In recent months, I have conducted a tour across the UK and the Nordic region, focusing on the Industrial Metaverse. Throughout this tour, I have interacted with numerous customers and delivered various presentations. Here, I outline the key insights and takeaways from these experiences.
The concept of Industrial Metaverse is at the forefront of driving innovation for industrial companies. Building digital worlds is not a new idea. However, the key distinction between the Industrial Metaverse and the earlier digital twin technology lies in its enhanced realism and integration capabilities. Early digital twin technologies offered digital representations but lacked the depth of realism and interconnectedness seen today. The advanced visuals in the Industrial Metaverse allow for more effective training of AI models, using synthetic data that closely mimics real-world conditions. This progress means we can develop autonomous vehicles in a virtual environment, greatly accelerating innovation and reducing costs.
Furthermore, Industrial Metaverse is based on data from its legacy systems. By connecting various systems, such as ERP, CRM, MES, and IoT sensor data, to a single platform, you break down data silos and can hence utilize AI models to drive efficiency gains. However, because the systems are synchronized, virtual collaborations across functional divisions are enabled, and simulations are allowed in real-time. This is a game-changer.
One company that has successfully implemented these capabilities is BMW, which leverages NVIDIA’s Omniverse platform for factory design and planning. According to the global auto manufacturer, they are gaining 30% in production planning efficiency. In addition, the solution indirectly supports the ESG agenda as fewer resources are spent, and you can plan for better employee working conditions, to provide some examples.
In my recent customer conversations, it is evident that digital maturity varies greatly. Some organizations are already experimenting with and utilizing digital twins in their operations. In contrast, others hardly gather any data from their production lines or perhaps, even more critically, capture large amounts of data without using them, thus driving costs up without any gains.
The Industrial Metaverse concept is perceived as truly inspiring, and many organizations see its valuable potential. But for most, at the current stage, it’s an aspiration—a vision. We have been asked how we can become more digitally mature.
Exploring and developing a technology roadmap becomes pivotal, with the end goal of onboarding and leveraging the Omniverse platform. Omniverse is not an off-the-shelf solution. It’s tailored to your business context. Hence, this exercise is essential to identify digital gaps and barriers. Are you gathering all relevant data from your production equipment? Do you need to install cameras in your warehouse? Are you adding meta-communication to your data? How do you handle unstructured data? Are you controlling storage, compliance, security, latency, and connectivity?
In multiple sessions with business leaders, we have discussed the applicability of Industrial Metaverse and the reasons for failing or succeeding. What amazed me was the width of the imagined use cases. Applicability goes way beyond product development, factory planning, and warehouse automation, which are some of the core use cases.
Examples, where the omniverse can be applied, include enhancing customer experiences when taking a train, optimizing and simulating 5G mast coverage, optimizing offshore wind farms, assisting in urban and construction planning, visualizing scientific data, onboard staff using XR technology, conducting risk assessments for insurance companies, and much more.
One could argue that only the imagination sets the boundaries of how to utilize the Industrial Metaverse concept. This point stresses its embeddedness in business operations and why it is not an off-the-shelf solution.
That touches upon the other debated topic: what could be the reasons for failing? The topics are not new. Insufficient data strategy and governance, board approval or executive buy-in, business case and ROI, resistance to adoption, skills, and know-how. Many organizations would have come across the same challenges for other digitalization projects. However, it is essential for the Industrial Metaverse that you define the use cases that provide value to your organization and fulfill the overall objectives. That demands exploration with domain knowledge and technical expertise. This means that most organizations require a co-creation mindset with partners.
Deep dive further into the topic of Industrial Metaverse and learn more about what it is, the benefits it can give your organization, and the technical setup by downloading the joint T-Systems and NVIDIA whitepaper that elaborates further on the topic. Download it for free here.
You’re also welcome to contact us if you would like to know more about how T-Systems helps customers drive tangible benefits of NVIDIA Omniverse.
