ANSYS and Microsoft Twin Up for Digital Twins
Mary Cristobal posted on November 22, 2019 |
The collaboration will see ANSYS Twin Builder and Azure Digital Twins working together.

(Image courtesy of ANSYS.)
(Image courtesy of ANSYS.)

Engineering simulation company ANSYS announced that it will be working with Microsoft to extend Azure Digital Twins. The collaboration is expected to allow Microsoft’s enterprise customers to improve operations and reduce the cost of unexpected downtime. Users should be able to predict future performance of assets with more accuracy while reducing time-to-market.

“ANSYS Twin Builder’s complementary simulation data stream augments Microsoft Azure IoT Services and greatly enhances their customers’ understanding of asset performance,” said ANSYS’s Eric Bantegnie.

The industrial sector can invest millions of dollars just to build, maintain and track the performance of assets and machinery enabled and deployed remotely with IoT. To maximize a product’s lifespan on the field, operators make use of a digital twin—a complete virtual prototype of the existing asset in a physical environment. This can be things such as shipping containers, rooms, factory floors, or any other entities involving IoT solutions. The data from the digital twin lets operators establish preventive maintenance programs while making improvements to product development.

Besides letting users create models of physical environments, Azure Digital Twins include full support for two-way communication with IoT and Edge devices. The collaboration with ANSYS will allow manufacturers using Azure Digital Twins to optimize asset production and operations with the ANSYS Twin Builder. The two companies made use of compute integration and the Digital Twin Definition Language (DTDL) standard so that users can easily adopt and deploy digital twins.

DTDL is a language used to describe models and interfaces for digital twins. It allows the IoT platform to use semantic annotations and Resource Description Framework (RDF)—a widely adopted standard for describing resources—with the same entity definitions. This means analytics, machine learning, UIs, or any other computations can reason about both the semantics and the schema of the data. This is significant as users rely on the data provided by digital twins.

With additional software and data analytics, digital twins can optimize the IoT deployment process for maximum efficiency. The more a digital twin can duplicate a physical object or scenario, the more likely designers can identify both efficiencies and deficiencies. This can be particularly beneficial for the manufacturing sector as it allows operators to assess how an object may perform over time.

“As Microsoft Azure customers adopt IoT and digital twins to understand their business assets in real time, many are now looking for analytics tools that help them find new insights. Collaborating with ANSYS to extend Azure Digital Twins provides our customers with an understanding of their deployed assets’ performance by leveraging physics and simulation-based analytics,” said Microsoft’s Sam George.

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