Generative AI Unlocks Machine Data Via Chat

Industrial AI Generative AI Unlocks Machine Data Via Chat

2026-07-06 Source: Press release Pressemitteilung Fraunhofer IPA | Translated by AI 2 min Reading Time

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Researchers at Fraunhofer IPA are working on generative AI that allows production and machine data to be queried via chat. The goal is to present complex data in an understandable way and make its use in everyday work easier.

Production and machine data are to become more easily accessible through generative artificial intelligence.(Source: University of Stuttgart IFF | Fraunhofer IPA | Rainer Bez) — Production and machine data are to become more easily accessible through generative artificial intelligence.
(Source: University of Stuttgart IFF | Fraunhofer IPA | Rainer Bez)

In industrial production, vast amounts of data are generated daily. However, in many cases, they remain unused because their evaluation is complex. Data must be compiled from various sources, processed, and visualized—a process that often requires specialized expertise and is particularly difficult for small and medium-sized enterprises to implement.

Access Data via Chat

In the "ViPGeniE" project, the Fraunhofer Institute for Manufacturing Engineering and Automation IPA, together with the companies Ads-tec Industrial IT GmbH, Data Coffee GmbH, and Ulrich GmbH & Co. KG, is working on making production and machine data accessible using generative AI. Similar to everyday applications, specific information, such as machine statuses or temperature trends, can be queried via chat.

The AI not only provides text as a response but also generates appropriate diagrams and visualizations. Through further queries, a dialog-based access to the data is created, enabling step-by-step analysis of correlations and potential causes of errors.

Digital Twins as a Foundation

The technical foundation is a digital twin of production, in which production and sensor data are continuously collected and structured. This provides the necessary contextual information so that the AI can correctly interpret and visualize the data.

"The barrier to using production and machine data is significantly lowered as a result," says Matthias Schneider from Fraunhofer IPA. Since access occurs directly via chat, there is no need to manually adjust or create new visualizations.

Small and medium-sized enterprises, in particular, could benefit from this approach, as they often lack their own specialized personnel for data analysis, leading to delays in conducting corresponding evaluations.

3D modeling software Blender with the integrated component catalog from MHJ-Software (left), the setup of a virtual system in the design area (central) and the specially developed plugin for skill configuration (right). (Image:MHJ software)

Demonstrator Planned for 2027

Fraunhofer IPA is developing, among other things, the system architecture, a flexible environment for the use of different language models, as well as the digital twins that structure the data. A first demonstrator showcasing the visualization of complex production and machine data from various sources is planned for the second quarter of 2027.

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