Accenture Launches “Physical AI Orchestrator” to Help Manufacturers Build Software-Defined Facilities
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New cloud solution combines NVIDIA Omniverse technologies and AI agents from
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Accenture introduces Physical AI Orchestrator and first clients in high tech, life sciences and consumer goods at NVIDIA GTCWashington, D.C.
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Manufacturers can use Accenture’s Physical AI Orchestrator solution to develop live digital twins of planned and existing factories, warehouses and equipment. Copyright (c)
In a software-defined facility, virtual replicas mirror the physical automated plant or warehouse and its equipment. These live digital twins detect issues and use accurate physics to simulate the impact of potential process changes in real time. AI Agents then convert the insights into precise instructions, which enable the physical plant to adapt to changing demand, quality or scheduling. Accenture’s Physical AI Orchestrator lets manufacturers build live digital twins of planned and existing physical assets, from conveyors and industrial and mobile robots to shop floor and warehouse layouts, and connect them to physical counterparts.
At NVIDIA GTC
For example, Belden, a network and data solutions provider, has developed a solution for worker safety in factories and warehouses. Using Physical AI Orchestrator, it developed a virtual safety fence solution to create safety zones around robots without disrupting ongoing operations. If a human enters the zone, the robots are automatically stopped or rerouted. The solution uses edge AI to detect and model worker, vehicle and robot movements and equipment paths at centimeter-level fidelity within facilities. Trained on multiple what-if scenarios, such as forklifts reversing unexpectedly, the virtual safety fence is expected to be first deployed by an automotive manufacturer to address pedestrian safety in warehouse environments.
Other examples of companies taking advantage of Physical AI Orchestrator include:
- A life sciences company can now validate ideal production conditions for biologics and vaccines faster than if using physical equipment. Using Physical AI Orchestrator to simulate the entire preservation cycle and drying process, the company tested various temperature and pressure profiles. The simulation showed exactly when, where, and why deviations occurred. This resulted in reduced batch variability and increased product shelf life.
- A consumer goods manufacturer has increased warehouse throughput and reduced capital expenditure. Using Physical AI Orchestrator, it built a digital twin of its warehouse operations to analyze worker movement, picking rates and conveyor systems to identify throughput gaps and layout inefficiencies. The twin recommended adjustments to the layout design and resource allocation. This resulted in a 20% throughput improvement from optimizing the conveyor flow and saved 15% in capital expenditure by eliminating iterative trial-and-error redesign.
“Physical AI Orchestrator acts as a brain for a physical space,” said
Early adopters have seen measurable benefits with Physical AI Orchestrator, which is designed to significantly lower product design costs and capital costs for building new plants and produce higher factory planning accuracy.
The capabilities Physical AI Orchestrator offers to manufacturers include but aren’t limited to the following:
- Reality capture – a set of automated, AI-powered processes to generate digital twins of factories and equipment. Videos and scans are converted into photorealistic 3D models to detect layout changes and keep the digital twin updated.
- AI agents – aiding engineers during the entire process of, for example, designing, simulating and installing a new production line, with expert knowledge from past projects.
- Vision analytics – to capture and ingest live video data, such as worker, vehicle and material movements in a facility required to run precise simulations.
- Asset connectors – to integrate existing equipment into a simulation in a plug and play fashion.
- XR extensions – enabling interactions with the digital twin in a high-quality augmented environment and training and collaboration in a shared virtual space.
Forward-Looking Statements
Except for the historical information and discussions contained herein, statements in this news release may constitute forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. Words such as “may,” “will,” “should,” “likely,” “anticipates,” “aspires,” “expects,” “intends,” “plans,” “projects,” “believes,” “estimates,” “positioned,” “outlook,” “goal,” “target” and similar expressions are used to identify these forward-looking statements. These statements are not guarantees of future performance nor promises that goals or targets will be met, and involve a number of risks, uncertainties and other factors that are difficult to predict and could cause actual results to differ materially from those expressed or implied. These risks include, without limitation, that the use of AI, including physical AI, could harm our business, damage our reputation or give rise to legal or regulatory action, as well as the risks, uncertainties and other factors discussed under the “Risk Factors” heading in
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