"The integration of AI into technology platforms will drive profound change in the way we work and operate in organizations," said Scott Guthrie, Executive Vice President, Cloud + AI at Microsoft. "Together with Siemens, we're unlocking the power of AI for more industrial organizations, enabling them to simplify workflows, break down silos and collaborate more inclusively to accelerate customer-centric innovation."

One step in this direction is the networking of employees from production with colleagues in other areas of the company through teams and AI-supported collaborative apps, which the two companies are aiming to achieve.
With the new Teamcenter app for Microsoft Teams, which is expected in the course of 2023, the companies want to enable design engineers, service and production staff and teams in all business areas to close feedback loops faster and solve challenges together. For example, service technicians or production employees can use mobile devices to document and report any product design or quality problems using natural language. Using Azure OpenAI Service, the app can analyze this informal voice data, automatically generate a summary report and then forward it within Teamcenter to the appropriate experts in design, development or production. To promote inclusion, employees can record their observations in their preferred language, which is then translated into the official corporate language by Microsoft Azure AI. Microsoft Teams offers features such as push notifications to simplify workflow approval, reduce the time it takes to request design changes and accelerate innovation cycles. The Teamcenter app for Microsoft Teams can empower millions of employees who don't have access to PLM tools today to more easily influence the design and manufacturing process as part of their existing workflows.

AI-supported development of software

Siemens and Microsoft are also working on accelerating code creation for programmable logic controllers for developers of software or automation solutions. At Hannover Messe, the companies presented a concept to show how OpenAI's ChatGPT and other Azure AI services can enrich Siemens' industrial automation solutions. The showcase demonstrated how development teams can significantly reduce their time and likelihood of errors by generating PLC code through natural language input. These functionalities can also empower maintenance teams to identify errors and generate step-by-step solutions faster.

Fewer product defects thanks to industrial AI

Early detection of defects in production is crucial to avoid costly and time-consuming production adjustments. Industrial AI such as computer vision enables quality management teams to scale quality control, identify product deviations more easily and make real-time adjustments even faster. In Hanover, Siemens and Microsoft already demonstrated how Microsoft Azure Machine Learning and Siemens' Industrial Edge can be used to analyze images and videos captured with cameras through machine learning and use them to create, deploy, execute and monitor AI vision models on the shop floor.