating cutting-edge micro-frontend technologies, our approach seeks to enhance maintainability, efficiency, and productivity. However, potential limitations such as code duplication and app payload concerns must be acknowledged. Future research will address these limitations to broaden applicability and improve performance. Overall, our proposed framework offers promising solutions to many challenges in industrial settings, paving the way for more efficient and effective DT deployment and management.

Multi-user Augmented Reality experiences have proven useful in increasing user engagement and facilitating the learning of new concepts. Thanks to the new generation of Augmented Reality frameworks for smartphones and tablets, their daily use in the classroom is becoming more common. In this paper, we present the work done towards the implementation of classroom-based behavioural lessons based on collaborative Augmented Reality environments. We have developed a library that enables multi-user Augmented Reality applications and have used it to implement some scenarios developed in the context Positive Behaviour Intervention and Support framework.

In the future, museums may undergo a partial transformation where traditional tours are replaced by teleoperated tours, offering innovative museum experiences. This transition is made possible by technological advances in various domains such as Extended Reality (XR), media workflow management or positioning systems. However, there is still a lack of synergy between these technologies to create comprehensive and seamless experiences that enable professionals to remotely guide visitors or cater to multiple groups and individuals simultaneously. To address this gap, we propose a web-based architecture that combines the following research themes: (i) Accurate indoor localization systems for museum visits, with an emphasis in geofencing; (ii) Low-latency interactive audio and video workflow management between visitors and guides; (iii) Rich AR and VR interactions between visitors and guides as well as the visitors themselves.

In the context of Multidisciplinary Design Optimization (MDO), the use of data visualization and data analytics is critical for the understanding of complex interactions between variables and multi-objective functions in high-dimensional (>3) spaces. Current Visual Analytics (VA) techniques provide powerful interactive tools to analyze general-purpose data in many scientific and business contexts. However, the application of these methods in MDO contexts is less explored. Direct application of existing methods can easily overwhelm the user, mainly due to a) incorrect preprocessing of raw data, b) use of incorrect tools, or c) a combination of the aforementioned factors. To overcome these challenges, this manuscript aims to explore the application of some relevant 2D and 3D visualization techniques in the context of MDO. To achieve this goal, this manuscript presents some of the best state-of-the-art tools and discusses best practices for data processing. In addition, the tools presented are implemented in a client-server web environment where the heavy work (data preprocessing) is carried out by a Python-based server while the visualization tasks are left to the client. Ongoing work includes the integration and deployment of the presented methods in an interactive visualization framework for the analysis of MDO results.

The introduction of the Digital Twin (DT) has sparked a great deal of interest in the virtual replication of physical assets and processes. However, to fully realize the potential of DT, companies require robust and scalable front-end solutions. This study proposes harnessing micro-frontend technologies to surmount the limitations of monolithic front-end frameworks, thereby crafting effective presentation layers tailored for industrial companies. By decomposing complex and distributed systems into modular web-based DT, the proposed framework enables better scalability, synergy, and efficient application development. It also tackles the intricacies introduced by complex multi-vendor elements within DT and the orchestration of services and virtual environments. Research is focused on developing an architecture that facilitates seamless connectivity between multiple blocks of DT as well as interactivity and immersive experiences. Our study offers insights into our journey of implementing this framework for various industrial use cases, such as training, monitoring, and control, highlighting the benefits, drawbacks, and challenges. Ultimately, this research aims to accelerate the creation of DT, improve maintainability, and increase efficiency and productivity in industrial environments.

Multi-physical modeling combined with data-driven decision making is giving rise to a new paradigm, the "digital twin." The digital twin is a living digital model of a system or physical asset that continuously adapts to operational changes based on real-time data. When properly designed, a digital twin can help predict the future behavior of its corresponding physical counterpart. This paper presents a series of use cases that illustrate the role of a digital twin in different stages of the industrial product lifecycle. The use cases are implemented using 3D web technology for user interfaces and web standards (X3D and glTF) for data exchange between modules. The contribution of this work consists of a set of lessons learnt and some hints on future synergies between digital twin and 3D web technologies.

One of the main objectives of Industry 4.0 (I4.0) is to generate new opportunities based on the convergence of traditionally isolated technologies such as industrial control systems (ICSs) and information and communication technology (ICT). This presents new opportunities to take advantage of ICT technologies to develop new applications and services related to industrial processes. However, there are a variety of requirements and constraints that must be addressed for the attainment of this purpose. Moreover, the large amount of existing technologies and tools that can cope with these requirements makes the definition and selection of a solution a cumbersome task for traditional industrial workers with a non-ICT focused background. This chapter analyses and describes the main requirements and technologies required to provide a data-based Industry 4.0 solution.

