Aras Announces Digital Twin Core for Creating and Managing Digital Twins

Enables organizations to create digital twins for any product or system of assets across any industry

ANDOVER, Mass. — (BUSINESS WIRE) — July 7, 2020Aras, the only resilient platform provider for digital industrial applications, today announced the release of a new application, Digital Twin Core, adding to the set of Aras low-code capabilities for creating and managing digital twins. The Aras Digital Twin Core application provides powerful new functionality for defining the digital twin configuration – the virtual representation of a specific physical asset or unique product instance. This provides the necessary context to interpret and analyze Internet of Things (IoT) sensor data for complicated scenarios such as predictive maintenance, performance optimization, over-the-air software updates and others.

Current digital twin initiatives focus on maintenance effectiveness, recalls, closed-loop quality, product innovation, and production throughput. Problems occur during analysis due to a lack of context or inaccuracies about that asset or product.

“As a real-world asset is maintained, updated and retrofitted, companies need the ability to easily reflect the real-time accurate status of the digital twin configuration,” said Peter Schroer, Founder and CEO of Aras. “Without an accurate configuration twin, companies risk analysis misinterpretations that lead to incorrect actions, safety issues and liability scenarios.”

Aras Digital Twin Core creates and manages the exact digital representation of an individual physical asset and its changes over time. This digital twin configuration mirrors a specific unit in operation such as an individual vehicle by VIN or aircraft by tail number. Digital Twin Core provides a low-code editor for modeling, adapting and extending highly sophisticated configuration twin representations. When combined with Aras 3D dynamic product navigation and graph views, users gain advanced visualization to see digital twin relationships throughout the product structure.

Related Aras functionality further extends Digital Twin Core capabilities for complex scenarios. Connectors to existing systems - such as ERP, PDM, CAD and others – provide connectivity to derive and persist configuration twin data from other sources and ensure digital thread traceability across the lifecycle. Open APIs enable connections with IoT cloud services and data lakes to bring together configuration twins with time series sensor data for analysis. Then, simulation management with Aras enables the combination of configuration twins in simulations with real world loading data for insights into wear & tear, stress impacts, and other effects that result from ongoing operation of the asset.

"As manufacturers continue to digitally transform, and product, supply chain, and operation complexity increases, manufacturers and owner operators are using digital twins to optimize product and asset quality and improve the customer experience. The ability to manage an assets configuration as it changes overtime is a foundational element to an effective digital twin strategy," said Jeff Hojlo, Program Director of Product Innovation at IDC.

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About Aras

Aras provides a resilient platform for digital industrial applications. Its open, low code technology enables the rapid delivery of flexible, upgradeable solutions for the engineering, manufacturing and maintenance of complex products. Aras’ platform and product lifecycle management applications connect users in all disciplines and functions to critical product data and processes across the lifecycle and throughout the extended supply chain. Airbus, Audi, Denso, GE, GM, Honda, Kawasaki, Microsoft, Mitsubishi, and Nissan are investing in the platform to manage complex change and traceability. Visit www.aras.com to learn more and follow us on Twitter and LinkedIn.



Contact:

Aras Press Contact
Kylie Reardon
Aras
kreardon@aras.com
+1 978 806 9410

Jenna Gilligan
Version 2.0 Communications
jgilligan@v2comms.com
+1 617 426 2222

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