How can production processes be intelligently controlled, flexibly adapted and reliably scheduled? INFORM will be addressing these and many other questions on AI-supported process optimization at HANNOVER MESSE 2025. The Aachen-based software developer is presenting FELIOS, an AI-based solution that is already being used successfully by more than 300 companies in the mechanical and plant engineering sector, making their production processes more efficient, transparent and adaptable. As an add-on to conventional ERP systems, FELIOS uses decision-intelligent algorithms to analyze all planning-relevant data, create optimized schedules and dynamically control production capacities. In addition, the software relies on machine learning to accurately predict replacement times for purchased parts, among other things. By analyzing supplier behavior and other relevant factors, FELIOS reduces estimation errors by up to 42 percent and sustainably increases planning accuracy.

Optimized planning across departmental boundaries

The optimization software connects all departments involved in the value creation process and brings together all the data centrally in one system. This enables companies to achieve cross-departmental planning transparency in production, purchasing, design, and sales. In addition to traditional production and manufacturing planning, FELIOS also includes dynamic shift and employee scheduling, strategic capacity requirements planning, and project planning tailored to the needs of the mechanical and plant engineering industry. Tailored to the requirements of the modern working world, the advanced planning and scheduling (APS) system now also offers an integrated chatbot that provides users with real-time support and well-founded answers on functions and planning processes. In addition, the FELIOS Academy offers a new e-learning platform that enables flexible, practical learning, which both facilitates the induction of new employees and deepens existing knowledge in a targeted manner.

New impetus for the future of production planning

“With FELIOS, we are focusing on an intelligent combination of optimization, machine learning and language assistance that enables companies to achieve integrated, AI-supported production planning,” explains Markus Günther, Head of Sales Production at INFORM. “The three pillars of AI work seamlessly together: optimization algorithms efficiently plan production resources, machine learning analyzes historical data and improves forecasts, while the language assistant facilitates direct access to planning information. At this year's HANNOVER MESSE, we will be demonstrating how companies can use this combination to their advantage. We look forward to engaging with trade visitors, presenting practical use cases and providing new impetus for the future of production planning,” says Günther.

Expert talks from INFORM at HANNOVER MESSE

In addition to the product presentations, INFORM will be offering exciting insights into the future of AI-supported process optimization at the trade fair. The focus will be on the presentation by Dr. Jörg Herbers, CEO of INFORM, on Wednesday, April 2, 2025, from 4:00 to 4:30 p.m. on the Digital Transformation Stage (Hall 17, Stand E44) on the topic “Process AI: The Future of Process Planning and Control”. Further expert input will be provided by Markus Günther, Head of Sales Production at INFORM and VDMA Board Member for Software & Digitization at the 17th International MES Conference (Wednesday, April 2, 2025, 2:00–3:00 p.m., Convention Center, Room 3B) and in the presentation “ERP Trends for SMEs 2025” (Friday, April 4, 2025, 9:30–10:00 a.m., Digital Transformation Stage, Hall 17, Stand E44). In addition, INFORM invites you to the master class 'Interactive simulation game: intelligent production planning to increase on-time delivery'. In the interactive session on March 31 from 10:45 to 11:45 a.m. in Hall 17, Stand E44, participants will experience the limits of classic planning methods in a practical way and learn how an APS system like FELIOS masters complex requirements in mechanical and plant engineering.

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