HELLER,  Booth C70 / Hall 12
HELLER Group
308
HELLER Group
308
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We are exhibiting this product at EMO 2025
ManufacturerGebr. Heller Maschinenfabrik GmbH
Product group Universal machining centres
Product NameAI Solutions
Product images
Description

Smart & data-driven – AI in process and analysis

A brand-new feature to be introduced at EMO 2025 will provide customers with access to an intelligent chat function called “ASK-me”. This tool, integrated into the machine control interface, offers operators a ChatGPT-like assistant. In other words: users can enter questions in plain language, and the AI function quickly delivers clear, straightforward answers. The AI assistant uses the collective expertise of HELLER and its users to provide answers and support relating to the handling of the machine, including operation, setup and maintenance, and helps to interpret warning and error messages based on the machine’s live status. 

HELLER will also showcase AI-powered analysis tools at EMO, offering valuable benefits for maintaining productivity and high precision of modern machining centres. To achieve this, the Nürtingen-based machine manufacturer uses data collected as part of its Industry 4.0 strategy. The data can be visualised by production planners and analysts via the shop floor system – the HELLER Services Interface – in the form of text, tables or diagrams. This ensures transparency throughout the entire lifecycle of the machine – in production, maintenance, and service processes. For instance, hidden machine downtime can be identified using a generatively produced chart visualisation, whilst AI-supported analysis of the production data helps to reveal potential for boosting output.

At the trade fair stand, the HELLER service experts will demonstrate how the combination of data acquisition and intelligent analysis provides key insights for preventive maintenance. Returning to the previous example of the HELLER spindle: run times, load and overload phases and spindle speed values are also routinely recorded in addition to temperature trends. Based on this, it is possible to monitor the spindle’s condition and to prevent unplanned machine downtime caused by wear-related failure of the spindle. The same principle applies to other components such as axes or tools.

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