In Industry 4.0 and 5.0 discussions, a common argument appears: AI models reach around 90% accuracy, and in industrial environments a 10% error can cost millions. The reasoning sounds compelling because it is framed numerically and linked to operational risk. However, this argument assumes something critical — the existence of a fully digitized factory. In reality, across many manufacturing plants in Poland and Europe — especially in the SME sector — that level of digital maturity simply does not exist.

Digital twins are increasingly appearing in modern factory strategies. Process simulations, virtual production lines, scenario testing without the risk of stopping production – this sounds like the future of manufacturing. One of the most recognizable tools in this area is NVIDIA Omniverse. The problem begins when a digital twin is supposed to stop being a visualization and become a reflection of actual production. For this, data is needed. And this is where MES-class systems play a key role.

Nvidia and the data problem at a broader scale

System MES (Manufacturing Execution System) - If someone in 2025 still thinks of an MES system as "terminals at workstations and reports from the department," it's about as current as a fax machine in OT-IT integration. The Manufacturing Execution System has ceased being a shop floor application. MES has become the operational layer of truth between the world of automation (OT) and the business world (IT). MES systems in 2025 are operational platforms that determine whether a company thrives on availability, quality, lead time, and energy efficiency. The MES system has stopped being a cost—it has become a mechanism for steering competitiveness.