In the context of generation of lubrication flows, gear pumps are widely used, with gerotor-type pumps being specially popular, given their low cost, high compactness, and reliability. The design process of gerotor pumps requires the simulation of the fluid dynamics phenomena that characterize the fluid displacement by the pump. Designers and researchers mainly rely on these methods: (i) computational fluid dynamics (CFD) and (ii) lumped parameter models. CFD methods are accurate in predicting the behavior of the pump, at the expense of large computing resources and time. On the other hand, Lumped Parameter models are fast and they do not require CFD software, at the expense of diminished accuracy. Usually, Lumped Parameter fluid simulation is mounted on specialized black-box visual programming platforms. The resulting pressures and flow rates are then fed to the design software. In response to the current status, this manuscript reports a virtual prototype to be used in the context of a Digital Twin tool. Our approach: (1) integrates pump design, fast approximate simulation, and result visualization processes, (2) does not require an external numerical solver platforms for the approximate model, (3) allows for the fast simulation of gerotor performance using sensor data to feed the simulation model, and (4) compares simulated data vs. imported gerotor operational data. Our results show good agreement between our prediction and CFD-based simulations of the actual pump. Future work is required in predicting rotor micro-movements and cavitation effects, as well as further integration of the physical pump with the software tool.

The once exclusive technology empowering immersive and interactive training systems is now more affordable and accessible to mainstream use cases. Its adoption in the manufacturing industry can help reshape training processes as an intrinsic part of production routines and reduce the mental resources required to complete a task. Current academic literature does not integrate components to describe the skills and attributes of workers with impairments. In contrast, the research in this paper addressed the design and evaluation of a new immersive and interactive training system that can effectively provide new human augmentation opportunities for workers with impairments by reducing the mental resources required to complete a task. Automated machine interpretation of tasks and actions of workers with impairments is still a long way off and one of the reasons is that individual skills are still difficult to describe formally. Therefore, in this paper, skill transfer is assessed through external evaluation. The results of the preliminary evaluation of our Cross Reality (XR) prototype for training and error minimization in the manufacturing of electrical cabinets confirmed significant productivity gains and high adoption by participants, validating the suitability of the solution for workers in industrial manufacturing processes.

The nature of industrial manufacturing processes and the need to learn and adapt production systems to new demands require new tools to cope with the vast amount of information being generated. This research aims to design, implement, and evaluate a process to streamline industrial assets to immersive environments and harness the interconnectivity of machines, processes, and products for more informed decision making. To evaluate the effectiveness of our solution, we compare it against existing solutions. A statistical test is used to corroborate our hypotheses, and the results of the usability test indicate well-perceived learnability.

Within the context of Industry 4.0, AREVA is presented: a Voice Assistant with Augmented Reality visualisations for the support and guidance of operators when carrying out tasks and processes in industrial environments. With the aim of validating its use for the training of new operators, first evaluations were performed by a group of non-expert users who were asked to carry out a maintenance task on a Universal Robot.

The nature of industrial manufacturing processes and the continuous need to adapt production systems to new demands require tools to support workers during transitions to new processes. At the early stage of transitions, human error rate is often high and the impact in quality and production loss can be significant. Over the past years, eXtended Reality (XR) technologies (such as virtual, augmented, immersive, and mixed reality) have become a popular approach to enhance operators' capabilities in the Industry 4.0 paradigm. The purpose of this research is to explore the usability of dialogue-based XR enhancement to ease the cognitive burden associated with manufacturing tasks, through the augmentation of linked multi-modal information available to support operators. The proposed Interactive XR architecture, using the Spoken Dialogue Systems' modular and user-centred architecture as a basis, was tested in two use case scenarios: the maintenance of a robotic gripper and as a shop-floor assistant for electric panel assembly. In both cases, we have confirmed a high user acceptance rate with an efficient knowledge communication and distribution even for operators without prior experience or with cognitive impairments, therefore demonstrating the suitability of the solution for assisting human workers in industrial manufacturing processes. The results endorse an initial validation of the Interactive XR architecture to achieve a multi-device and user-friendly experience to solve industrial processes, which is flexible enough to encompass multiple tasks.

As cloud technology gains traction as a platform in the architecture, engineering, and construction (AEC) sector, so does the adoption of Web3D technologies for the visualisation of massive 3D models. However, the interaction with highly complex CAD models typical of these sectors is still critical. Various efforts are found in the literature to create suitable transmission formats that do not require users to wait long periods for massive scenes to load and to define standards for enhancing such data with interaction. However, most of the existing frameworks are either domain-specific or too general, which results in increased data preparation times and additional needs for processing at the application level. This paper describes a novel system for CAD (Computer-Aided Design) data interaction built on Web3D technologies. First, we discuss the approach to prepare CAD models for visualisation: importation of data, the definition of mechanical behaviours, and physically-based rendering (PBR) properties. Next, we describe how to export CAD models as an X3D scene with federated glTF nodes to increase performance and overall client interactivity. We followup with a description of how the Denavit-Hartenberg (DH) parameters can enable the visualisation of mechanical motion characteristics directly from the design and enhance user interaction. Finally, we summarise lessons learned from this industry-based software engineering experience. We also identify several future research directions in this area.

