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EDAG SMART INDUSTRY SUMMIT:
SEPTEMBER 17 TO 19, 2025

EDAG Smart Industry Summit 2025

A summit of ideas – for industry and the public sector    

The EDAG Smart Industry Summit was more than just an industry trade event: it was a meeting place for thought leaders, practitioners, and decision-makers, who came together to look into the future of industry.
Presentations, live demonstrations, and discussions brought to life what digital technologies are already capable of today.

From digital twins that enable entire process chains to be rethought, to AI-supported manufacturing and perspectives on the industrial metaverse and robotics – the topics impressively combine vision and practice.

The event clearly illustrated that the transformation has already begun. And those who actively shape it are laying the foundation today for the production and operations of tomorrow.

We would like to thank all participants for their interest and participation in the Smart Industry Summit 2025.

For those who were unable to attend the event or who are particularly interested in the topics presented, we have set up a dedicated download area. You can access it once you complete the form via the provided link.

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Highlights from the Smart Industry Summit 2025

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AGENDA

RegistrationKeynoteCouch TalkBreakClosing
TimePresentation TitleSpeakers
09:00 – 10:15
1 h 15 min
Registration + Networking
Check-in, welcome, networking.
10:15 – 10:45
30 min
Opening of the Smart Industry Summit Europe 2025
Welcome by the Executive Board of EDAG Group.
Harald Keller — CEO EDAG Group
10:50 – 11:15
20 min + 5 min Q&A
EDAG KEYNOTE: Smart Product
Openness to exchange between automotive and industrial development – transparency, mutual respect, reciprocal benefits.
Michael Küpper — VP Engineering Smart Product
11:20 – 12:15
45 min + 10 min Q&A
Couch Talk: Smart Product
Challenges, market trends and impact on product development.
Prof. Dr. Florian Kauf (PwC) — R&D
Ales Paldus (EDAG) — Vice President E/E
Heiko Herchet (EDAG) — Vice President Digital Transformation
Jörg Hülsmann (EDAG) — Vice President CAE & Vehicle Safety
Dr. Frank Breitenbach — EDAG Senior Expert Planning Methodology
12:15 – 13:30
1 h 15 min
Lunch Break + Networking
13:30 – 13:55
20 min + 5 min Q&A
EDAG
Adoption of Smart Product Ideas in Medical Technology
Peter Weismüller — EDAG Senior Sales Manager
14:00 – 14:25
20 min + 5 min Q&A
EDAG: Industry in the Energy Transition
Barriers and Solutions for Energy Buffering and Storage across Scales
Marius Koch — Head of Department Testing and Vehicle Construction
Aron Deutschländer — Head of Department Project- and Portfolio Management EA
14:30 – 14:55
20 min + 5 min Q&A
Google: Shifting gears with Google AI in Manufacturing & Automotive
Gerhard Keller — Head of Manufacturing & Auto, Germany
15:00 – 15:25
20 min + 5 min Q&A
AI for Engineers: How AI is rethinking product development in industry
Insights into the AI-based engineering process – today and in the future.
Nick Westphal — Project Manager Digital Transformation/AI
15:25 – 16:00
30 min
Coffee Break
16:00 – 16:25
20 min + 5 min Q&A
EDAG: AI, Safety & Security in the Smart Industry
Opportunities, challenges, risks, and practical approaches.
Ugur Akcakoca — Head of Tech Center Safety & Security
16:30 – 16:55
20 min + 5 min Q&A
Combient Foundry
Venture Clienting – how medium-sized companies can benefit from startups
Carolina Alex — Head of Operations
Felix Gugler — Head of Business Development Central Europe
17:00 – 17:25
20 min + 5 min Q&A
EDAG: Reduce Time-to-Market
New tools & methods in industrial design – combining innovation power & efficiency.
Andreas Farnung — Head of Design Studio
Oliver Baehr — Project Manager
17:25 – 17:30
5 min
Closing Day 1 & Opening Dinner Buffet
Dirk Keller — Member of the Board of Management EDAG PS

INDUSTRIAL SOLUTIONS AT A GLANCE

SMART PRODUCT

From idea to series production: Digital twins, AI, and models accelerate the development of connected products.
 

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      Smart products don't just happen by chance. They are the result of well-thought-out, model-based development, networked system architectures, and intelligent optimization. Companies are faced with the challenge of integrating software solutions into their products, mastering complex data models, and accelerating time to market.

      At the Smart Product theme island, we show how digital twins, AI-supported simulations, and end-to-end development processes make the entire product development process more efficient and secure. You will learn how new technologies help minimize risks, reduce costs, and implement innovative product features.

      You can look forward to practical application examples that show how the requirements of customers, markets, and regulatory authorities can be mapped and implemented at an early stage. The result is products that are connected, adaptable, and truly future-proof.

