Leverage the comprehensive digital twin to design, simulate, and optimize products, machines, production and entire plants in the digital world before taking action in the real world. This helps manufacturers to tackle industry's biggest challenges.
The comprehensive digital twin is a living digital model of a product, machine or plant that evolves across its lifecycle. It combines the real and digital worlds to simulate, test and optimize before anything is built, cutting risk, cost and prototypes. Predict performance; get it right first time; boost uptime; reduce maintenance, and maximize reuse. Start small and scale as you grow.
A digital twin of a product or process uses physics-based simulations to create real value by running "what-if" scenarios, predicting performance and enabling fast, confident decisions before acting in the real world.
The digital twin can analyze the past, reflect the present and predict the future. It optimizes products and production systems before physical assets and prototypes are invested in, thus, helping to avoid expensive failures.
Operational data and data-driven algorithms help make the digital twin as precise as possible for continuous optimization and predictive maintenance. Combining the digital twin with industrial AI unlocks additional potential.
The Siemens comprehensive digital twin approach uniquely integrates the entire product and production lifecycle, providing actionable insights and enabling informed decisions for the continuous optimization of products and production.
Using proven, scalable IT mechanisms — such as decoupling functions from hardware — systems can be expanded via software and centrally managed as needed, enabling agility and continuous evolution from product to production.
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The industrial metaverse is an immersive, collaborative space where users interact with digital representations of real assets. Here, interoperable digital twins connect, enabling teams to test, simulate and optimize together.
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The integration of AI is pushing the boundaries of what is possible, removing data preparation bottlenecks, improving the fidelity of digital models, and enabling rapid simulation and optimization. An AI-powered digital twin and automated data contextualization now open up a new possibilities for boosting the efficiency and productivity.
Simulation capabilities have emerged as the key to adapting to the changes of today's environment. Companies can leverage this technology to remain competitive through managing industry challenges.
