en.Wedoany.com Reported - Siemens, in collaboration with NVIDIA, has launched a new software called "Digital Twin Builder" for the UK and Irish markets. This product combines industrial AI, simulation, and real-time physical data, helping enterprises make decisions quickly and at scale in a virtual environment.
The Digital Twin Builder is part of the Siemens Xcelerator portfolio and was first showcased at "Transform 2026," Siemens' biennial industrial technology event held in Manchester. Brian Holliday, CEO of Siemens UK and Ireland, along with Anthony Hills, Regional Director of NVIDIA UK and Ireland, demonstrated how comprehensive digital twins, real-time operational data, and physical AI can support faster, lower-risk decision-making.
This tool enables industrial enterprises to combine 2D and 3D data from Siemens digital twins with real-time physical information, operating within a managed, secure, real-time visualization environment built on the NVIDIA Omnibus library. Companies can quickly build and maintain this holistic environment, securely placing virtual and physical production data into a managed, high-fidelity 3D experience throughout the entire lifecycle of a product, process, or facility.
The Digital Twin Builder allows enterprises to integrate digital twin data with physical information, generating real-time insights for visualizing and iterating any element of a factory process or field product.
The solution has already been deployed at PepsiCo, marking the first industry collaboration between Siemens and NVIDIA. PepsiCo is using advanced digital twin technology and AI to transform factory and supply chain operations. This is also the first time a global consumer packaged goods (CPG) company has used digital twins to reshape how factory and warehouse facilities are digitally simulated and tested. This approach helped PepsiCo identify up to 90% of potential issues before any physical modifications were made. Following the initial deployment, throughput increased by 20%, design validation approached 100%, design cycles accelerated, and capital expenditure (Capex) was reduced by 10-15% through discovering hidden capacity and validating investments in a virtual environment.
KION, a global supply chain solutions and logistics company, is also using this technology to enable parallel and real-time simulation of multiple processes, unlocking previously unattainable levels of efficiency and flexibility.
Siemens states that using industrial AI to simulate entire processes aims to help enterprises manage the pressure of connecting and simulating the complex, massive data within engineering and production lifecycles, thereby improving productivity, achieving product and production performance targets, enhancing resilience, and reducing emissions. Companies can model a facility, production line, or process, and then test its response to different scenarios, such as changing factory layouts, introducing new automation, increasing capacity, altering warehouse material flow, or validating equipment before installation. By leveraging industrial AI throughout the process, enterprises can optimize throughput and test multiple productivity scenarios.
Brian Holliday, CEO of Siemens UK and Ireland, stated that organizations in the industrial and infrastructure sectors face new, complex challenges requiring faster transformation. However, operating factories and power grids are difficult to experiment with, as every change incurs costs in effort, expenditure, energy, or risk. Industrial AI and digital simulation provide enterprises with a practical way to test decisions and designs before costs are incurred in the physical world. He noted that teams can optimize production lines to increase capacity or reduce energy consumption, validate automation designs to truly optimize desired business outcomes, while simultaneously addressing typical project issues. Holliday emphasized that the product is already being used with key customers in the US and holds significant potential for supporting the transformation of UK industry. It fundamentally reduces the software engineering workload, which has historically been a barrier to digital twin adoption. By connecting simulation, physical AI, and real-time operational data, enterprises can quickly solve practical problems, act with greater confidence, and reduce the risk of costly errors.