  • Focus areas:
      • Model-based development: Consistent and end-to-end product models from concept to series production
      • Digital twins: Integration of development, manufacturing, and operation in a central data model
      • AI-supported optimization: Automated validation and intelligent decision support
      • Scalable system architectures: Platform approaches for connected, future-proof products
      • Data-based services: Predictive maintenance, product feedback, and new business models

SMART FACTORY

The future of industrial manufacturing

 

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      The smart factory is no longer just a visionary concept. It is a reality and a decisive factor for efficiency, quality, and future viability in industrial manufacturing. The challenge: mastering complexity, using resources efficiently, and remaining adaptable at all times.

      At the Smart Factory theme island, we showcase
      Virtual twins of physical plants and processes enable improved development, simulation, and real-time monitoring. This reduces development times and downtime and improves product quality.
      Intelligent factories are becoming the global standard through the integration of advanced sensors, real-time connectivity, and data analysis to optimize efficiency and productivity. This increases flexibility and enables rapid adaptation to new circumstances, while reducing costs.
      Cognitive robots and advanced automation work alongside humans to increase productivity, safety, and adaptability across a wider range of manufacturing tasks. AI-driven automation enables predictive maintenance, quality control, and real-time process optimization. Machine learning enables factories to anticipate problems, reduce downtime, and make data-driven decisions.
      Sustainable and circular economy Factories are committed to environmentally friendly production and focus on reducing energy consumption, minimizing waste, and achieving carbon neutrality.

  • Focus areas:
      • The Industrial Metaverse in practical application
      • The global standard for smart factories
      • Cognitive robotics will be the worker of the future
      • Operational excellence and cost-optimized production solutions
      • Supply chain excellence and the digitization of the supply chain
      • AI-based quality control: Predictive error prevention in real time
      • Adaptive control concepts: Flexible response to fluctuations and disruptions
      • Scalable platform architectures: Integration of all production data for strategic control

SMART PEOPLE

Humans and machines work together intelligently – with AI assistance, learning systems, and intuitive interaction.
 

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      In the smart factory, people are part of a larger system. Their capabilities are enhanced by digital tools, and their decisions are backed up by data-based support.
      Smart People stands for the integration of human expertise into a highly networked industrial environment. Whether through interactive training models, personalized dashboards, or AI-supported assistance systems, this is about a new quality of collaboration.
      At the Smart People theme island, we show how companies promote talent, scale knowledge, and create an agile work culture in which technology becomes a partner.

  • Focus areas:
      • Adaptive training models: Interactive learning scenarios in virtual environments
      • AI assistance: Support for decision-making processes through smart algorithms
      • Human-machine collaboration: Intuitive interfaces and safe workplaces
      • Knowledge management: Dynamic systems for contextualizing and utilizing expert knowledge
      • Empowerment through data: Individual support for productive, secure work processes

SMART ECOSYSTEM

Add new digital services and business models to your smart factory, reach new target groups and sales channels, and increase added value with external data and software solutions.
 

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      Software and digitalization are becoming increasingly important—even outside of actual production. The key question here is how to reach new target groups and develop data and interface architectures that can be scaled in a future-proof manner and create sustainable added value. This is based on networked data spaces, adaptive systems, and AI-supported assistance solutions that make knowledge accessible. Equally important are industrial web shops, connections to global marketplaces, and SaaS-based business models.

      In the Smart Ecosystem theme island, we show how physical and digital worlds are seamlessly converging in industrial practice. Experience how a data lake hub connects, optimizes, automates, and secures collaboration and processes, accelerating the development of innovative solutions and new business models.

      Using practical examples, we show how companies can confidently use their data, scale their expertise, and increase their value creation with relevant data and third-party services – for a productive, secure, and resiliently connected ecosystem.

  • Focus areas:
      • Networked data rooms: Trustworthy data exchange in dynamic industrial ecosystems
      • Data architecture: Development of scalable data infrastructures (data lake hubs) for integrating a wide variety of sources
      • Interfaces & systems: Connection/integration and orchestration of existing IT/OT landscapes
      • Tool selection & integration: Selection of suitable tools for data management and analysis
      • Data analytics: creating value from data through pattern recognition, evaluation, forecasting, and reporting
      • AI-supported assistance systems: support for decision-making processes, automation, and training situations
      • Cognitive robotics: Intelligent systems with swarm behavior and adaptive learning
      • Dashboard solutions: Data visualization and monitoring for process transparency
      • App development: Customized applications for mobile and industrial applications
      • Foundation models: Scalable AI building blocks for specific industrial applications
      • Industrial Webshop: Dynamic adaptation of production to market movements

INDUSTRIAL METAVERSE

The Industrial Metaverse is the digital foundation of tomorrow's manufacturing. It is data-driven, AI-powered, and opens up new possibilities for automation.

