Heterogeneous environment of digital twins for industrial applications

This PhD project explores the innovative concept of a heterogeneous environment of digital twins, focusing on how diverse digital twin technologies can interact and collaborate seamlessly. Imagine a future where digital twins of robots, humans, and their work environments are interconnected, creating a dynamic and responsive ecosystem. This research aims to make that vision a reality. The project focuses on three key aspects: Human Motion Prediction: By utilizing advanced 3D sensors and deep learning algorithms, we're developing digital twins that can accurately predict human motion in real-time. This capability allows for proactive adjustments in the digital twin environment, enhancing safety and efficiency. Intuitive User Interfaces: We're creating immersive interfaces that allow humans to interact with digital twins effortlessly. Imagine controlling a robot in an augmented reality (AR) with simple hand gestures or receiving tactile feedback through a wearable device, enhancing the intuitive connection between the human and the digital twin. Safe and Efficient Collaboration: By integrating 3D sensors, user interfaces, and intrinsically safe robots, we're creating a collaborative digital twin environment where robots and humans can work in close proximity, exchanging solutions and performing tasks together, all while ensuring safety. This research has the potential to revolutionize industrial automation by enabling the creation of more complex and interconnected digital twin systems. It's about empowering humans and digital twins to work together, unlocking a new era of productivity and innovation.

Over the last few decades, there have been rapid advancements within automation and digitalization due to the advancements made within the fields of internet of things (IoT) and computing power. These, together with emerging technologies like big data, cloud computing, artificial intelligence (AI) and digital twins (DT), makes smart manufacturing and the transition to industry 4.0 possible. The transitions demand high competences within the field of mechatronics combining information and communications technology (ICT) with technical understanding of manufacturing processes. Many small and medium-sized businesses (SMBs) are struggling to keep up with the pace of these rapidly evolving technologies. Tvillingfabrikken is positioned in the market of developing DTs for industrial SMBs and intends to be a catalyst for smart manufacturing systems towards industry 4.0. DTs are used to some extent today, mainly for visualization purposes and product development. However, the full potential is far from being fully exploited. This project aims at combining DTs with big data and AI for smart production planning, predictive maintenance as well as virtual commissioning and testing of new automated systems.