Powerful and advanced artificial intelligence is emerging as one of the most important technologies for digital transformation.
For this reason, siemens
are harnessing their power of collaboration to help industrial companies drive innovation and efficiencies in the design, engineering, manufacturing, and operational lifecycle of products.
In this way, companies are integrating Siemens’ Teamcenter software for product lifecycle management with Microsoft’s Teams collaboration platform and Azure OpenAI Service language models, as well as other Azure AI capabilities.
“With Siemens, we are bringing the power of AI to more industrial organizations, enabling them to simplify workflows, overcome silos, and collaborate in more inclusive ways to accelerate customer-centric innovation.” explains Scott Guthrie, executive vice president of Cloud + AI at Microsoft.
Artificial Intelligence with Teamcenter
The new Teamcenter app for Microsoft Teams, available in late 2023, will empower design engineers, first-line workers, and teams across all business functions to solve problems together and close feedback loops faster.
The app will use the Azure OpenAI Service to analyze voice data and automatically create summary reports. In this way, workers can record their observations in the language they want, so that it can later be automatically translated into the official language of the company.
Keep factories running with automation software engineering
Both companies are also collaborating to accelerate code generation for Programmable Logic Controllers (PLCs) in factories around the world. At Hannover Messe, they are demonstrating how ChatGPT and other Azure AI services can enhance industrial automation engineering solutions from Siemens.
Siemens and Microsoft boost industrial productivity with generative artificial intelligence
This test will show how PLC code generation through natural language inputs can reduce time and error probability, as well as allow maintenance teams to identify errors and generate solutions more quickly.
Detection and prevention of product defects
Early detection of defects in production is crucial to avoid more expensive and lengthy adjustments. This is where industrial AI can help teams scale quality control, easily identify product deviations, and make real-time adjustments more efficiently.
In Hannover, it will be demonstrated how the use of Microsoft Azure with Machine Learning and Siemens Industrial Edge will enable the analysis of images captured by cameras and videos using ML systems.