 

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      The Industrial Metaverse is a virtual replica of real-world manufacturing that takes efficiency, innovation, and flexibility to a whole new level. People, machines, and processes are connected in real time. This creates the conditions for the intelligent use of cognitive robots and automation solutions, data-driven decisions, and a completely new level of industrial value creation.

      Experience how efficiency is being reimagined at the “Industrial Metaverse” theme island:

      Decision-makers, planners, technicians, and operators access digital twins together. They simulate decisions, analyze scenarios, and implement even complex projects in a targeted manner during ongoing operations.

      Whether in brownfield or new construction, the Industrial Metaverse creates new opportunities for industrial transformation. Existing and new infrastructures are intelligently networked, proactively optimized, and raised to a new level of performance. In existing plants in particular, this can be achieved without long downtimes or costly new purchases.

      This enables companies to actively address the megatrends facing industry: the shortage of skilled workers, deglobalization, increasing pressure to innovate and reduce costs, and the growing demand for sustainability.

      The Industrial Metaverse is becoming the central lever for efficiency, resilience, and future viability.

  • Focus areas:
      • AI in the loop: data-driven and adaptive
        Use of adaptive systems for continuous optimization of planning, operation, and maintenance
      • Cognitive robots in the production environment
        Autonomous, context-aware systems trained with domain-specific foundation models
      • Use of AI-supported assistants (“co-pilots”)
        Digital assistants to support skilled workers in maintenance, planning, operation, and decision-making
      • Digital twin 2.0 in products and processes
        Virtual images across all life phases – networked, interactive, simulation-capable
      • IT/OT networking and lifelong digital twins
        Consistent use of operating and sensor data across the entire product and plant life cycle
      • Networked data platforms for planning, operation, and optimization
        Common database for greater transparency, efficiency, and proactive action
      • Real-time simulation and validation
        Decisions can be tested and validated digitally before they are implemented in real life

PUBLIC SOLUTIONS

Digital technologies create new opportunities for livable regions, modern administrations, and sustainable infrastructures.

 

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      The digital transformation is creating new opportunities for government and society. With the Federal Ministry for Digitalization and Transformation (BMDS), the modernization of administration and public infrastructure is becoming a greater focus. In light of growing demands and scarce resources, municipalities, authorities, and public enterprises are looking ahead. Processes must be rethought, digital solutions consistently utilized, and citizen-centricity actively shaped.

      EDAG supports public sector players on their path to digital transformation – from strategy and development to concrete implementation. The focus is on efficient administrative processes, networked infrastructures, and data-based decision-making.
      Whether automated processes, predictive environmental monitoring, or smart mobility services: we show how IoT systems, digital platforms, and user-centric solutions create real added value—sustainably, resiliently, and future-proof.

      Real-world use cases clearly demonstrate that targeted use of digitalization strengthens innovation, decision-making, and citizen focus—even in areas such as healthcare, energy, and mobility.

  • Focus areas:
      • Administrative digitization:
        Efficient processes, digital citizen services, and modern specialist applications to reduce the burden on staff and resources
      • Data networking and visualization:
        Smart city dashboards for real-time analysis, planning, and control of municipal data
      • Data platforms and IoT applications:
        Integration of sensor, environmental, energy, and traffic data for automated processes and monitoring
      • Heavy rain early warning system:
        Early detection of local heavy rain and flood situations, targeted alerts and initiation of protective measures
      • Mobility solutions for cities:
        Intermodal mobility stations, networked apps and digital services for sustainable urban mobility

Industrial Metaverse: Experience the future today

Experience practical use cases related to the Industrial Metaverse.

Digital Twin 2.0 and AI in product development

Accelerate innovation with Digital Twin 2.0 and AI

Consistent data models, automated simulations, and integration into the Industrial Metaverse make your product development faster, more robust, and future-proof.

 

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      Digital Twin 2.0 creates a consistent image of the product from the initial design to series production. All domains work on a uniform database. Mechanics, electrics, software, and simulation are fully networked.

      AI models analyze real loads, identify weak points at an early stage, and automatically develop optimized variants. The direct connection to the Industrial Metaverse allows cross-functional tests to be carried out in realistic digital environments.

      The result: more efficient development times, high speed of innovation, and shorter time-to-market

Software-defined automation

Cognitive robots are trained in realistic conditions in virtual environments such as Omniverse Isaac Sim. With the help of reinforcement learning, sensor simulation, and Sim2Real strategies, they learn how to grasp, navigate, and interact. They then use the skills they have learned to work flexibly in production.

