This rich data foundation allows Siemens to extend digital twins beyond isolated products or equipment into comprehensive, dynamic representations of entire production lines, facilities, and infrastructure. These digital twins act as living models, continuously updated with operational data, providing agencies with deep insights into system performance, potential failure points, and optimization opportunities.
In fact, a prime example of our work to develop the most robust industrial digital twin possible is manifested through the Navy’s ongoing Shipyard Industrial Optimization Program, a multi-decade effort using digital twins as the core of their plan to modernize four public shipyards and accelerate the operational availability of the fleet.
By combining industrial AI with these sophisticated digital twins, Siemens empowers operators to simulate “what-if” scenarios, predict maintenance needs before failures occur, and make data-driven decisions that improve throughput, reduce downtime, and enhance overall resilience. This integrated approach not only maximizes asset utilization but also drives sustainable and efficient operations, which in turn help to deliver measurable improvements across complex industrial ecosystems.