It is widely acknowledged that geospatial information has immense applicability across a vast spectrum of human endeavors. Examples include oil and gas exploration, energy management, smart city engineering, weather forecasting, tracking, aviation, satellite ground systems, environmental planning, disaster management, public administration, civil planning and engineering, and science. All such activities entail gathering a significant amount of data and other critical information stored, accessed, managed, manipulated, analyzed, and visualized. This variety of applications requires novel methodologies and technologies capable of delivering both interactive visualization and intelligent complexity reduction.The main focus of this workshop report is the detailed dissection of these technologies, their relationship to one another, and their unique abilities to realize cross-reality capabilities and design principles in a multimodal immersive, and intelligent geographical environment. The goal is to enumerate (and prioritize) critical research and standards opportunities for merging geospatial technologies with smart manufacturing systems.

Nowadays there is a clear trend for improving productivity and efficiency in the Industrial sector by integrating new advanced ICT technologies that are re-shaping the industrial production paradigms, as in the Industry 4.0 initiative. This new trend does not only affect production lines and machines but also operators. Markets demanding efficiency and flexibility would not be possible excluding the human-factor. Putting the operators in the centre of this new paradigm is mandatory for its success. The operators need to be empowered by giving them new tools and solutions for improving their decision-making processes. In this paper we show how Visual Computing technologies can play a key role in this empowering process, being therefore essential in the realization of the Operator 4.0 vision.

Rapid advances in immersive reality technologies have resulted in a vast quantity of research papers which generally include or attempt to apply it to human cognitive augmentation. Taking advantage of traditional psychological and physiological metrics for studying human cognition and behavior, researchers are applying various near-real time analysis techniques to modulate immersive experiences and influence the mental state of the user. Because of the variety of contributing sub-domains, there is little consensus as to any rigid paradigm for the knowledge being synthesized. In this paper, we conduct a systematic literature review to determine the state of the art of dynamic cognitive augmentation in immersive environments. Following a structured query of academic publications, we conduct an in-depth analysis of 104 papers from a sample of 538. We observed that roughly 66% of papers among this frontier apply methods best suited for exploratory purposes, limiting the overall extent to which conclusions can be drawn about immersive reality technology's capability to augment human cognition. We further identify a pressing gap in the knowledge necessary for the effective application of immersive reality towards dynamic cognitive augmentation in practical industrial scenarios. We hope this work will influence academia, industry, and standards development organizations to extend the use of XR technology networked with biosensor-enabled intelligent cognitive assistants to enhance the effectiveness of hybrid human-machine systems.

In this paper, we discuss how Cross Reality (XR) and the Industrial Internet of Things (IIoT) can support assembly tasks in hybrid human-machine manufacturing lines. We describe a Cross Reality system, designed to improve efficiency and ergonomics in industrial environments that require manual assembly operations. Our objective is to reduce the high costs of authoring assembly manuals and to improve the process of skills transfer, in particular, in assembly tasks that include workers with disabilities. The automation of short-lived assembly tasks, i.e., manufacturing of limited batches of customized products, does not yield significant returns considering the automation effort necessary and the production time frame. In the design of our XR system, we discuss how aspects of content creation can be automated for short-lived tasks and how seamless interoperability between devices facilitates skills transfer in human-machine hybrid environments.

Augmented Reality (AR) has evolved over the past years, but before it is widely adopted and used in manufacturing industry, it has to overcome a number of technological challenges. Although new advancements in tracking and display technology have been a priority in recent research works, the use of accurate registration methods is not fundamental for users to understand the intent of the augmentation. Moreover, interactive visualization of contextual data in augmented spaces did not receive enough attention from the research community. In this paper, we investigate the creation of AR workspaces focused on interaction and visualization modes rather than on the registration accuracy, and how to provide more effective means to support assembly tasks in hybrid human-machine manufacturing lines. In particular, we focus on short-lived assembly tasks, i.e. manufacturing of limited batches of customized products, which do not yield significant returns considering the effort necessary to adapt AR systems and the production time frame.

Effective presentation of data is critical to a users understanding of it. In this manuscript, we explore research challenges associated with presenting large geospatial datasets through a multimodal experience. We also suggest an interaction schema that enhances users cognition of geographic information through a user-driven display that visualizes and sonifies geospatial data.

Information visualization has been widely adopted to represent and visualize data patterns as it offers users fast access to data facts and can highlight specific points beyond plain figures and words. As data comes from multiple sources, in all types of formats, and in unprecedented volumes, the need intensifies for more powerful and effective data visualization tools. In the manufacturing industry, immersive technology can enhance the way users artificially perceive and interact with data linked to the shop floor. However, showcases of prototypes of such technology have shown limited results. The low level of digitalization, the complexity of the required infrastructure, the lack of knowledge about Augmented Reality (AR), and the calibration processes that are required whenever the shop floor configuration changes hinders the adoption of the technology. In this paper, we investigate the design of middleware that can automate the configuration of X-Reality (XR) systems and create tangible in-site visualizations and interactions with industrial assets. The main contribution of this paper is a middleware architecture that enables communication and interaction across different technologies without manual configuration or calibration. This has the potential to turn shop floors into seamless interaction spaces that empower users with pervasive forms of data sharing, analysis and presentation that are not restricted to a specific hardware configuration. The novelty of our work is due to its autonomous approach for finding and communicating calibrations and data format transformations between devices, which does not require user intervention. Our prototype middleware has been validated with a test case in a controlled digital-physical scenario composed of a robot and industrial equipment.