 

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      The training of complex robot functions is increasingly taking place virtually. In photorealistic simulation environments such as Omniverse, Cosmos, and Isaac Sim, digital twins with realistic sensor technology and typical production environments are created. They form the basis for repeatable training and test scenarios with high practical relevance.

      Reinforcement learning, imitation learning, and foundation models enable robots to independently learn complex tasks such as gripping, navigating, or voice interaction. The acquired skills are reliably transferred to real hardware using Sim2Real strategies – for example, to robot arms with grippers for assembly processes.

      The result: standardized, highly flexible, AI-controlled robot systems for maximum adaptability in real-world operations.

Intelligent process control with AI – closed-loop quality in real time

An adaptive system collects and analyzes real process and quality data from production, identifies causes of errors, and provides targeted recommendations for action. Based on this analysis, maintenance measures are initiated and parameters and robot movements are automatically adjusted. Together with Wandelbots and Siemens, this results in software-driven automation that continuously learns and adapts flexibly to new conditions.

 

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      In smart production, the quality of products and processes is of central importance. With the help of modern sensor technology, relevant process parameters such as vibration, pressure, forces, and visual information from camera-based vision systems, etc., are recorded during production. This data provides the basis for an AI-supported system that immediately detects deviations, analyzes causes, and derives concrete recommendations for action.

      This enables well-informed, data-based decisions: production parameters and robot paths are automatically adjusted, and maintenance is informed of necessary measures in a targeted manner. This leads to short response times, stable and optimized processes, and the avoidance of downtime and manual rework.

      Thanks to standardized interfaces—for example, to platforms such as Wandelbot's NOVA or Siemens Industrial Edge—new solutions and functions can be integrated with minimal effort.

      The result: adaptive, reliable production with maximum process stability and consistently high quality.

Maintenance reimagined with AR and digital twins

Technicians receive precise, visual instructions for repairing a product on site via AR glasses. The instructions are directly linked to the digital twin, enabling fast, error-free implementation without additional training.

 

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      The AR glasses display affected components, necessary work steps, and safety-related information directly in the field of view. This is based on the digital twin, which maps the product in real time and visualizes the detected errors in context.

      Parts lists, instructions, and assembly notes appear exactly where they are needed. This enables even less experienced employees to perform complex maintenance tasks safely and efficiently.

      The result: Thanks to the connection to systems such as CMMS or ERP, the entire process is automatically documented and available for later evaluation. This creates a scalable, digital maintenance solution across the entire product lifecycle.

Speed up maintenance, avoid downtime – with autonomous AI agents

An autonomous AI continuously analyzes all diagnostic data, compares it in real time between networked robots and their digital twin, and immediately detects any deviations. If a defect is identified, the AI automatically selects the appropriate replacement part, checks its availability, and initiates the order and maintenance request. Integrated into ERP and supply chains, response times and manual effort are significantly reduced, unplanned line downtime is avoided, and thanks to the product app and dashboard, everyone involved is kept informed about every step in a transparent manner.

 

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      An autonomous AI agent continuously analyzes sensor and telemetry data and independently detects defects in machines or robots. The digital twin serves as a precise reference, supplemented by a comparison between the robots via optional swarm intelligence, so that the cause, affected component, and variant configuration can be determined with pinpoint accuracy.

      The system then automatically selects the appropriate spare part, checks stock levels and supply chains in real time, and immediately initiates the ordering and maintenance process. At the same time, it optimizes the processes on the production line and keeps those responsible up to date via the product app – including step-by-step installation instructions, which can be sent directly to the AR headset on request.

      The result: Thanks to seamless integration into ERP and logistics systems, the entire maintenance process runs fully automatically and without interruptions. Unplanned downtime is avoided, coordination requirements and manual effort are reduced, and all processes become measurably faster.

More efficient projects: better decisions with a digital project system

EDAG digitizes the entire project process – from site selection to implementation. All data flows into a central model that improves planning quality, resource utilization, and decision-making processes. The result: less friction, more transparency, and a robust digital twin for operations.

 

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      Throughout the entire project, location information, layout plans, timelines, and resources are consistently maintained in the digital model. Simulations and real-time data from implementation continuously supplement the system—the model grows with it.

      At the end of the process, a complete, dynamic digital twin is created. This can be used directly for commissioning, monitoring, and optimization. The asset is seamlessly integrated into operations and can be continuously maintained by EDAG as a managed service.

      Typical functions include KPI analyses, predictive maintenance, integration of new variants, and connection to existing ERP and MES systems.

      The result: end-to-end transparency, a controllable project system, and the basis for continuous optimization in the Industrial Metaverse.

WITH EDAG, YOU HAVE A STRONG PARTNER AT YOUR SIDE: WE SUPPORT YOU IN LEADING YOUR COMPANY SUCCESSFULLY INTO THE FUTURE.

 

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