Metaverse hyperconnected for operators training within industry 5.0

Abstract

The digital transformation is revolutionizing the manufacturing industry, fostering a convergence between physical and virtual realms through Cyber-Physical Systems (CPS). These systems, equipped with sensors, actuators, intelligence, and connectivity, forge a crucial collaborative environment. Yet, overcoming technological challenges inherent in the merging of diverse Smart Manufacturing-associated technologies is pivotal to attaining industrial virtualization. This digital shift has opened novel perspectives for process simulation and operator training, elevating efficiency and collaboration in industrial landscapes. Developing these applications requires virtualizing the CPSs, requiring modeling their behavior by understanding their responses to real stimuli in the physical environment. Thus, the virtualization extends beyond CPSs to encompass their dynamic physical settings, creating a simulation environment denominated as Digital Twins (DTs). These DTs can recreate numerous scenarios and hypotheses that replicate the real behavior of the systems in a virtual way allowing the analysis of different operational conditions in the virtual world. In this sense, DTs find relevance in contexts like intelligent industrial transportation, where the environment plays a pivotal role in guiding Autonomous Mobile Robots (AMRs) navigation. For this reason, in Chapter 5, a DT was developed to compare times and trajectories between a virtual and a real autonomous vehicle, yielding high similarity. Implementing DTs in industrial transportation enhances decision-making for optimizing key processes critical for the overall performance of the industrial plant. Moreover, this virtualized environment later incorporates an AMR fleet to scrutinize their behavior under real industrial settings. This allows the understanding of the response of each AMR of the fleet using different navigation algorithms within a dynamic virtualized environment. Particularly, Chapter 6 analyzes the Timed Elastic Band (BET) and Dynamic Window Approach (DWA) navigation algorithms. Additionally, to facilitate the comprehension of the simulations performed, an interface was devised to dynamically modify parameters and visualize real-time simulation data. However, valuable DT insights aren’t seamlessly integrated within Chapters 5 and 6 into the collaborative environment of productive processes, as per the Smart Manufacturing (SM) paradigm. Hence, transmitting DT and other external assets data to industrial architectures and communications protocols demanded the development of an interoperability gateway. This gateway analyzes assets’ communications, tailoring them to destination hardware and software needs achieving what is defined in this dissertation as the hyperconnectivity among heterogeneous assets. This specifically applies to the industrial collaborative environment proposed in Chapter 4. This hyperconnected environment facilitates the convergence of diverse industrial technologies within it for multifaceted applications. For instance, integrating DTs with Virtual Reality (VR) offers a more immersive perception of industrial process virtualization, bridging not only technological but also human assets through immersive experiences. This facilitates the development of numerous industrial applications, including operator training to mitigate costs and risks in real environments, as studied in Chapter 7. In this sense, it is demonstrated that humans can learn to handle industrial machines in a virtual environment nearly as effectively as they do in the real world. However, the generation of a virtual ecosystem that completely replicates the real environment not only entails the relations between humans and machines but also among humans. Thus, including another human in this virtual environment enables more realistic interactions and collaboration, creating a fully virtual space, the industrial metaverse. Thus, finally, Chapter 8 evaluates performance and user satisfaction by comparing real and virtual environments in collaborative activities involving two humans and an AMR, showing a novel research direction that helps to completely develop the principles of the next industrial revolution, Industry 5.0. For these reasons, this dissertation particularly explores the virtualization of industrial assets, overcoming technological barriers to develop hyperconnected applications within the Industry 5.0 paradigm, placing humans at the forefront of the factory of the future.